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Sample records for adaptive notch filters

  1. Regularized Adaptive Notch Filters for Acoustic Howling Suppression

    DEFF Research Database (Denmark)

    Gil-Cacho, Pepe; van Waterschoot, Toon; Moonen, Marc

    2009-01-01

    In this paper, a method for the suppression of acoustic howling is developed, based on adaptive notch filters (ANF) with regularization (RANF). The method features three RANFs working in parallel to achieve frequency tracking, howling detection and suppression. The ANF-based approach to howling...

  2. Unbalance vibration suppression for AMBs system using adaptive notch filter

    Science.gov (United States)

    Chen, Qi; Liu, Gang; Han, Bangcheng

    2017-09-01

    The unbalance of rotor levitated by active magnetic bearings (AMBs) will cause synchronous vibration which greatly degrade the performance at high speeds in the rotating machinery. To suppress the unbalance vibration without angular velocity information, a novel modified adaptive notch filter (ANF) with phase shift in the AMBs system is presented in this study. Firstly, a 4-degree-of-freedom (DOF) radial unbalanced AMB rotor system is described and analyzed, and the solution of rotor vibration displacement is compared with the experimental data to verify the preciseness of the dynamic model. Then the principle and structure of the proposed notch filter used for the frequency estimation and online identification of synchronous component are presented. As well, the convergence property of the algorithm is investigated. In addition, the stability analysis of the closed-loop AMB system with the proposed ANF is conducted. Simulation and experiments on an AMB driveline system demonstrate the effectiveness and the adaptive characteristics of the proposed ANF on the elimination of synchronous controlled current in a widely operating speed range.

  3. [Research of adaptive notch filter based on QRD-LS algorithm for power line interference in ECG].

    Science.gov (United States)

    Wang, Shuyan; Dong, Jian; Guan, Xin

    2008-10-01

    In this paper, an adaptive notch filter based on QRD-LS algorithm for power line interference in ECG is researched. It can automatically eliminate the power line interference in order to improve the signal-to-interference ratio. Furthermore, QLD-LS algorithm, which is recursive least-squares minimization using systolic arrays, is employed to adjust the weight vector. Compared with the adaptive notch filter based on LMS (least mean square) algorithm, it has good robustness. Simulation examples confirm the results. QRD-LS adaptive notch filter has better performance in comparison with LMS method.

  4. Superconducting notch filter

    Energy Technology Data Exchange (ETDEWEB)

    Pang, C S; Falco, C M; Kampwirth, R T; Schuller, I K; Hudak, J J; Anastasio, T A

    1979-01-01

    Results of a preliminary investigation of a superconducting notch filter for possible application in the 2 to 30 MHz high frequency (HF) communication band are presented. The circuit was successfully implemented using planar geometry so that closed cycle refrigeration could be used to cool circuits fabricated from high T/sub c/ Nb/sub 3/Sn or Nb/sub 3/Ge thin films. In the present design, circuit Q's of about 2 x 10/sup 3/ were obtained with 50-ohm source and output impedance. (TFD)

  5. Adaptive notch filter for removal of coherent noise from infrared scanner data

    Science.gov (United States)

    Jaggi, Sandeep

    1991-11-01

    This paper addresses the use of an adaptive noise canceling technique to eliminate the coherent noise generated in scanner data. The technique is based on a Finite Impulse Response (FIR) adaptive noise canceler. A two-weight FIR filter is used to adaptively learn the characteristics of a sinusoid. This sinusoid is then removed from the data. The least Mean Squares (LMS) algorithm is used to converge to the coefficients of the adaptive filter during the learning process. An image corrupted with a single frequency periodic noise is used for investigating the algorithm. It is observed that the efficiency of the algorithm is dependent on the convergence gains and the initial positioning of the weights of the FIR filter. Because of the computational simplicity of the algorithm, it is possible to implement this in real-time mode.

  6. Notch filters for port-Hamiltonian systems

    NARCIS (Netherlands)

    Dirksz, D.A.; Scherpen, J.M.A.; van der Schaft, A.J.; Steinbuch, M.

    2012-01-01

    In this paper a standard notch filter is modeled in the port-Hamiltonian framework. By having such a port-Hamiltonian description it is proven that the notch filter is a passive system. The notch filter can then be interconnected with another (nonlinear) port-Hamiltonian system, while preserving the

  7. Compact microstrip bandpass filter with tunable notch

    DEFF Research Database (Denmark)

    Christensen, Silas; Zhurbenko, Vitaliy; Johansen, Tom Keinicke

    2014-01-01

    Two different designs combining a bandpass and a notch filter are developed to operate in the receiving band from 350–470 MHz. The bandpass filter is designed from a simple structure, by use of only four short circuited stubs and a half wavelength transmission line connecting the stubs. The tunable...

  8. Improved Notch Filter For Synchronous-Response Control

    Science.gov (United States)

    Johnson, Bruce G.; Downer, James R.; Eisenhaure, David B.; Hockney, Richard; Misovec, Kathleen

    1991-01-01

    Tracking differential-notch filter (TDNF) developed to retain good synchronous-response performance of notch filter, but with vastly improved stability properties. Measurement error perfectly filtered from feedback signal used to drive compensator. Provides good stability of simple lead/lag compensator combined with good synchronous-response performance gained by addition of notch filter.

  9. Digital notch filter based active damping for LCL filters

    DEFF Research Database (Denmark)

    Yao, Wenli; Yang, Yongheng; Zhang, Xiaobin

    2015-01-01

    LCL filters are widely used in Pulse Width Modulation (PWM) inverters. However, it also introduces a pair of unstable resonant poles that may challenge the controller stability. The passive damping is a convenient possibility to tackle the resonance problem at the cost of system overall efficiency....... In contrast, the active damping does not require any dissipation elements, and thus has become of increasing interest. As a result, a vast of active damping solutions have been reported, among which multi-loop control systems and additional sensors are necessary, leading to increased cost and complexity....... In this paper, a notch filter based active damping without the requirement of additional sensors is proposed, where the inverter current is employed as the feedback variable. Firstly, a design method of the notch filter for active damping is presented. The entire system stability has then been investigated...

  10. On-line identification, flutter testing and adaptive notching of ...

    Indian Academy of Sciences (India)

    The second technique is based on decoupling rigid-body and structural modes of the aircraft by means of a Kalman filter and using rigid-body estimates in the feedback control loop. The difference between the two approaches is that on-line identification and adaptive notching in the first approach are entirely based on the ...

  11. Broadband notch filter design for millimeter-wave plasma diagnostics

    DEFF Research Database (Denmark)

    Furtula, Vedran; Michelsen, Poul; Leipold, Frank

    2010-01-01

    Notch filters are integrated in plasma diagnostic systems to protect millimeter-wave receivers from intensive stray radiation. Here we present a design of a notch filter with a center frequency of 140 GHz, a rejection bandwidth of ∼ 900 MHz, and a typical insertion loss below 2 dB in the passband...

  12. Thomson scattering using an atomic notch filter

    Science.gov (United States)

    Bakker, L. P.; Freriks, J. M.; de Hoog, F. J.; Kroesen, G. M. W.

    2000-05-01

    One of the biggest problems in performing Thomson scattering experiments in low-density plasmas is the very high stray light intensity in comparison with the Thomson scattering intensity. This problem is especially present in fluorescent lamps because of the proximity of the glass tube. We propose an atomic notch filter in combination with a dye laser and an amplified spontaneous emission (ASE) filter as a way of reducing this stray light level. The dye laser produces 589 nm radiation which is guided through the ASE filter that increases the spectral purity. The beam is then guided in the fluorescent lamp, where the Thomson scattering process takes place. The scattered light is collected and guided through a sodium vapor absorption cell, where the stray light is absorbed because it is resonant to the D2 transition of sodium. The spectral width of the Thomson scattering light is large enough to be transmitted through the absorption cell. In this way we only measure the Thomson scattering light.

  13. Wavelet Transform Based Filter to Remove the Notches from Signal Under Harmonic Polluted Environment

    Science.gov (United States)

    Das, Sukanta; Ranjan, Vikash

    2017-12-01

    The work proposes to annihilate the notches present in the synchronizing signal required for converter operation appearing due to switching of semiconductor devices connected to the system in the harmonic polluted environment. The disturbances in the signal are suppressed by wavelet based novel filtering technique. In the proposed technique, the notches in the signal are determined and eliminated by the wavelet based multi-rate filter using `Daubechies4' (db4) as mother wavelet. The computational complexity of the adapted technique is very less as compared to any other conventional notch filtering techniques. The proposed technique is developed in MATLAB/Simulink and finally validated with dSPACE-1103 interface. The recovered signal, thus obtained, is almost free of the notches.

  14. Reconfigurable UWB Bandpass Filter with Flexible Notch Characteristics

    Science.gov (United States)

    Dhwaj, Kirti

    The thesis reports a compact tunable ultra-wideband (UWB) notch filter using hybrid microstrip and coplanar waveguide (CPW) structure. The tunable notch is implemented to filter out the wireless local area network (WLAN) channels from 5GHz to 6GHz. The proposed structure utilizes the resonance of open ended stubs to achieve transmission zeroes in the filter passband. Varactors and by-pass capacitors are then introduced for dynamic tunability of notch. Further, the electromagnetic decoupling of the two resonators leads to tunable bandwidth of notch. DC bias circuitry is implemented to control the varactor capacitances. Rejection levels up to 25 dB are attained using this technique while maintaining insertion loss levels below 2.5 dB in the passband. The reconfigurability of bandwidth is shown by maintaining a constant bandwidth of 150 MHz across the WLAN band for the notch. The filter achieves an excellent wide bandwidth (from 2.5 GHz to 8.5 GHz) using multimode-resonator (MMR) based topology which makes the filter one wavelength long at the central frequency.

  15. A novel notch filter based on block copolymer photonic crystal

    Science.gov (United States)

    Hara, Shigeo; Yamanaka, Takahiko; Hirohata, Toru; Niigaki, Minoru

    2011-11-01

    We demonstrate filtering characteristics of a polymer notch filter (PNF) with highly-ordered microphase-separated structure of block copolymers (BCPs). This PNF is characterized by an Optical Density > 5 blocking at the center wavelength and narrow blocking full bandwidth of 8 nm. Moreover, the wavelength is easily tuned by blending two BCPs with different molecular-weight. A low frequency Raman shift of 200 cm-1 are, in fact, detected with a sufficient resolution by using this filter in Raman spectroscopy.

  16. 105 GHz Notch Filter Design for Collective Thomson Scattering

    DEFF Research Database (Denmark)

    Furtula, Vedran; Michelsen, Poul; Leipold, Frank

    2011-01-01

    A millimeter-wave notch filter with 105-GHz center frequency, >20-GHz passband coverage, and 1-GHz rejection bandwidth has been constructed. The design is based on a fundamental rectangular waveguide with cylindrical cavities coupled by narrow iris gaps, i.e., small elongated holes of negligible ...

  17. Adaptive digital filters

    CERN Document Server

    Kovačević, Branko; Milosavljević, Milan

    2013-01-01

    Adaptive Digital Filters” presents an important discipline applied to the domain of speech processing. The book first makes the reader acquainted with the basic terms of filtering and adaptive filtering, before introducing the field of advanced modern algorithms, some of which are contributed by the authors themselves. Working in the field of adaptive signal processing requires the use of complex mathematical tools. The book offers a detailed presentation of the mathematical models that is clear and consistent, an approach that allows everyone with a college level of mathematics knowledge to successfully follow the mathematical derivations and descriptions of algorithms.   The algorithms are presented in flow charts, which facilitates their practical implementation. The book presents many experimental results and treats the aspects of practical application of adaptive filtering in real systems, making it a valuable resource for both undergraduate and graduate students, and for all others interested in m...

  18. Switchable microwave photonic filter between high Q bandpass filter and notch filter with flat passband based on phase modulation.

    Science.gov (United States)

    Yu, Yuan; Xu, Enming; Dong, Jianji; Zhou, Lina; Li, Xiang; Zhang, Xinliang

    2010-11-22

    We propose and demonstrate a novel switchable microwave photonic filter based on phase modulation. Both a microwave high Q bandpass filter and a microwave notch filter with flat passband are achieved respectively. And the switchability between them by tuning the two tunable optical bandpass filters is demonstrated. We also present a theoretical model and analytical expression for the proposed scheme. A frequency response of a high Q bandpass filter with a Q factor of 327 and a rejection ratio of exceeding 42 dB, and a frequency response of a notch filter with flat passband with a rejection ratio exceeding 34 dB are experimentally obtained. The operation frequency of microwave photonic filter is around 20 GHz.

  19. Self-collimation-based photonic crystal notch filters

    Science.gov (United States)

    Lee, Sun-Goo; Kim, Kap-Joong; Kim, Seong-Han; Kee, Chul-Sik

    2017-05-01

    We introduce a design concept of an optical notch filter (NF) utilizing two perfectly reflecting mirrors and a beam splitter. Based on the new design concept, a photonic crystal (PC)-NF based on the self-collimation phenomenon in a two-dimensional PC is proposed and studied through finite-difference time-domain simulations and experimental measurements in a microwave region. The transmission properties of the self-collimation-based PC-NF were demonstrated to be controlled by adjusting the values of parameters such as the radius of rods in the line-defect beam splitter, distance between the two perfectly reflecting mirrors, and radius of rods on the outermost surface of the perfectly reflecting mirrors. Our results indicate that the proposed design concept could provide a new approach to manipulate light propagation, and the PC-NF could increase the applicability of the self-collimation phenomenon in a PC.

  20. Hybrid Microstrip/Slotline Ultra-Wideband Bandpass Filter with a Controllable Notch Band

    Directory of Open Access Journals (Sweden)

    Xuehui Guan

    2017-01-01

    Full Text Available An ultra-wideband (UWB bandpass filter (BPF with a controllable notch band is presented by using hybrid microstrip/slotline structure. Firstly, a slotline resonator with symmetrically loaded stubs is fed by two microstrip lines to produce a UWB bandpass filtering response. Secondly, a microstrip triangular loop resonator is externally loaded over the slotline, and a notch band is introduced in the UWB passband. The notch band is determined by the perimeter of the loop resonator. Thirdly, two patches are added as the perturbation element to the corners of the microstrip resonator to excite a pair of degenerate modes. Bandwidth of the notch band can be tuned by properly selecting the patch size. Circuit model for the microstrip resonator loaded slotline is given and studied. Finally, the filter is designed, simulated, and measured. Measured results have agreed well with the simulated ones, demonstrating that a UWB filter with a controllable notch band has been realized.

  1. Self-commissioning notch filter for active damping in three phase LCL-filter based grid converters

    DEFF Research Database (Denmark)

    Alzola, Rafael Pena; Liserre, Marco; Blaabjerg, Frede

    2013-01-01

    LCL-filters are used to mitigate the harmonic current content in grid converters. The LCL-filter resonance must be damped in order to avoid stability problems in the current control. Active damping avoids resistors at the expense of increased control complexity. Large grid impedance variations can...... of exciting the LCL-filter. However, the notch filter tuning requires considerable design effort and the variations in the resonance frequency limit the LCL-filter robustness. This paper proposes a simple tuning procedure for the notch filter that results in proper robustness. In order to cope with the grid...

  2. Adaptive filtering and change detection

    CERN Document Server

    Gustafsson, Fredrik

    2003-01-01

    Adaptive filtering is a classical branch of digital signal processing (DSP). Industrial interest in adaptive filtering grows continuously with the increase in computer performance that allows ever more conplex algorithms to be run in real-time. Change detection is a type of adaptive filtering for non-stationary signals and is also the basic tool in fault detection and diagnosis. Often considered as separate subjects Adaptive Filtering and Change Detection bridges a gap in the literature with a unified treatment of these areas, emphasizing that change detection is a natural extensi

  3. Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide

    DEFF Research Database (Denmark)

    Xiao, Binggang; Li, Sheng-Hua; Xiao, Sanshui

    2016-01-01

    Spoof surface plasmon polaritons based notch filter for ultra-wideband microwave waveguide is proposed. Owing to subwavelength confinement, such a filter has advantage in the structure size without sacrificing the performance. The spoof SPP based notch is introduced to suppress the WLAN...... and satellite communication signals. Due to planar structures proposed here, it is easy to integrate in the microwave integrated systems, which can play an important role in the microwave communication circuit and system....

  4. 160 Gb/s Raman-assisted notch-filtered XPM wavelength conversion and transmission

    DEFF Research Database (Denmark)

    Galili, Michael; Oxenløwe, Leif Katsuo; Mulvad, Hans Christian Hansen

    2007-01-01

    In-line wavelength conversion of 160 Gb/s data by Raman-assisted notch-filtered XPM is demonstrated for 130 km total transmission. The improvement in system performance from applying Raman gain during conversion is shown.......In-line wavelength conversion of 160 Gb/s data by Raman-assisted notch-filtered XPM is demonstrated for 130 km total transmission. The improvement in system performance from applying Raman gain during conversion is shown....

  5. Frequency agile microwave photonic notch filter with anomalously high stopband rejection.

    Science.gov (United States)

    Marpaung, David; Morrison, Blair; Pant, Ravi; Eggleton, Benjamin J

    2013-11-01

    We report a novel class microwave photonic (MWP) notch filter with a very narrow isolation bandwidth (10 MHz), an ultrahigh stopband rejection (>60 dB), a wide frequency tuning (1-30 GHz), and flexible bandwidth reconfigurability (10-65 MHz). This performance is enabled by a new concept of sideband amplitude and phase controls using an electro-optic modulator and an optical filter. This concept enables energy efficient operation in active MWP notch filters, and opens up a pathway toward enabling low-power nanophotonic devices as high-performance RF filters.

  6. Adaptive filtering prediction and control

    CERN Document Server

    Goodwin, Graham C

    2009-01-01

    Preface1. Introduction to Adaptive TechniquesPart 1. Deterministic Systems2. Models for Deterministic Dynamical Systems3. Parameter Estimation for Deterministic Systems4. Deterministic Adaptive Prediction5. Control of Linear Deterministic Systems6. Adaptive Control of Linear Deterministic SystemsPart 2. Stochastic Systems7. Optimal Filtering and Prediction8. Parameter Estimation for Stochastic Dynamic Systems9. Adaptive Filtering and Prediction10. Control of Stochastic Systems11. Adaptive Control of Stochastic SystemsAppendicesA. A Brief Review of Some Results from Systems TheoryB. A Summary o

  7. Widely tunable microwave photonic notch filter based on slow and fast light effects

    DEFF Research Database (Denmark)

    Xue, Weiqi; Sales, Salvador; Mørk, Jesper

    2009-01-01

    A continuously tunable microwave photonic notch filter at around 30 GHz is experimentally demonstrated and 100% fractional tuning over 360 range is achieved without changing the shape of the spectral response. The tuning mechanism is based on the use of slow and fast light effects in semiconductor...... optical amplifiers assisted by optical filtering....

  8. Notch Filter Analysis and Its Application in Passive Coherent Location Radar (in English

    Directory of Open Access Journals (Sweden)

    Li Ji-chuan

    2015-01-01

    Full Text Available The Normalized Least-Mean-Squares (NLMS algorithm is widely used to cancel the direct and multiple path interferences in Passive Coherent Location (PCL radar systems. This study proposes that the interference cancelation using the NLMS algorithm and the calculation of the radar Cross Ambiguity Function (CAF can be modeled as a notch filter, with the notch located at zero Doppler frequency in the surface of the radar CAF. The analysis shows that the notch’s width and depth are closely related to the step size of the NLMS algorithm. Subsequently, the effect of the notch in PCL radar target detection is analyzed. The results suggest that the detection performance of the PCL radar deteriorates because of the wide notch. Furthermore, the Nonuniform NLMS (NNLMS algorithm is proposed for removing the clutter with the Doppler frequency by using notch filtering. A step-size matrix is adopted to mitigate the low Doppler frequency clutter and lower the floor of the radar CAF. With the step-size matrix, can be obtained notches of different depths and widths in different range units of the CAF, which can filter the low Doppler frequency clutter. In addition, the convergence rate of the NNLMS algorithm is better than that of the traditional NLMS algorithm. The validity of the NNLMS algorithm is verified by experimental results.

  9. Mid-wave infrared narrow bandwidth guided mode resonance notch filter.

    Science.gov (United States)

    Zhong, Y; Goldenfeld, Z; Li, K; Streyer, W; Yu, L; Nordin, L; Murphy, N; Wasserman, D

    2017-01-15

    We have designed, fabricated, and characterized a guided mode resonance notch filter operating in the technologically vital mid-wave infrared (MWIR) region of the electromagnetic spectrum. The filter provides a bandstop at λ≈4.1  μm, with a 12 dB extinction on resonance. In addition, we demonstrate a high transmission background (>80%), less than 6% transmission on resonance, and an ultra-narrow bandwidth transmission notch (10  cm-1). Our filter is optically characterized using angle- and polarization-dependent Fourier transform infrared spectroscopy, and simulated using rigorous coupled-wave analysis (RCWA) with excellent agreement between simulations and our experimental results. Using our RCWA simulations, we are able to identify the optical modes associated with the transmission dips of our filter. The presented structure offers a potential route toward narrow-band laser filters in the MWIR.

  10. Adaptive optical filtering techniques

    Science.gov (United States)

    Psaltis, D.

    1985-05-01

    The purpose of this study was to examine the potential of using optical information processing technology for adaptive antenna beamforming and null steering. The adaptive beamforming/null steering problem consists of estimation of the covariance matrix of the noise field and inversion of the covariance matrix to obtain the antenna element weights which optimize the antenna's directional characteristics (gain pattern). This report examines the adaptive beamforming/nulling problem in view of the capabilities of optics and identifies areas where optics can be used to benefit. Benefits and drawbacks of various optical implementations of open and closed loop adaptive algorithms are discussed as well as the issues involved with optically processing digital binary numbers.

  11. Fibre Optic Notch Filter For The Antiproton Decelerator Stochastic Cooling System

    CERN Document Server

    Simmonds, Max Vincent John

    2016-01-01

    The project scope included reverse engineering, upgrading, and recovering the operational conditions of an existing fibre optic notch filter. Once operational, tests were to be preformed to confirm the performance of the temperature stabilisation. The end goal is to use said notch filter in the Antiproton Decelerator (AD) facility at CERN to help aid antimatter research. The notch filter was successfully reverse engineered and then documented. Changes were made in order to increase performance and reliability, and also allow easy integration into the AD. An additional phase was added whereby the notch filter was to be controller via a touchscreen computer, situated next to the filter, allowing engineers to set-up each of the electronic devices used. While one of the devices (Motorised Delay Line) can be controlled by the touchscreen computer, the other two cannot.Due to time constraints and difficulties with the Beckhoff TwincatII programming language, the USB devices were not able to be controlled via the To...

  12. A wideband stepped-impedance rectangular-ring resonator bandpass filter with multiple notched bands

    Science.gov (United States)

    Nakhlestani, Amir; Movahhedi, Masoud; Hakimi, Ahmad

    2014-07-01

    A configuration of wideband bandpass filter (BPF) with multiple notched bands is presented. Proposed BPF is based on stepped-impedance resonator. By utilising dual stepped-impedance resonators in folded topology a rectangular-ring resonator is formed. Two notched bands in the passband are achieved without using asymmetrical coupled lines. In other words, the filter configuration is capable of producing notched bands. It should be noted that additional information on filter performance and design is presented. Measurement results are presented to approve propounded filter characteristics. The measured passband of the second proposed filter is from 3.68 to 10.2 GHz with insertion loss of -1.76 dB in the first passband at the centre frequency of 4.45 GHz. The measured notched band frequencies are about 5.45 and 7.95 GHz with rejection of -21.77 and -20.82 dB, respectively. The return loss in the passband is better than -11.4 dB.

  13. Restrictions on TWT Helix Voltage Ripple for Acceptable Notch Filter Performance

    Energy Technology Data Exchange (ETDEWEB)

    Hyslop, B.

    1984-12-01

    An ac ripple on the helix voltage of the 1-2 GHz TWT's creates FM sidebands that cause amplitude and phase modulation of the microwave TWT output signal. A limit of 16 volts peak-to-peak is required for acceptable superconducting notch filter performance.

  14. Thin-film optical notch filter spectacle coatings for the treatment of migraine and photophobia.

    Science.gov (United States)

    Hoggan, Ryan N; Subhash, Amith; Blair, Steve; Digre, Kathleen B; Baggaley, Susan K; Gordon, Jamison; Brennan, K C; Warner, Judith E A; Crum, Alison V; Katz, Bradley J

    2016-06-01

    Previous evidence suggests optical treatments hold promise for treating migraine and photophobia. We designed an optical notch filter, centered at 480nm to reduce direct stimulation of intrinsically photosensitive retinal ganglion cells. We used thin-film technology to integrate the filter into spectacle lenses. Our objective was to determine if an optical notch filter, designed to attenuate activity of intrinsically photosensitive retinal ganglion cells, could reduce headache impact in chronic migraine subjects. For this randomized, double-masked study, our primary endpoint was the Headache Impact Test (HIT-6; GlaxoSmithKline, Brentford, Middlesex, UK). We developed two filters: the therapeutic filter blocked visible light at 480nm; a 620nm filter was designed as a sham. Participants were asked to wear lenses with one of the filters for 2weeks; after 2weeks when no lenses were worn, they wore lenses with the other filter for 2weeks. Of 48 subjects, 37 completed the study. Wearing either the 480 or 620nm lenses resulted in clinically and statistically significant HIT-6 reductions. However, there was no significant difference when comparing overall effect of the 480 and 620nm lenses. Although the 620nm filter was designed as a sham intervention, research published following the trial indicated that melanopsin, the photopigment in intrinsically photosensitive retinal ganglion cells, is bi-stable. This molecular property may explain the unexpected efficacy of the 620nm filter. These preliminary findings indicate that lenses outfitted with a thin-film optical notch filter may be useful in treating chronic migraine. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. A low-loss, continuously tunable microwave notch filter

    DEFF Research Database (Denmark)

    Acar, Öncel; Johansen, Tom Keinicke; Zhurbenko, Vitaliy

    2016-01-01

    The development in high-end microwave transceiver systems toward the software defined radio has brought about the need for tunable frontend filters. Although the problem is being tackled by the microwave community, there still appears to be an unmet demand for practical tunable filter technologies...

  16. Novel Notched UWB Filter Using Stepped Impedance Stub Loaded Microstrip Resonator and Spurlines

    Directory of Open Access Journals (Sweden)

    Ramkumar Uikey

    2015-01-01

    Full Text Available This paper presents a novel ultrawideband (UWB bandpass filter using stepped impedance stub loaded microstrip resonator (SISLMR. The proposed resonator is so formed to allow its four resonant frequencies in the UWB passband, which extends from 3.1 GHz to 10.6 GHz. Moreover, two spurline sections are employed to create a sharp notched-band filter for suppressing the signals of 5 GHz WLAN devices. Experimental results of the fabricated filters are in good agreement with the HFSS simulations and validate the design.

  17. Demonstration of tunable microwave photonic notch filters using slow and fast light effects in semiconductor optical amplifiers

    DEFF Research Database (Denmark)

    Xue, Weiqi; Sales, Salvador; Mørk, Jesper

    2009-01-01

    We introduce a novel scheme based on slow and fast light effects in semiconductor optical amplifiers, to implement a microwave photonic notch filter with ~100% fractional tuning range at a microwave frequency of 30 GHz.......We introduce a novel scheme based on slow and fast light effects in semiconductor optical amplifiers, to implement a microwave photonic notch filter with ~100% fractional tuning range at a microwave frequency of 30 GHz....

  18. Frequency Agile Microwave Photonic Notch Filter in a Photonic Chip

    Science.gov (United States)

    2016-10-21

    Figure 2(b, lower). The measured interferer suppression in this case was 47 dB, limited by the noise floor of the measurements. This paper is in the...kilometers of silica fiber. However, it is worth noting that the length of integrated SBS circuits is orders of magnitude lower than that of fibers...resonance (i.e. 30 MHz). In this work, we achieve a microwave photonic bandpass filter with a flat pass band, sharp edges, and a near rectangular shape

  19. Elimination of Harmonic Force and Torque in Active Magnetic Bearing Systems with Repetitive Control and Notch Filters.

    Science.gov (United States)

    Xu, Xiangbo; Chen, Shao; Liu, Jinhao

    2017-04-04

    Harmonic force and torque, which are caused by rotor imbalance and sensor runout, are the dominant disturbances in active magnetic bearing (AMB) systems. To eliminate the harmonic force and torque, a novel control method based on repetitive control and notch filters is proposed. Firstly, the dynamics of a four radial degrees of freedom AMB system is described, and the AMB model can be described in terms of the translational and rotational motions, respectively. Next, a closed-loop generalized notch filter is utilized to identify the synchronous displacement resulting from the rotor imbalance, and a feed-forward compensation of the synchronous force and torque related to the AMB displacement stiffness is formulated by using the identified synchronous displacement. Then, a plug-in repetitive controller is designed to track the synchronous feed-forward compensation adaptively and to suppress the harmonic vibrations due to the sensor runout. Finally, the proposed control method is verified by simulations and experiments. The control algorithm is insensitive to the parameter variations of the power amplifiers and can precisely suppress the harmonic force and torque. Its practicality stems from its low computational load.

  20. A Self-commissioning Notch Filter for Active Damping in a Three-Phase LCL -Filter-Based Grid-Tie Converter

    DEFF Research Database (Denmark)

    Pena-Alzola, Rafael; Liserre, Marco; Blaabjerg, Frede

    2014-01-01

    LCL-filters are a cost-effective solution to mitigate harmonic current content in grid-tie converters. In order to avoid stability problems, the resonance frequency of LCL-filters can be damped with active techniques that remove dissipative elements but increase control complexity. A notch filter...

  1. Split quaternion nonlinear adaptive filtering.

    Science.gov (United States)

    Ujang, Bukhari Che; Took, Clive Cheong; Mandic, Danilo P

    2010-04-01

    A split quaternion learning algorithm for the training of nonlinear finite impulse response adaptive filters for the processing of three- and four-dimensional signals is proposed. The derivation takes into account the non-commutativity of the quaternion product, an aspect neglected in the derivation of the existing learning algorithms. It is shown that the additional information taken into account by a rigorous treatment of quaternion algebra provides improved performance on hypercomplex processes. A rigorous analysis of the convergence of the proposed algorithms is also provided. Simulations on both benchmark and real-world signals support the approach. Copyright 2009 Elsevier Ltd. All rights reserved.

  2. Inductive Displacement Sensors with a Notch Filter for an Active Magnetic Bearing System

    Directory of Open Access Journals (Sweden)

    Seng-Chi Chen

    2014-07-01

    Full Text Available Active magnetic bearing (AMB systems support rotating shafts without any physical contact, using electromagnetic forces. Each radial AMB uses two pairs of electromagnets at opposite sides of the rotor. This allows the rotor to float in the air gap, and the machine to operate without frictional losses. In active magnetic suspension, displacement sensors are necessary to detect the radial and axial movement of the suspended object. In a high-speed rotating machine equipped with an AMB, the rotor bending modes may be limited to the operating range. The natural frequencies of the rotor can cause instability. Thus, notch filters are a useful circuit for stabilizing the system. In addition, commercial displacement sensors are sometimes not suitable for AMB design, and cannot filter the noise caused by the natural frequencies of rotor. Hence, implementing displacement sensors based on the AMB structure is necessary to eliminate noises caused by natural frequency disturbances. The displacement sensor must be highly sensitive in the desired working range, and also exhibit a low interference noise, high stability, and low cost. In this study, we used the differential inductive sensor head and lock-in amplifier for synchronous demodulation. In addition, an active low-pass filter and a notch filter were used to eliminate disturbances, which caused by natural frequencies. As a consequence, the inductive displacement sensor achieved satisfactory linearity, high sensitivity, and disturbance elimination. This sensor can be easily produced for AMB applications. A prototype of these displacement sensors was built and tested.

  3. Inductive displacement sensors with a notch filter for an active magnetic bearing system.

    Science.gov (United States)

    Chen, Seng-Chi; Le, Dinh-Kha; Nguyen, Van-Sum

    2014-07-15

    Active magnetic bearing (AMB) systems support rotating shafts without any physical contact, using electromagnetic forces. Each radial AMB uses two pairs of electromagnets at opposite sides of the rotor. This allows the rotor to float in the air gap, and the machine to operate without frictional losses. In active magnetic suspension, displacement sensors are necessary to detect the radial and axial movement of the suspended object. In a high-speed rotating machine equipped with an AMB, the rotor bending modes may be limited to the operating range. The natural frequencies of the rotor can cause instability. Thus, notch filters are a useful circuit for stabilizing the system. In addition, commercial displacement sensors are sometimes not suitable for AMB design, and cannot filter the noise caused by the natural frequencies of rotor. Hence, implementing displacement sensors based on the AMB structure is necessary to eliminate noises caused by natural frequency disturbances. The displacement sensor must be highly sensitive in the desired working range, and also exhibit a low interference noise, high stability, and low cost. In this study, we used the differential inductive sensor head and lock-in amplifier for synchronous demodulation. In addition, an active low-pass filter and a notch filter were used to eliminate disturbances, which caused by natural frequencies. As a consequence, the inductive displacement sensor achieved satisfactory linearity, high sensitivity, and disturbance elimination. This sensor can be easily produced for AMB applications. A prototype of these displacement sensors was built and tested.

  4. Waterfall notch-filtering for restoration of acoustic backscatter records from Admiralty Bay, Antarctica

    Science.gov (United States)

    Fonseca, Luciano; Hung, Edson Mintsu; Neto, Arthur Ayres; Magrani, Fábio José Guedes

    2017-08-01

    A series of multibeam sonar surveys were conducted from 2009 to 2013 around Admiralty Bay, Shetland Islands, Antarctica. These surveys provided a detailed bathymetric model that helped understand and characterize the bottom geology of this remote area. Unfortunately, the acoustic backscatter records registered during these bathymetric surveys were heavily contaminated with noise and motion artifacts. These artifacts persisted in the backscatter records despite the fact that the proper acquisition geometry and the necessary offsets and delays were applied during the survey and in post-processing. These noisy backscatter records were very difficult to interpret and to correlate with gravity-core samples acquired in the same area. In order to address this issue, a directional notch-filter was applied to the backscatter waterfall in the along-track direction. The proposed filter provided better estimates for the backscatter strength of each sample by considerably reducing residual motion artifacts. The restoration of individual samples was possible since the waterfall frame of reference preserves the acquisition geometry. Then, a remote seafloor characterization procedure based on an acoustic model inversion was applied to the restored backscatter samples, generating remote estimates of acoustic impedance. These remote estimates were compared to Multi Sensor Core Logger measurements of acoustic impedance obtained from gravity core samples. The remote estimates and the Core Logger measurements of acoustic impedance were comparable when the shallow seafloor was homogeneous. The proposed waterfall notch-filtering approach can be applied to any sonar record, provided that we know the system ping-rate and sampling frequency.

  5. Design of low power DTMOS based FCS and its notch filter application for ECG signals

    OpenAIRE

    UGRANLI, Hatice Gül; YILDIRIM, Melih; KAÇAR, Fırat

    2017-01-01

    Inthis study, p-MOSFETs in floating current source circuit are converted todynamic threshold voltage MOSFET structure and a second order notch filterapplication is carried out by using the DTMOS based FCS circuit. The proposedmodel is simulated in LTSPICE simulator by using Taiwan SemiconductorManufacturing Company 0,18μm CMOS technology. DTMOS structure allows theoperation of the circuit at lower power about 4,95nW. Operating frequency ofnotch filter consisting of the DTMOS-FCS circuit is se...

  6. Miniature Microwave Notch Filters and Comparators Based on Transmission Lines Loaded with Stepped Impedance Resonators (SIRs

    Directory of Open Access Journals (Sweden)

    Lijuan Su

    2015-12-01

    Full Text Available In this paper, different configurations of transmission lines loaded with stepped impedance resonators (SIRs are reviewed. This includes microstrip lines loaded with pairs of SIRs, and coplanar waveguides (CPW loaded with multi-section SIRs. Due to the high electric coupling between the line and the resonant elements, the structures are electrically small, i.e., dimensions are small as compared to the wavelength at the fundamental resonance. The circuit models describing these structures are discussed and validated, and the potential applications as notch filters and comparators are highlighted.

  7. Adaptive Filtering Algorithms and Practical Implementation

    CERN Document Server

    Diniz, Paulo S R

    2013-01-01

    In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner. The main classes of adaptive filtering algorithms are presented in a unified framework, using clear notations that facilitate actual implementation. The main algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Many examples address problems drawn from actual applications. New material to this edition includes: Analytical and simulation examples in Chapters 4, 5, 6 and 10 Appendix E, which summarizes the analysis of set-membership algorithm Updated problems and references Providing a concise background on adaptive filtering, this book covers the family of LMS, affine projection, RLS and data-selective set-membership algorithms as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Several problems are...

  8. A widely tunable microwave photonic notch filter with adjustable bandwidth based on multi-wavelength fiber laser

    Science.gov (United States)

    Li, Xin-yang; Cao, Ye; Xu, Dong; Tong, Zheng-rong; Yang, Jing-peng

    2017-07-01

    A widely tunable microwave photonic notch filter with adjustable bandwidth based on multi-wavelength fiber laser is proposed and demonstrated. The multi-wavelength fiber laser generates the multi-taps of the microwave photonic filter (MPF). In order to obtain notch frequency response, a Fourier-domain optical processor (FD-OP) is introduced to control the amplitude and phase of the optical carrier and phase modulation sidebands. By adjusting the polarization controller (PC), different numbers of taps are got, such as 6, 8, 10 and 12. And the wavelength spacing of the multi-wavelength laser is 0.4 nm. The bandwidth of the notch filter is changed by adjusting the number of taps and the corresponding bandwidths are 4.41 GHz, 3.30 GHz, 2.64 GHz and 2.19 GHz, respectively. With the additional phase shift introduced by FD-OP, the notch position is continuously tuned in the whole free spectral range ( FSR) of 27.94 GHz. The center frequency of the notch filter can be continuously tuned from 13.97 GHz to 41.91 GHz.

  9. Generalized Frequency Domain LMS Adaptive Filter

    Directory of Open Access Journals (Sweden)

    F. Dohnal

    1995-06-01

    Full Text Available The most significant problems of acoustic echo canceller (AEC realizations are high computational complexity and insufficient convergence rate of the applied adaptive algorithms. From the analysis of the frequency domain block adaptive filter [2,3] realization and the modified subband acoustic echo canceller [6] the generalized frequency domain adaptive filter [8,9] has been derived. The result of simulations is demonstrated the efficiency of this algorithm for a stationary noise and real speech signal excitation.

  10. Adaptable Iterative and Recursive Kalman Filter Schemes

    Science.gov (United States)

    Zanetti, Renato

    2014-01-01

    Nonlinear filters are often very computationally expensive and usually not suitable for real-time applications. Real-time navigation algorithms are typically based on linear estimators, such as the extended Kalman filter (EKF) and, to a much lesser extent, the unscented Kalman filter. The Iterated Kalman filter (IKF) and the Recursive Update Filter (RUF) are two algorithms that reduce the consequences of the linearization assumption of the EKF by performing N updates for each new measurement, where N is the number of recursions, a tuning parameter. This paper introduces an adaptable RUF algorithm to calculate N on the go, a similar technique can be used for the IKF as well.

  11. DC-pass filter design with notch filters superposition for CPW rectenna at low power level

    Science.gov (United States)

    Rivière, J.; Douyère, A.; Alicalapa, F.; Luk, J.-D. Lan Sun

    2016-03-01

    In this paper the challenging coplanar waveguide direct current (DC) pass filter is designed, analysed, fabricated and measured. As the ground plane and the conductive line are etched on the same plane, this technology allows the connection of series and shunt elements to the active devices without via holes through the substrate. Indeed, this study presents the first step in the optimization of a complete rectenna in coplanar waveguide (CPW) technology: key element of a radio frequency (RF) energy harvesting system. The measurement of the proposed filter shows good performance in the rejection of F0=2.45 GHz and F1=4.9 GHz. Additionally, a harmonic balance (HB) simulation of the complete rectenna is performed and shows a maximum RF-to-DC conversion efficiency of 37% with the studied DC-pass filter for an input power of 10 µW at 2.45 GHz.

  12. Adaptivni digitalni filtri / Adaptive digital filters

    Directory of Open Access Journals (Sweden)

    Dragan Petković

    2002-01-01

    Full Text Available Rad opisuje osnove funkcionisanja adaptivnih filtara. U uvodnim razmatranjima obra-đene su osnove matematičke obrade diskretnih signala i z-transformacije kod adaptivnih filtara. Izložen je Wienerov problem filtracije. Predstavljeni su CCL petlja i Widrow-Hoffov LMS algoritam i razmotrena brzina konvergencije adaptivnih filtara. Praktično je realizova-na CCL petlja sa osvrtom na brzinu konvergencije. / The paper describes the basis of adaptive filter functioning. The first considerations deal with the mathematical processing of discrete signals and the Z-transform in adaptive filters. The Wieners filter processing problem was exposed. The Correlation Canceler Loop (CCL was presented as well as the Widrow-Hoffs adaptive Least Mean Squares (LMS step-by-step procedure. The convergence rate of adaptive filters was considered as well. The CCL simulations were obtained pointing out the convergence rate.

  13. Performance Analysis of LMS Adaptive FIR Filter and RLS Adaptive FIR Filter for Noise Cancellation

    OpenAIRE

    Jyotsna Yadav; Mukesh Kumar; Rohini Saxena; Jaiswal, A K

    2013-01-01

    Interest in adaptive filters continues to grow as they begin to find practical real-time applications in areas such as channel equalization, echo cancellation, noise cancellation and many other adaptive signal processing applications. The key to successful adaptive signal processing understands the fundamental properties of adaptive algorithms such as LMS, RLS etc. Adaptive filter is used for the cancellation of the noise component which is overlap with undesired si...

  14. New LMS adaptive filter for GPR processing

    Science.gov (United States)

    Dube, F. N.; Devlin, John C.

    2000-04-01

    The DFT method popular in GPR processing assumes that data is infinite outside a given interval. The selection of a finite time interval and of the orthogonal trigonometric basis over a given interval means that only those frequencies which coincide with the basis will project onto a single basis vector. The rest of the frequency set will give nonzero projections on the entire basis set [harris, 1978]. The finite data set is obtained by windowing an infinite data sequence. The assumption is that the unmeasured data is zero and this is not true. When the power of the signal is concentrated on a narrow BW this operation spreads that power into adjacent frequency regions. This phenomenon is called spectral leakage. Leakage affects power estimation, resolution, dynamic range, implementation and detectability of a sinusoidal component. Parametric methods can be used to describe the process that creates a signal. A priori knowledge is required to extrapolate the information from the input signal. This approach eliminates spectral leakage problems. Parametric methods create a model that use a number of parameters to describe the process that create the signal under observation. Adaptive filters are parametric and iterative, theses filters respond to the input by changing their model parameters. The number of samples used at the input is small, however the samples are stored in memory so that the parameters obtained from an estimate are statistically combined with those of the previous estimates. This gives an accurate reading over several iterations. To date the closed loop adaptive filters have been used more commonly in radar signal processing. The closed loop adaptive filters have a feedback factor. One of the main disadvantages of closed loop adaptive filters are firstly the need for continual optimization and secondly instability. The second little known group of adaptive filters are called open loop adaptive filters. These filters differ from open loop ADF in that

  15. Adaptive filtering primer with Matlab

    CERN Document Server

    Poularikas, Alexander D

    2006-01-01

    INTRODUCTIONSignal ProcessingAn ExampleOutline of the TextDISCRETE-TIME SIGNAL PROCESSINGDiscrete Time SignalsTransform-Domain Representation of Discrete-Time SignalsThe Z-TransformDiscrete-Time SystemsProblemsHints-Solutions-SuggestionsRANDOM VARIABLES, SEQUENCES, AND STOCHASTIC PROCESSESRandom Signals and DistributionsAveragesStationary ProcessesSpecial Random Signals and Probability Density FunctionsWiener-Khinchin RelationsFiltering Random ProcessesSpecial Types of Random ProcessesNonparametric Spectra EstimationParametric Methods of power Spectral EstimationProblemsHints-Solutions-SuggestionsWIENER FILTERSThe Mean-Square ErrorThe FIR Wiener FilterThe Wiener SolutionWiener Filtering ExamplesProblemsHints-Solutions-SuggestionsEIGENVALUES OF RX - PROPERTIES OF THE ERROR SURFACEThe Eigenvalues of the Correlation MatrixGeometrical Properties of the Error SurfaceProblemsHints-Solutions-SuggestionsNEWTON AND STEEPEST-DESCENT METHODOne-Dimensional Gradient Search MethodSteepest-Descent AlgorithmProblemsHints-Sol...

  16. Adaptive Filter Design Using Discrete Orthogonal Functions

    Science.gov (United States)

    1992-03-01

    polynomials; Iaguerre polynomials. Jacobi polynom ia Is: aelait .%l:1 tal ilters; lattice filter 19 ABSTRACT (continue on reverse if necessary and identify by...Advisor i C.- / . . / .- - Roberto Cristi, Second Reader Michael A. Morgan. Chairniai l)ep:irtment of Electrical and Computer Engineering ii ABSTRACT...discrete Legendre, Laguerre, and Jacobi polynomials, and backward prediction-error polynomials from a lattice structure. The adaptive filter weights

  17. Adaptive filtering for the lattice Boltzmann method

    Science.gov (United States)

    Marié, Simon; Gloerfelt, Xavier

    2017-03-01

    In this study, a new selective filtering technique is proposed for the Lattice Boltzmann Method. This technique is based on an adaptive implementation of the selective filter coefficient σ. The proposed model makes the latter coefficient dependent on the shear stress in order to restrict the use of the spatial filtering technique in sheared stress region where numerical instabilities may occur. Different parameters are tested on 2D test-cases sensitive to numerical stability and on a 3D decaying Taylor-Green vortex. The results are compared to the classical static filtering technique and to the use of a standard subgrid-scale model and give significant improvements in particular for low-order filter consistent with the LBM stencil.

  18. Partial update least-square adaptive filtering

    CERN Document Server

    Xie, Bei

    2014-01-01

    Adaptive filters play an important role in the fields related to digital signal processing and communication, such as system identification, noise cancellation, channel equalization, and beamforming. In practical applications, the computational complexity of an adaptive filter is an important consideration. The Least Mean Square (LMS) algorithm is widely used because of its low computational complexity (O(N)) and simplicity in implementation. The least squares algorithms, such as Recursive Least Squares (RLS), Conjugate Gradient (CG), and Euclidean Direction Search (EDS), can converge faster a

  19. Design of a Broadband Band-Pass Filter with Notch-Band Using New Models of Coupled Transmission Lines

    OpenAIRE

    Navid Daryasafar; Somaye Baghbani; Mohammad Naser Moghaddasi; Ramezanali Sadeghzade

    2014-01-01

    We intend to design a broadband band-pass filter with notch-band, which uses coupled transmission lines in the structure, using new models of coupled transmission lines. In order to realize and present the new model, first, previous models will be simulated in the ADS program. Then, according to the change of their equations and consequently change of basic parameters of these models, optimization and dependency among these parameters and also their frequency response are attended and results...

  20. A Rapid Introduction to Adaptive Filtering

    CERN Document Server

    Vega, Leonardo Rey

    2013-01-01

    In this book, the authors provide insights into the basics of adaptive filtering, which are particularly useful for students taking their first steps into this field. They start by studying the problem of minimum mean-square-error filtering, i.e., Wiener filtering. Then, they analyze iterative methods for solving the optimization problem, e.g., the Method of Steepest Descent. By proposing stochastic approximations, several basic adaptive algorithms are derived, including Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS) and Sign-error algorithms. The authors provide a general framework to study the stability and steady-state performance of these algorithms. The affine Projection Algorithm (APA) which provides faster convergence at the expense of computational complexity (although fast implementations can be used) is also presented. In addition, the Least Squares (LS) method and its recursive version (RLS), including fast implementations are discussed. The book closes with the discussion of severa...

  1. Design of a broadband band-pass filter with notch-band using new models of coupled transmission lines.

    Science.gov (United States)

    Daryasafar, Navid; Baghbani, Somaye; Moghaddasi, Mohammad Naser; Sadeghzade, Ramezanali

    2014-01-01

    We intend to design a broadband band-pass filter with notch-band, which uses coupled transmission lines in the structure, using new models of coupled transmission lines. In order to realize and present the new model, first, previous models will be simulated in the ADS program. Then, according to the change of their equations and consequently change of basic parameters of these models, optimization and dependency among these parameters and also their frequency response are attended and results of these changes in order to design a new filter are converged.

  2. Design of a Broadband Band-Pass Filter with Notch-Band Using New Models of Coupled Transmission Lines

    Directory of Open Access Journals (Sweden)

    Navid Daryasafar

    2014-01-01

    Full Text Available We intend to design a broadband band-pass filter with notch-band, which uses coupled transmission lines in the structure, using new models of coupled transmission lines. In order to realize and present the new model, first, previous models will be simulated in the ADS program. Then, according to the change of their equations and consequently change of basic parameters of these models, optimization and dependency among these parameters and also their frequency response are attended and results of these changes in order to design a new filter are converged.

  3. Adaptive noise Wiener filter for scanning electron microscope imaging system.

    Science.gov (United States)

    Sim, K S; Teh, V; Nia, M E

    2016-01-01

    Noise on scanning electron microscope (SEM) images is studied. Gaussian noise is the most common type of noise in SEM image. We developed a new noise reduction filter based on the Wiener filter. We compared the performance of this new filter namely adaptive noise Wiener (ANW) filter, with four common existing filters as well as average filter, median filter, Gaussian smoothing filter and the Wiener filter. Based on the experiments results the proposed new filter has better performance on different noise variance comparing to the other existing noise removal filters in the experiments. © Wiley Periodicals, Inc.

  4. Kernel adaptive filtering a comprehensive introduction

    CERN Document Server

    Liu, Weifeng; Haykin, Simon

    2010-01-01

    Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, O

  5. Adaptive Filtering Queueing for Improving Fairness

    Directory of Open Access Journals (Sweden)

    Jui-Pin Yang

    2015-06-01

    Full Text Available In this paper, we propose a scalable and efficient Active Queue Management (AQM scheme to provide fair bandwidth sharing when traffic is congested dubbed Adaptive Filtering Queueing (AFQ. First, AFQ identifies the filtering level of an arriving packet by comparing it with a flow label selected at random from the first level to an estimated level in the filtering level table. Based on the accepted traffic estimation and the previous fair filtering level, AFQ updates the fair filtering level. Next, AFQ uses a simple packet-dropping algorithm to determine whether arriving packets are accepted or discarded. To enhance AFQ’s feasibility in high-speed networks, we propose a two-layer mapping mechanism to effectively simplify the packet comparison operations. Simulation results demonstrate that AFQ achieves optimal fairness when compared with Rotating Preference Queues (RPQ, Core-Stateless Fair Queueing (CSFQ, CHOose and Keep for responsive flows, CHOose and Kill for unresponsive flows (CHOKe and First-In First-Out (FIFO schemes under a variety of traffic conditions.

  6. Target Response Adaptation for Correlation Filter Tracking

    KAUST Repository

    Bibi, Adel Aamer

    2016-09-16

    Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations to actual translations in the image, which become unreliable in many realistic tracking scenarios including fast motion, occlusion, etc. In these cases, the traditional use of a single centered Gaussian as the target response impedes tracker performance and can lead to unrecoverable drift. To circumvent this major drawback, we propose a generic framework that can adaptively change the target response from frame to frame, so that the tracker is less sensitive to the cases where circular shifts do not reliably approximate translations. To do that, we reformulate the underlying optimization to solve for both the filter and target response jointly, where the latter is regularized by measurements made using actual translations. This joint problem has a closed form solution and thus allows for multiple templates, kernels, and multi-dimensional features. Extensive experiments on the popular OTB100 benchmark show that our target adaptive framework can be combined with many CF trackers to realize significant overall performance improvement (ranging from 3 %-13.5% in precision and 3.2 %-13% in accuracy), especially in categories where this adaptation is necessary (e.g. fast motion, motion blur, etc.). © Springer International Publishing AG 2016.

  7. Quaternion-valued nonlinear adaptive filtering.

    Science.gov (United States)

    Ujang, Bukhari Che; Took, Clive Cheong; Mandic, Danilo P

    2011-08-01

    A class of nonlinear quaternion-valued adaptive filtering algorithms is proposed based on locally analytic nonlinear activation functions. To circumvent the stringent standard analyticity conditions which are prohibitive to the development of nonlinear adaptive quaternion-valued estimation models, we use the fact that stochastic gradient learning algorithms require only local analyticity at the operating point in the estimation space. It is shown that the quaternion-valued exponential function is locally analytic, and, since local analyticity extends to polynomials, products, and ratios, we show that a class of transcendental nonlinear functions can serve as activation functions in nonlinear and neural adaptive models. This provides a unifying framework for the derivation of gradient-based learning algorithms in the quaternion domain, and the derived algorithms are shown to have the same generic form as their real- and complex-valued counterparts. To make such models second-order optimal for the generality of quaternion signals (both circular and noncircular), we use recent developments in augmented quaternion statistics to introduce widely linear versions of the proposed nonlinear adaptive quaternion valued filters. This allows full exploitation of second-order information in the data, contained both in the covariance and pseudocovariances to cater rigorously for second-order noncircularity (improperness), and the corresponding power mismatch in the signal components. Simulations over a range of circular and noncircular synthetic processes and a real world 3-D noncircular wind signal support the approach.

  8. Nonlinear Adaptive Filters based on Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Faten BEN ARFIA

    2009-07-01

    Full Text Available This paper presents a particle swarm optimization (PSO algorithm to adjust the parameters of the nonlinear filter and to make this type of the filters more powerful for the elimination of the Gaussian noise and also the impulse noise. In this paper we apply the particle swarm optimization to the rational filters and we completed this work with the comparison between our results and other adaptive nonlinear filters like the LMS adaptive median filters and the no-adaptive rational filter.

  9. Research on adaptive filtering method for electrostatic signals

    Science.gov (United States)

    Xu, Hongke; Pang, Yue; Yi, Yingmin

    2017-05-01

    The signal will be inevitably mixed with various types of noise in the process of transmission, which causes the distortion of information in different degree, in order to obtain accurate information, it's an important work to suppress random noise in the digital signal processing system. This paper mainly studies the adaptive filtering method, using LMS algorithm in adaptive filter (Least mean square LMS algorithm), when the filter starts reading the electrostatic signal, it also can estimate the statistical characteristics of electrostatic signal, adaptive adjust its filter parameters, filtering the electrostatic signal on time, attain the maximum noise suppression, to avoid distortion of information, and to achieve optimal filtering.

  10. Adaptive ship autopilot with wave filter

    Directory of Open Access Journals (Sweden)

    Steinar Sælid

    1983-01-01

    Full Text Available This paper is concerned with analysis and design of an adaptive autopilot for ships. The design is based on a low and high frequency model of the vessel motion adequate to ship steering. The low frequency model describes the vessel response to rudder control and slowly varying environmental forces. The high frequency model represents the wave induced oscillatory part of the yaw motion. The models are used in a Kalman filter and the rudder control is computed from linear quadratic theory based on the low frequency part of the vector. This yields a very effective filtering of the wave component of the yaw motion. Proper operation of this filter/controller structure requires knowledge of the vessel model parameters and the dominating wave frequency. The vessel parameters are estimated on line by a recursive prediction error method. In order to reduce the computing requirements, the state estimator is operated using scheduled gains. This results in an easy and robust design. The convergence properties are investigated by using the method of Ljung. The performance is confirmed by simulation experiments.

  11. Design and Analysis of Multilayered Waveguide Structure With Metal-Dielectric Gratings for Sensing With Reflection Narrowband Notch Filter

    Directory of Open Access Journals (Sweden)

    Guiju ZHANG

    2015-11-01

    Full Text Available Developments in micro and nanofabrication technologies have led a variety of grating waveguide structures (GWS being proposed and implemented in optics and laser application systems. A new design of multilayered nanostructure double-grating is described for reflection notch filter. Thin metal film and dielectric film are used and designed with one-dimensional composite gratings. The results calculated by rigorous coupled-wave analysis (RCWA present that the thin metal film between substrate and grating can produce significant attenuated reflections and efficiency in a broad reflected spectral range. The behavior of such a reflection filter is evaluated for refractive index sensing, which can be applied inside the integrated waveguide structure while succeeding cycles in measurement. The filter peaks are designed and obtained in a visible range with full width half maximum (FWHM of several nanometers to less than one nanometer. The multilayered structure shows a sensitivity of refractive index of 220nm/RIU as changing the surroundings. The reflection spectra are studied under different periods, depths and duty cycles. The passive structure and its characteristics can achieve practical applications in various fields, such as optical sensing, color filtering, Raman spectroscopy and laser technology.DOI: http://dx.doi.org/10.5755/j01.ms.21.4.9625

  12. Applying Maxi-adjustment to Adaptive Information Filtering Agents

    OpenAIRE

    Lau, Raymond; ter Hofstede, Arthur H.M.; Bruza, Peter D.

    2000-01-01

    Learning and adaptation is a fundamental property of intelligent agents. In the context of adaptive information filtering, a filtering agent's beliefs about a user's information needs have to be revised regularly with reference to the user's most current information preferences. This learning and adaptation process is essential for maintaining the agent's filtering performance. The AGM belief revision paradigm provides a rigorous foundation for modelling rational and minimal changes to an age...

  13. Simulation for noise cancellation using LMS adaptive filter

    Science.gov (United States)

    Lee, Jia-Haw; Ooi, Lu-Ean; Ko, Ying-Hao; Teoh, Choe-Yung

    2017-06-01

    In this paper, the fundamental algorithm of noise cancellation, Least Mean Square (LMS) algorithm is studied and enhanced with adaptive filter. The simulation of the noise cancellation using LMS adaptive filter algorithm is developed. The noise corrupted speech signal and the engine noise signal are used as inputs for LMS adaptive filter algorithm. The filtered signal is compared to the original noise-free speech signal in order to highlight the level of attenuation of the noise signal. The result shows that the noise signal is successfully canceled by the developed adaptive filter. The difference of the noise-free speech signal and filtered signal are calculated and the outcome implies that the filtered signal is approaching the noise-free speech signal upon the adaptive filtering. The frequency range of the successfully canceled noise by the LMS adaptive filter algorithm is determined by performing Fast Fourier Transform (FFT) on the signals. The LMS adaptive filter algorithm shows significant noise cancellation at lower frequency range.

  14. A hybrid RNS adaptive filter for channel equalization

    DEFF Research Database (Denmark)

    Bernocchi, Gian Luca; Cardarilli, Gian Carlo; Re, Andrea Del

    2006-01-01

    In this work a hybrid Residue Number System (RNS) implementation of an adaptive FIR filter is presented. The used adaptation algorithm is the Least Mean Squares (LMS). The filter has been designed to meet the constraints of specific class of applications. In fact, it is suitable for applications...... simplifications. Vice versa, the RNS implementation of the adaptation algorithm needs scaling circuits that are complex and expensive in RNS arithmetic. For this reason, a serial binary implementation of the adaptation algorithm is chosen. The advantages in terms of area and speed of the RNS adaptive filter...

  15. An adaptive filter for smoothing noisy radar images

    Science.gov (United States)

    Frost, V. S.; Stiles, J. A.; Shanmugam, K. S.; Holtzman, J. C.; Smith, S. A.

    1981-01-01

    A spatial domain adaptive Wiener filter for smoothing radar images corrupted by multiplicative noise is presented. The filter is optimum in a minimum mean squared error sense, computationally efficient, and preserves edges in the image better than other filters. The proposed algorithm can also be used for processing optical images with illumination variations that have a multiplicative effect.

  16. Robust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion

    Directory of Open Access Journals (Sweden)

    Zongze Wu

    2015-10-01

    Full Text Available The maximum correntropy criterion (MCC has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers. In this work, we apply the MCC criterion to develop a robust Hammerstein adaptive filter. Compared with the traditional Hammerstein adaptive filters, which are usually derived based on the well-known mean square error (MSE criterion, the proposed algorithm can achieve better convergence performance especially in the presence of impulsive non-Gaussian (e.g., α-stable noises. Additionally, some theoretical results concerning the convergence behavior are also obtained. Simulation examples are presented to confirm the superior performance of the new algorithm.

  17. Applications of adaptive filters in active noise control

    Science.gov (United States)

    Darlington, Paul

    The active reduction of acoustic noise is achieved by the addition of a cancelling acoustic signal to the unwanted sound. Successful definition of the cancelling signal amounts to a system identification problem. Recent advances in adaptive signal processing have allowed this problem to be tackled using adaptive filters, which offer significant advantages over conventional solutions. The extension of adaptive noise cancelling techniques, which were developed in the electrical signal conditioning context, to the control of acoustic systems is studied. An analysis is presented of the behavior of the Widrow-Hoff LMS adaptive noise canceller with a linear filter in its control loop. The active control of plane waves propagating axially in a hardwalled duct is used as a motivating model problem. The model problem also motivates the study of the effects of feedback around an LMS adaptive filter. An alternative stochastic gradient algorithm for controlling adaptive filters in the presence of feedback is presented.

  18. Low-Complexity Adaptive Filtering Implementation for Acoustic Echo Cancellation

    OpenAIRE

    Schüldt, Christian; Lindström, Fredric; Claesson, Ingvar

    2006-01-01

    Acoustic echo cancellation is generally achieved with adaptive FIR filters. Due to the often large dimensionality of the adaptive filters, required to model rooms with standard reverberation time, the adaptation process can be computationally demanding. This paper presents a block based selective updating method which reduces the complexity with nearly a half in practical situations, while showing superior convergence speed performance as compared to conventional partial update complexity red...

  19. An adaptive dynamically weighted median filter for impulse noise removal

    Science.gov (United States)

    Khan, Sajid; Lee, Dong-Ho

    2017-12-01

    A new impulsive noise removal filter, adaptive dynamically weighted median filter (ADWMF), is proposed. A popular method for removing impulsive noise is a median filter whereas the weighted median filter and center weighted median filter were also investigated. ADWMF is based on weighted median filter. In ADWMF, instead of fixed weights, weightages of the filter are dynamically assigned with the results of noise detection. A simple and efficient noise detection method is also used to detect noise candidates and dynamically assign zero or small weights to the noise candidates in the window. This paper proposes an adaptive method which increases the window size according to the amounts of impulsive noise. Simulation results show that the AMWMF works better for both images with low and high density of impulsive noise than existing methods work.

  20. Low-power adaptive filter based on RNS components

    DEFF Research Database (Denmark)

    Bernocchi, Gian Luca; Cardarilli, Gian Carlo; Del Re, Andrea

    2007-01-01

    on the least mean squares (LMS) algorithm, is allowed. Previous work showed that the use of the residue number system (RNS) for the variable FIR filter grants advantages both in area and power consumption. On the other hand, the use of a binary serial implementation of the adaptation algorithm eliminates......In this paper a low-power implementation of an adaptive FIR filter is presented. The filter is designed to meet the constraints of channel equalization for fixed wireless communications that typically requires a large number of taps, but a serial updating of the filter coefficients, based...

  1. Real time microcontroller implementation of an adaptive myoelectric filter.

    Science.gov (United States)

    Bagwell, P J; Chappell, P H

    1995-03-01

    This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

  2. Exposing Objects under Light Cloud Cover by Adaptive Homomorphic Filtering.

    Science.gov (United States)

    1982-01-06

    U’.S. (;overnment agencies. The views and conclusions contained in this do-ument are those of the contrat or and should not be interpreted as ne...The Stochastic Iterative Approach 16 3.2 The Deterministic Adaptive Approach 20 3.3 Filter Design 24 4. EXPERIMENTAL RESULTS 28 4.1 Stochastic Approach... modification of this it- 17 eration where rather than filtering the original cloudy image on each iteration we filter the updated signal estimate (i.e

  3. Adaptive Subband Filtering Method for MEMS Accelerometer Noise Reduction

    Directory of Open Access Journals (Sweden)

    Piotr PIETRZAK

    2008-12-01

    Full Text Available Silicon microaccelerometers can be considered as an alternative to high-priced piezoelectric sensors. Unfortunately, relatively high noise floor of commercially available MEMS (Micro-Electro-Mechanical Systems sensors limits the possibility of their usage in condition monitoring systems of rotating machines. The solution of this problem is the method of signal filtering described in the paper. It is based on adaptive subband filtering employing Adaptive Line Enhancer. For filter weights adaptation, two novel algorithms have been developed. They are based on the NLMS algorithm. Both of them significantly simplify its software and hardware implementation and accelerate the adaptation process. The paper also presents the software (Matlab and hardware (FPGA implementation of the proposed noise filter. In addition, the results of the performed tests are reported. They confirm high efficiency of the solution.

  4. Nonlinear Adaptive Filter for MEMS Gyro Error Cancellation Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The Nonlinear adaptive filters (NAF) can learn deterministic gyro errors and cancel the error’s effect from attitude estimates. By completely canceling...

  5. Junction-type photonic crystal waveguides for notch- and pass-band filtering

    KAUST Repository

    Shahid, Naeem

    2011-01-01

    Evolution of the mode gap and the associated transmission mini stop-band (MSB) as a function of photonic crystal (PhC) waveguide width is theoretically and experimentally investigated. The change of line-defect width is identified to be the most appropriate way since it offers a wide MSB wavelength tuning range. A high transmission narrow-band filter is experimentally demonstrated in a junction-type waveguide composed of two PhC waveguides with slightly different widths. The full width at half maximum is 5.6 nm; the peak transmission is attenuated by only ∼5 dB and is ∼20 dB above the MSBs. Additionally, temperature tuning of the filter were also performed. The results show red-shift of the transmission peak and the MSB edges with a gradient of dλ/dT = 0.1 nm/°C. It is proposed that the transmission MSBs in such junction-type cascaded PhC waveguides can be used to obtain different types of filters. © 2011 Optical Society of America.

  6. Despeckling PolSAR images with an adaptive bilateral filter

    Science.gov (United States)

    Liu, Liu; Zhou, Fang; Chen, Jing; Yang, Xuezhi; Jia, Lu; Dong, Zhangyu; Ai, Jiaqiu

    2017-04-01

    An improved bilateral filter with adaptive parameters estimation in space domain and polarimetric domain for polarimetric synthetic aperture radar (PolSAR) image despeckling, named PolSAR adaptive bilateral filtering (PABF), is proposed. On one hand, PABF sets the spatial parameter adaptively according to the local coefficient of variation. On the other hand, the polarimetric parameter is adjusted adaptively on the basis of the noise variance estimated from the convolution between the intensity image and Laplacian template. The experiments performed on simulated and real PolSAR data show that PABF effectively suppresses speckles while maintaining important details of images.

  7. Introducing Adaptive Filters Based on Shadow Concept for Speech Processing

    OpenAIRE

    Koteswara Rao, M; Prabha, I.Santhi

    2014-01-01

    This paper presents the new approach to introducing adaptive Filter with LMS Algorithm based on Shadow concept. Which is useful for the cancellation of the noise component overlap with Speech signal in the same frequency range, but fixed LMS algorithm produces minimum convergence rate and fixed steady state error. So we presents design, implementation and performance of adaptive FIR filter, based on Shadow concept, which produces minimum mean square error compare to fixed LMS, and we also o...

  8. A novel gradient adaptive step size LMS algorithm with dual adaptive filters.

    Science.gov (United States)

    Jiao, Yuzhong; Cheung, Rex Y P; Chow, Winnie W Y; Mok, Mark P C

    2013-01-01

    Least mean square (LMS) adaptive filter has been used to extract life signals from serious ambient noises and interferences in biomedical applications. However, a LMS adaptive filter with a fixed step size always suffers from slow convergence rate or large signal distortion due to the diversity of the application environments. An ideal adaptive filtering system should be able to adapt different environments and obtain the useful signals with low distortion. Adaptive filter with gradient adaptive step size is therefore more desirable in order to meet the demands of adaptation and convergence rate, which adjusts the step-size parameter automatically by using gradient descent technique. In this paper, a novel gradient adaptive step size LMS adaptive filter is presented. The proposed algorithm utilizes two adaptive filters to estimate gradients accurately, thus achieves good adaptation and performance. Though it uses two LMS adaptive filters, it has a low computational complexity. An active noise cancellation (ANC) system with two applications for extracting heartbeat and lung sound signals from noises is used to simulate the performance of the proposed algorithm.

  9. Adaptive Control of Flexible Structures Using Residual Mode Filters

    Science.gov (United States)

    Balas, Mark J.; Frost, Susan

    2010-01-01

    Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter. We have proposed a modified adaptive controller with a residual mode filter. The RMF is used to accommodate troublesome modes in the system that might otherwise inhibit the adaptive controller, in particular the ASPR condition. This new theory accounts for leakage of the disturbance term into the Q modes. A simple three-mode example shows that the RMF can restore stability to an otherwise unstable adaptively controlled system. This is done without modifying the adaptive controller design.

  10. Adaptive Filtering for Non-Gaussian Processes

    DEFF Research Database (Denmark)

    Kidmose, Preben

    2000-01-01

    A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulat......A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals....... A simulation study, applying both synthetic and real-world signals, shows that the proposed method has overall better robustness performance, in terms of modeling error, compared with state-of-the-art robust filtering methods. A remarkable property of the proposed method is that it can handle double...

  11. Thermal control of the magnon-photon coupling in a notch filter coupled to a yttrium iron garnet/platinum system

    Science.gov (United States)

    Castel, Vincent; Jeunehomme, Rodolphe; Ben Youssef, Jamal; Vukadinovic, Nicolas; Manchec, Alexandre; Dejene, Fasil Kidane; Bauer, Gerrit E. W.

    2017-08-01

    We report thermal control of mode hybridization between the ferromagnetic resonance and a planar resonator (notch filter) working at 4.74 GHz. The chosen magnetic material is a ferrimagnetic insulator (yttrium iron garnet: YIG) covered by 6 nm of platinum (Pt). A current-induced heating method has been used in order to enhance the temperature of the YIG/Pt system. The device permits us to control the transmission spectra and the magnon-photon coupling strength at room temperature. These experimental findings reveal a potentially applicable tunable microwave filtering function.

  12. Adaptive ensemble Kalman filtering of non-linear systems

    Directory of Open Access Journals (Sweden)

    Tyrus Berry

    2013-07-01

    Full Text Available A necessary ingredient of an ensemble Kalman filter (EnKF is covariance inflation, used to control filter divergence and compensate for model error. There is an on-going search for inflation tunings that can be learned adaptively. Early in the development of Kalman filtering, Mehra (1970, 1972 enabled adaptivity in the context of linear dynamics with white noise model errors by showing how to estimate the model error and observation covariances. We propose an adaptive scheme, based on lifting Mehra's idea to the non-linear case, that recovers the model error and observation noise covariances in simple cases, and in more complicated cases, results in a natural additive inflation that improves state estimation. It can be incorporated into non-linear filters such as the extended Kalman filter (EKF, the EnKF and their localised versions. We test the adaptive EnKF on a 40-dimensional Lorenz96 model and show the significant improvements in state estimation that are possible. We also discuss the extent to which such an adaptive filter can compensate for model error, and demonstrate the use of localisation to reduce ensemble sizes for large problems.

  13. Adaptive Filtering for Aeroservoelastic Response Suppression Project

    Data.gov (United States)

    National Aeronautics and Space Administration — CSA Engineering proposes the design of an adaptive aeroelastic mode suppression for advanced fly-by-wire aircraft, which will partition the modal suppression...

  14. A spatial filtering approach to robust adaptive beaming

    Science.gov (United States)

    Claesson, I.; Nordholm, S.

    1992-09-01

    This communication treats the problem of controlling the superresolution in adaptive beamformers. A straightforward method is presented that works for both narrow-band and broad-band arrays. The method is based on forming the blocking matrix in a general sidelobe canceller (GSC) structure using a spatial FIR filter. The suppression of this spatial filter and the implicit noise of the leaky (LMS) algorithm together determine the beamformer.

  15. Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

    Science.gov (United States)

    Frost, Susan A.; Balas, Mark J.

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

  16. Artifact removal from EEG signals using adaptive filters in cascade

    Science.gov (United States)

    Garcés Correa, A.; Laciar, E.; Patiño, H. D.; Valentinuzzi, M. E.

    2007-11-01

    Artifacts in EEG (electroencephalogram) records are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). These noise sources increase the difficulty in analyzing the EEG and to obtaining clinical information. For this reason, it is necessary to design specific filters to decrease such artifacts in EEG records. In this paper, a cascade of three adaptive filters based on a least mean squares (LMS) algorithm is proposed. The first one eliminates line interference, the second adaptive filter removes the ECG artifacts and the last one cancels EOG spikes. Each stage uses a finite impulse response (FIR) filter, which adjusts its coefficients to produce an output similar to the artifacts present in the EEG. The proposed cascade adaptive filter was tested in five real EEG records acquired in polysomnographic studies. In all cases, line-frequency, ECG and EOG artifacts were attenuated. It is concluded that the proposed filter reduces the common artifacts present in EEG signals without removing significant information embedded in these records.

  17. Robust Adaptive Control Using a Filtering Action

    Science.gov (United States)

    2009-09-01

    Control and Signal Processing (ALCOSP 2007). Saint Petersburg, RUSSIA August 2007. [65] R. K. Miller and G. R. Sell, Volterra Integral Equations and...Experimental Results with Modified L1 Adaptive Controller and FSS. .........82 Figure C.1. Region of Integration for Equation (C.2...is that 1 1 ( ) ( ) D p E p is a PID controller, with the integral action to satisfy Equation (4.3), and the derivative action to make its inverse

  18. The Least Mean Squares Adaptive FIR Filter for Narrow-Band RFI Suppression in Radio Detection of Cosmic Rays

    Science.gov (United States)

    Szadkowski, Zbigniew; Głas, Dariusz

    2017-06-01

    Radio emission from the extensive air showers (EASs), initiated by ultrahigh-energy cosmic rays, was theoretically suggested over 50 years ago. However, due to technical limitations, successful collection of sufficient statistics can take several years. Nowadays, this detection technique is used in many experiments consisting in studying EAS. One of them is the Auger Engineering Radio Array (AERA), located within the Pierre Auger Observatory. AERA focuses on the radio emission, generated by the electromagnetic part of the shower, mainly in geomagnetic and charge excess processes. The frequency band observed by AERA radio stations is 30-80 MHz. Thus, the frequency range is contaminated by human-made and narrow-band radio frequency interferences (RFIs). Suppression of contaminations is very important to lower the rate of spurious triggers. There are two kinds of digital filters used in AERA radio stations to suppress these contaminations: the fast Fourier transform median filter and four narrow-band IIR-notch filters. Both filters have worked successfully in the field for many years. An adaptive filter based on a least mean squares (LMS) algorithm is a relatively simple finite impulse response (FIR) filter, which can be an alternative for currently used filters. Simulations in MATLAB are very promising and show that the LMS filter can be very efficient in suppressing RFI and only slightly distorts radio signals. The LMS algorithm was implemented into a Cyclone V field programmable gate array for testing the stability, RFI suppression efficiency, and adaptation time to new conditions. First results show that the FIR filter based on the LMS algorithm can be successfully implemented and used in real AERA radio stations.

  19. Streak image denoising and segmentation using adaptive Gaussian guided filter.

    Science.gov (United States)

    Jiang, Zhuocheng; Guo, Baoping

    2014-09-10

    In streak tube imaging lidar (STIL), streak images are obtained using a CCD camera. However, noise in the captured streak images can greatly affect the quality of reconstructed 3D contrast and range images. The greatest challenge for streak image denoising is reducing the noise while preserving details. In this paper, we propose an adaptive Gaussian guided filter (AGGF) for noise removal and detail enhancement of streak images. The proposed algorithm is based on a guided filter (GF) and part of an adaptive bilateral filter (ABF). In the AGGF, the details are enhanced by optimizing the offset parameter. AGGF-denoised streak images are significantly sharper than those denoised by the GF. Moreover, the AGGF is a fast linear time algorithm achieved by recursively implementing a Gaussian filter kernel. Experimentally, AGGF demonstrates its capacity to preserve edges and thin structures and outperforms the existing bilateral filter and domain transform filter in terms of both visual quality and peak signal-to-noise ratio performance.

  20. BPSK Receiver Based on Recursive Adaptive Filter with Remodulation

    Directory of Open Access Journals (Sweden)

    N. Milosevic

    2011-12-01

    Full Text Available This paper proposes a new binary phase shift keying (BPSK signal receiver intended for reception under conditions of significant carrier frequency offsets. The recursive adaptive filter with least mean squares (LMS adaptation is used. The proposed receiver has a constant, defining the balance between the recursive and the nonrecursive part of the filter, whose proper choice allows a simple construction of the receiver. The correct choice of this parameter could result in unitary length of the filter. The proposed receiver has performance very close to the performance of the BPSK receiver with perfect frequency synchronization, in a wide range of frequency offsets (plus/minus quarter of the signal bandwidth. The results obtained by the software simulation are confirmed by the experimental results measured on the receiver realized with the universal software radio peripheral (USRP, with the baseband signal processing at personal computer (PC.

  1. Adaptive filtering for stochastic risk premia in bond market

    NARCIS (Netherlands)

    Aihara, ShinIchi; Bagchi, Arunabha

    We consider the adaptive filtering problem for estimating the randomly changing risk premium and its system parameters for zero-coupon bond models. The term structure model for a zero-coupon bond is formulated including the stochastic risk-premium factor. We specify our observation data from the

  2. Adaptive Unscented Kalman Filter using Maximum Likelihood Estimation

    DEFF Research Database (Denmark)

    Mahmoudi, Zeinab; Poulsen, Niels Kjølstad; Madsen, Henrik

    2017-01-01

    The purpose of this study is to develop an adaptive unscented Kalman filter (UKF) by tuning the measurement noise covariance. We use the maximum likelihood estimation (MLE) and the covariance matching (CM) method to estimate the noise covariance. The multi-step prediction errors generated...

  3. Adaptive detail enhancement for infrared image based on bilateral filter

    Science.gov (United States)

    Zeng, Qingjie; Qin, Hanlin; Leng, Hanbing; Yan, Xiang; Li, Jia; Zhou, Huixin

    2015-10-01

    In order to solve the problem that infrared images usually have a poor visual effect with low contrast and weak detail information, an adaptive detail enhancement method for infrared image based on bilateral filter is proposed in this paper. Firstly, adopting the bilateral filter which has a good filtering performance, the original infrared image is effectively derived into the smoothed component and the detail component. Exactly, the detail component is the difference between the original infrared image and the smoothed component. The major merit of using the bilateral filter is that the abundant and subtle detail contents containing a lot of edges and textures of the original infrared image could be obtained via adjusting the parameters flexibly. Further, the detail component plays a key role in obtaining an adaptive detail enhancement weight which is generated by the normalization of the detail component. The weight is in the range [0, 1] and their magnitudes can be regarded as the intensity of the original image details. As a result, this detail enhancement weight is adaptive and effective for the original infrared image. Finally, a kind of linear weighting strategy is utilized to achieve the image sharpness combing the original image and the adaptive weight. The experimental results show that the proposed method outperforms other conventional methods in terms of visual effect and quantitative evaluation, which provides a new approach for infrared image detail enhancement.

  4. A Reconfigurable Triple-Notch-Band Antenna Integrated with Defected Microstrip Structure Band-Stop Filter for Ultra-Wideband Cognitive Radio Applications

    Directory of Open Access Journals (Sweden)

    Yingsong Li

    2013-01-01

    Full Text Available A printed reconfigurable ultra-wideband (UWB monopole antenna with triple narrow band-notched characteristics is proposed for cognitive radio applications in this paper. The triple narrow band-notched frequencies are obtained using a defected microstrip structure (DMS band stop filter (BSF embedded in the microstrip feed line and an inverted π-shaped slot etched in the rectangular radiation patch, respectively. Reconfigurable characteristics of the proposed cognitive radio antenna (CRA are achieved by means of four ideal switches integrated on the DMS-BSF and the inverted π-shaped slot. The proposed UWB CRA can work at eight modes by controlling switches ON and OFF. Moreover, impedance bandwidth, design procedures, and radiation patterns are presented for analysis and explanation of this antenna. The designed antenna operates over the frequency band between 3.1 GHz and 14 GHz (bandwidth of 127.5%, with three notched bands from 4.2 GHz to 6.2 GHz (38.5%, 6.6 GHz to 7.0 GHz (6%, and 12.2 GHz to 14 GHz (13.7%. The antenna is successfully simulated, fabricated, and measured. The results show that it has wide impedance bandwidth, multimodes characteristics, stable gain, and omnidirectional radiation patterns.

  5. Adaptive training of feedforward neural networks by Kalman filtering

    Energy Technology Data Exchange (ETDEWEB)

    Ciftcioglu, Oe. [Istanbul Technical Univ. (Turkey). Dept. of Electrical Engineering; Tuerkcan, E. [Netherlands Energy Research Foundation (ECN), Petten (Netherlands)

    1995-02-01

    Adaptive training of feedforward neural networks by Kalman filtering is described. Adaptive training is particularly important in estimation by neural network in real-time environmental where the trained network is used for system estimation while the network is further trained by means of the information provided by the experienced/exercised ongoing operation. As result of this, neural network adapts itself to a changing environment to perform its mission without recourse to re-training. The performance of the training method is demonstrated by means of actual process signals from a nuclear power plant. (orig.).

  6. A COMPARISON OF TWO METHODS FADING MEMORY FILTER AND ADAPTIVE KALMAN FILTER IN MONITORING CRUSTAL MOVEMENT

    Directory of Open Access Journals (Sweden)

    Cahit Tağı ÇELİK

    2004-01-01

    Full Text Available Monitoring the Crustal Movement in Geodesy is performed by the deformation survey and analysis. If monitoring the crustal movements involves more than two epochs of survey campaign then from the plate tectonic theory, stations do not move randomly from one epoch to the other, therefore Kalman Filter may be suitable to use. However, if sudden movements happened in the crust in particular earthquake happened, the crust moves very fast in a very short period of time. When Kalman Filter used for monitoring these movements, from associated epoch, for a number of epochs the results may be biased. In the paper, comparison of two methods for elimination of the above mentioned biases have been performed. These methods are Fading Memory Filter and Adaptive Kalman Filter for an unknown bias.

  7. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems

    Directory of Open Access Journals (Sweden)

    Chien-Hao Tseng

    2016-07-01

    Full Text Available This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF and fuzzy logic adaptive system (FLAS for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF, unscented Kalman filter (UKF, and CKF approaches.

  8. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

    Science.gov (United States)

    Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

    2016-07-26

    This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches.

  9. Selected annotated bibliographies for adaptive filtering of digital image data

    Science.gov (United States)

    Mayers, Margaret; Wood, Lynnette

    1988-01-01

    Digital spatial filtering is an important tool both for enhancing the information content of satellite image data and for implementing cosmetic effects which make the imagery more interpretable and appealing to the eye. Spatial filtering is a context-dependent operation that alters the gray level of a pixel by computing a weighted average formed from the gray level values of other pixels in the immediate vicinity.Traditional spatial filtering involves passing a particular filter or set of filters over an entire image. This assumes that the filter parameter values are appropriate for the entire image, which in turn is based on the assumption that the statistics of the image are constant over the image. However, the statistics of an image may vary widely over the image, requiring an adaptive or "smart" filter whose parameters change as a function of the local statistical properties of the image. Then a pixel would be averaged only with more typical members of the same population. This annotated bibliography cites some of the work done in the area of adaptive filtering. The methods usually fall into two categories, (a) those that segment the image into subregions, each assumed to have stationary statistics, and use a different filter on each subregion, and (b) those that use a two-dimensional "sliding window" to continuously estimate the filter either the spatial or frequency domain, or may utilize both domains. They may be used to deal with images degraded by space variant noise, to suppress undesirable local radiometric statistics while enforcing desirable (user-defined) statistics, to treat problems where space-variant point spread functions are involved, to segment images into regions of constant value for classification, or to "tune" images in order to remove (nonstationary) variations in illumination, noise, contrast, shadows, or haze.Since adpative filtering, like nonadaptive filtering, is used in image processing to accomplish various goals, this bibliography

  10. An Affine Combination of Adaptive Filters for Channels with Different Sparsity Levels

    Directory of Open Access Journals (Sweden)

    M. Butsenko

    2016-06-01

    Full Text Available In this paper we present an affine combination strategy for two adaptive filters. One filter is designed to handle sparse impulse responses and the other one performs better if impulse response is dispersive. Filter outputs are combined using an adaptive mixing parameter and the resulting output shows a better performance than each of the combining filters separately. We also demonstrate that affine combination results in faster convergence than a convex combination of two adaptive filters.

  11. Adaptive gain and filtering circuit for a sound reproduction system

    Science.gov (United States)

    Engebretson, A. Maynard (Inventor); O'Connell, Michael P. (Inventor)

    1998-01-01

    Adaptive compressive gain and level dependent spectral shaping circuitry for a hearing aid include a microphone to produce an input signal and a plurality of channels connected to a common circuit output. Each channel has a preset frequency response. Each channel includes a filter with a preset frequency response to receive the input signal and to produce a filtered signal, a channel amplifier to amplify the filtered signal to produce a channel output signal, a threshold register to establish a channel threshold level, and a gain circuit. The gain circuit increases the gain of the channel amplifier when the channel output signal falls below the channel threshold level and decreases the gain of the channel amplifier when the channel output signal rises above the channel threshold level. A transducer produces sound in response to the signal passed by the common circuit output.

  12. Kalman filtering to suppress spurious signals in Adaptive Optics control

    Energy Technology Data Exchange (ETDEWEB)

    Poyneer, L; Veran, J P

    2010-03-29

    In many scenarios, an Adaptive Optics (AO) control system operates in the presence of temporally non-white noise. We use a Kalman filter with a state space formulation that allows suppression of this colored noise, hence improving residual error over the case where the noise is assumed to be white. We demonstrate the effectiveness of this new filter in the case of the estimated Gemini Planet Imager tip-tilt environment, where there are both common-path and non-common path vibrations. We discuss how this same framework can also be used to suppress spatial aliasing during predictive wavefront control assuming frozen flow in a low-order AO system without a spatially filtered wavefront sensor, and present experimental measurements from Altair that clearly reveal these aliased components.

  13. Model Adaptation for Prognostics in a Particle Filtering Framework

    Directory of Open Access Journals (Sweden)

    Bhaskar Saha

    2011-01-01

    Full Text Available One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion and Li-Polymer batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  14. Model Adaptation for Prognostics in a Particle Filtering Framework

    Science.gov (United States)

    Saha, Bhaskar; Goebel, Kai Frank

    2011-01-01

    One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the "curse of dimensionality", i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for "well-designed" particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well-designed prognostic model that can take advantage of the model adaptation properties of a particle filter.

  15. Parameter testing for lattice filter based adaptive modal control systems

    Science.gov (United States)

    Sundararajan, N.; Williams, J. P.; Montgomery, R. C.

    1983-01-01

    For Large Space Structures (LSS), an adaptive control system is highly desirable. The present investigation is concerned with an 'indirect' adaptive control scheme wherein the system order, mode shapes, and modal amplitudes are estimated on-line using an identification scheme based on recursive, least-squares, lattice filters. Using the identified model parameters, a modal control law based on a pole-placement scheme with the objective of vibration suppression is employed. A method is presented for closed loop adaptive control of a flexible free-free beam. The adaptive control scheme consists of a two stage identification scheme working in series and a modal pole placement control scheme. The main conclusion from the current study is that the identified parameters cannot be directly used for controller design purposes.

  16. A neural architecture for nonlinear adaptive filtering of time series

    DEFF Research Database (Denmark)

    Hoffmann, Nils; Larsen, Jan

    1991-01-01

    A neural architecture for adaptive filtering which incorporates a modularization principle is proposed. It facilitates a sparse parameterization, i.e. fewer parameters have to be estimated in a supervised training procedure. The main idea is to use a preprocessor which determines the dimension...... of the polynominals by scaling and limiting the inputs signals. The nonlinearity is constructed from Chebychev polynominals. The authors apply a second-order algorithm for updating the weights for adaptive nonlinearities. Finally the simulations indicate that the two kinds of preprocessing tend to complement each...

  17. Adaptive Compensation of Reactive Power With Shunt Active Power Filters

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Asiminoaei, Lucian; Hansen, Steffan

    2008-01-01

    This paper describes an adaptive method for compensating the reactive power with an active power filter (APF), which is initially rated for mitigation of only the harmonic currents given by a nonlinear industrial load. It is proven that, if the harmonic currents do not load the APF at the rated...... power, the available power can be used to provide a part of the required reactive power. Different indicators for designing such application are given, and it is proven that the proposed adaptive algorithm represents an added value to the APF. The algorithm is practically validated on a laboratory setup...... with a 7-kVA APF....

  18. Reduced Rank Adaptive Filtering in Impulsive Noise Environments

    KAUST Repository

    Soury, Hamza

    2014-01-06

    An impulsive noise environment is used in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction. The minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each algorithm is discussed.

  19. Hyperspectral image filtering with adaptive manifold for classification

    Science.gov (United States)

    Xie, Weiying; Li, Yunsong; Zhou, Weiping

    2017-05-01

    Hyperspectral image (HSI) is a three-dimensional data cube containing two spatial information dimensions and one spectral information dimension. The spectral vectors of different classes may have similar tendency and value that may bring about negative influences on classification. It is, therefore, important to introduce signal preprocessing techniques in the spatial domain to improve classification accuracy of HSIs. Assuming that local pixels in HSI have some correlations with each other, this paper proposes a spatial filtering model based on adaptive manifold (AM) for HSI. The AM for spatial filtering emphasizes the similar neighboring pixels and is robust to resist the noisy points with fast speed. The rich information in the filtered data is effective for improving the performance of the subsequent classification. The filtered data are classified by an extreme learning machine (ELM). The experimental results indicate that the framework built based on AM and ELM provides competitive performance. Specifically, by classifying the filtered data, the average accuracy of ELM can be improved as high as 30.54%, while performing tens to hundreds times faster than those state-of-the-art classifiers.

  20. Combination of Adaptive Feedback Cancellation and Binaural Adaptive Filtering in Hearing Aids

    Directory of Open Access Journals (Sweden)

    Anthony Lombard

    2009-01-01

    Full Text Available We study a system combining adaptive feedback cancellation and adaptive filtering connecting inputs from both ears for signal enhancement in hearing aids. For the first time, such a binaural system is analyzed in terms of system stability, convergence of the algorithms, and possible interaction effects. As major outcomes of this study, a new stability condition adapted to the considered binaural scenario is presented, some already existing and commonly used feedback cancellation performance measures for the unilateral case are adapted to the binaural case, and possible interaction effects between the algorithms are identified. For illustration purposes, a blind source separation algorithm has been chosen as an example for adaptive binaural spatial filtering. Experimental results for binaural hearing aids confirm the theoretical findings and the validity of the new measures.

  1. Dual Adaptive Filtering by Optimal Projection Applied to Filter Muscle Artifacts on EEG and Comparative Study

    Directory of Open Access Journals (Sweden)

    Samuel Boudet

    2014-01-01

    Full Text Available Muscle artifacts constitute one of the major problems in electroencephalogram (EEG examinations, particularly for the diagnosis of epilepsy, where pathological rhythms occur within the same frequency bands as those of artifacts. This paper proposes to use the method dual adaptive filtering by optimal projection (DAFOP to automatically remove artifacts while preserving true cerebral signals. DAFOP is a two-step method. The first step consists in applying the common spatial pattern (CSP method to two frequency windows to identify the slowest components which will be considered as cerebral sources. The two frequency windows are defined by optimizing convolutional filters. The second step consists in using a regression method to reconstruct the signal independently within various frequency windows. This method was evaluated by two neurologists on a selection of 114 pages with muscle artifacts, from 20 clinical recordings of awake and sleeping adults, subject to pathological signals and epileptic seizures. A blind comparison was then conducted with the canonical correlation analysis (CCA method and conventional low-pass filtering at 30 Hz. The filtering rate was 84.3% for muscle artifacts with a 6.4% reduction of cerebral signals even for the fastest waves. DAFOP was found to be significantly more efficient than CCA and 30 Hz filters. The DAFOP method is fast and automatic and can be easily used in clinical EEG recordings.

  2. A New Adaptive Framework for Collaborative Filtering Prediction.

    Science.gov (United States)

    Almosallam, Ibrahim A; Shang, Yi

    2008-06-01

    Collaborative filtering is one of the most successful techniques for recommendation systems and has been used in many commercial services provided by major companies including Amazon, TiVo and Netflix. In this paper we focus on memory-based collaborative filtering (CF). Existing CF techniques work well on dense data but poorly on sparse data. To address this weakness, we propose to use z-scores instead of explicit ratings and introduce a mechanism that adaptively combines global statistics with item-based values based on data density level. We present a new adaptive framework that encapsulates various CF algorithms and the relationships among them. An adaptive CF predictor is developed that can self adapt from user-based to item-based to hybrid methods based on the amount of available ratings. Our experimental results show that the new predictor consistently obtained more accurate predictions than existing CF methods, with the most significant improvement on sparse data sets. When applied to the Netflix Challenge data set, our method performed better than existing CF and singular value decomposition (SVD) methods and achieved 4.67% improvement over Netflix's system.

  3. A New Adaptive Framework for Collaborative Filtering Prediction

    Science.gov (United States)

    Almosallam, Ibrahim A.; Shang, Yi

    2010-01-01

    Collaborative filtering is one of the most successful techniques for recommendation systems and has been used in many commercial services provided by major companies including Amazon, TiVo and Netflix. In this paper we focus on memory-based collaborative filtering (CF). Existing CF techniques work well on dense data but poorly on sparse data. To address this weakness, we propose to use z-scores instead of explicit ratings and introduce a mechanism that adaptively combines global statistics with item-based values based on data density level. We present a new adaptive framework that encapsulates various CF algorithms and the relationships among them. An adaptive CF predictor is developed that can self adapt from user-based to item-based to hybrid methods based on the amount of available ratings. Our experimental results show that the new predictor consistently obtained more accurate predictions than existing CF methods, with the most significant improvement on sparse data sets. When applied to the Netflix Challenge data set, our method performed better than existing CF and singular value decomposition (SVD) methods and achieved 4.67% improvement over Netflix’s system. PMID:21572924

  4. Adaptive distributed Kalman filtering with wind estimation for astronomical adaptive optics.

    Science.gov (United States)

    Massioni, Paolo; Gilles, Luc; Ellerbroek, Brent

    2015-12-01

    In the framework of adaptive optics (AO) for astronomy, it is a common assumption to consider the atmospheric turbulent layers as "frozen flows" sliding according to the wind velocity profile. For this reason, having knowledge of such a velocity profile is beneficial in terms of AO control system performance. In this paper we show that it is possible to exploit the phase estimate from a Kalman filter running on an AO system in order to estimate wind velocity. This allows the update of the Kalman filter itself with such knowledge, making it adaptive. We have implemented such an adaptive controller based on the distributed version of the Kalman filter, for a realistic simulation of a multi-conjugate AO system with laser guide stars on a 30 m telescope. Simulation results show that this approach is effective and promising and the additional computational cost with respect to the distributed filter is negligible. Comparisons with a previously published slope detection and ranging wind profiler are made and the impact of turbulence profile quantization is assessed. One of the main findings of the paper is that all flavors of the adaptive distributed Kalman filter are impacted more significantly by turbulence profile quantization than the static minimum mean square estimator which does not incorporate wind profile information.

  5. A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.

    Science.gov (United States)

    Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

    2016-12-19

    The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms.

  6. Digital Signal Processing Applications and Implementation for Accelerators Digital Notch Filter with Programmable Delay and Betatron Phase Adjustment for the PS, SPS and LHC Transverse Dampers

    CERN Document Server

    Rossi, V

    2002-01-01

    In the framework of the LHC project and the modifications of the SPS as its injector, I present the concept of global digital signal processing applied to a particle accelerator, using Field Programmable Gate Array (FPGA) technology. The approach of global digital synthesis implements in numerical form the architecture of a system, from the start up of a project and the very beginning of the signal flow. It takes into account both the known parameters and the future evolution, whenever possible. Due to the increased performance requirements of today's projects, the CAE design methodology becomes more and more necessary to handle successfully the added complexity and speed of modern electronic circuits. Simulation is performed both for behavioural analysis, to ensure conformity to functional requirements, and for time signal analysis (speed requirements). The digital notch filter with programmable delay for the SPS Transverse Damper is now fully operational with fixed target and LHC-type beams circulating in t...

  7. Real Time Adaptive Stream-oriented Geo-data Filtering

    Directory of Open Access Journals (Sweden)

    A. A. Golovkov

    2016-01-01

    Full Text Available The cutting-edge engineering maintenance software systems of various objects are aimed at processing of geo-location data coming from the employees’ mobile devices in real time. To reduce the amount of transmitted data such systems, usually, use various filtration methods of geo-coordinates recorded directly on mobile devices.The paper identifies the reasons for errors of geo-data coming from different sources, and proposes an adaptive dynamic method to filter geo-location data. Compared with the static method previously described in the literature [1] the approach offers to align adaptively the filtering threshold with changing characteristics of coordinates from many sources of geo-location data.To evaluate the efficiency of the developed filter method have been involved about 400 thousand points, representing motion paths of different type (on foot, by car and high-speed train and parking (indoors, outdoors, near high-rise buildings to take data from different mobile devices. Analysis of results has shown that the benefits of the proposed method are the more precise location of long parking (up to 6 hours and coordinates when user is in motion, the capability to provide steam-oriented filtering of data from different sources that allows to use the approach in geo-information systems, providing continuous monitoring of the location in streamoriented data processing in real time. The disadvantage is a little bit more computational complexity and increasing amount of points of the final track as compared to other filtration techniques.In general, the developed approach enables a significant quality improvement of displayed paths of moving mobile objects.

  8. Adaptive Digital Signature Design and Short-Data-Record Adaptive Filtering

    Science.gov (United States)

    2008-04-01

    Linear adaptive transmitter-receiver structures for asynchronous CDMA systems ,” European Trans. Telecomm ., vol. 6, pp. 21-28, Jan.-Feb. 1995. [8] T. F...terms of its performance in and application to multiple-input-multiple-output (MIMO) systems . 15. SUBJECT TERMS Short data record, adaptive filtering...Design of Minimum PTSC Binary Antipodal Signature Sets . . . 28 Case 1:Underloaded Systems (K ≤ L) . . . . . . . . . . . . . . . 29 Case 2

  9. An Innovations-Based Noise Cancelling Technique on Inverse Kepstrum Whitening Filter and Adaptive FIR Filter in Beamforming Structure

    Science.gov (United States)

    Jeong, Jinsoo

    2011-01-01

    This paper presents an acoustic noise cancelling technique using an inverse kepstrum system as an innovations-based whitening application for an adaptive finite impulse response (FIR) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal will then be a whitened sequence to a cascaded adaptive FIR filter in the beamforming structure. By using an inverse kepstrum filter as a whitening filter with the use of a delay filter, the cascaded adaptive FIR filter estimates only the numerator of the polynomial part from the ratio of overall combined transfer functions. The test results have shown that the adaptive FIR filter is more effective in beamforming structure than an adaptive noise cancelling (ANC) structure in terms of signal distortion in the desired signal and noise reduction in noise with nonminimum phase components. In addition, the inverse kepstrum method shows almost the same convergence level in estimate of noise statistics with the use of a smaller amount of adaptive FIR filter weights than the kepstrum method, hence it could provide better computational simplicity in processing. Furthermore, the rear-end inverse kepstrum method in beamforming structure has shown less signal distortion in the desired signal than the front-end kepstrum method and the front-end inverse kepstrum method in beamforming structure. PMID:22163987

  10. Reduced rank adaptive filtering in impulsive noise environments

    KAUST Repository

    Soury, Hamza

    2014-11-01

    An impulsive noise environment is considered in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction, while the minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each method is discussed. © 2014 IEEE.

  11. Adaptive Noise Parameter Determination Based on a Particle Filter Algorithm

    Directory of Open Access Journals (Sweden)

    Hyun-Tae Cho

    2016-01-01

    Full Text Available Due to the growing number of vehicles using the national road networks that link major urban centers, traffic noise is becoming a major issue in relation to the transportation system. Thus, it is important to determine noise model parameters to predict road traffic noise levels as part of an environmental assessment, according to traffic volume and pavement surface type. To determine the parameters of a noise prediction model, statistical pass-by and close proximity tests are required. This paper provides a parameter determination procedure for noise prediction models through an adaptive particle filter (PF algorithm, based on using a weigh-in-motion system, which obtains vehicle velocities and types, as well as step-up microphones, which measure the combined noises emitted by various vehicle types. Finally, an evaluation of the adaptive noise parameter determination algorithm was carried out to assess the agreement between predictions and measurements.

  12. A Stochastic Total Least Squares Solution of Adaptive Filtering Problem

    Science.gov (United States)

    Ahmad, Noor Atinah

    2014-01-01

    An efficient and computationally linear algorithm is derived for total least squares solution of adaptive filtering problem, when both input and output signals are contaminated by noise. The proposed total least mean squares (TLMS) algorithm is designed by recursively computing an optimal solution of adaptive TLS problem by minimizing instantaneous value of weighted cost function. Convergence analysis of the algorithm is given to show the global convergence of the proposed algorithm, provided that the stepsize parameter is appropriately chosen. The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. It provides minimum mean square deviation by exhibiting better convergence in misalignment for unknown system identification under noisy inputs. PMID:24688412

  13. Multimodal Medical Image Fusion by Adaptive Manifold Filter

    Directory of Open Access Journals (Sweden)

    Peng Geng

    2015-01-01

    Full Text Available Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images.

  14. QRS detection using adaptive filters: A comparative study.

    Science.gov (United States)

    Jain, Shweta; Ahirwal, M K; Kumar, Anil; Bajaj, V; Singh, G K

    2017-01-01

    Electrocardiogram (ECG) is one of the most important physiological signals of human body, which contains important clinical information about the heart. Monitoring of ECG signal is done through QRS detection. In this paper, an improved QRS detection algorithm, based on adaptive filtering principle, has been designed. Enumeration of the effectiveness of various LMS variants used in adaptive filtering based QRS detection algorithm has been done through fidelity parameters like sensitivity and positive predictivity. Whole family of LMS algorithm has been implemented for comparison. Sign-sign LMS, sign error LMS, basic LMS and normalized LMS are re-implemented, while variable leaky LMS, variable step-size LMS, leaky LMS, recursive least squares (RLS), and fractional LMS are novel combination presented in this paper. After analysis of the obtained results, performance of leaky-LMS algorithm is found to be the best with sensitivity, positive predictivity, and processing time of 99.68%, 99.84%, and 0.45s respectively. Reported results are tested and evaluated over MIT/BIH arrhythmia database. Presented study also concludes that the performance of most of the variants gets affected due to low SNR but the Leaky LMS performs better even under heavy noise conditions. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Application of adaptive filters in denoising magnetocardiogram signals

    Science.gov (United States)

    Khan, Pathan Fayaz; Patel, Rajesh; Sengottuvel, S.; Saipriya, S.; Swain, Pragyna Parimita; Gireesan, K.

    2017-05-01

    Magnetocardiography (MCG) is the measurement of weak magnetic fields from the heart using Superconducting QUantum Interference Devices (SQUID). Though the measurements are performed inside magnetically shielded rooms (MSR) to reduce external electromagnetic disturbances, interferences which are caused by sources inside the shielded room could not be attenuated. The work presented here reports the application of adaptive filters to denoise MCG signals. Two adaptive noise cancellation approaches namely least mean squared (LMS) algorithm and recursive least squared (RLS) algorithm are applied to denoise MCG signals and the results are compared. It is found that both the algorithms effectively remove noisy wiggles from MCG traces; significantly improving the quality of the cardiac features in MCG traces. The calculated signal-to-noise ratio (SNR) for the denoised MCG traces is found to be slightly higher in the LMS algorithm as compared to the RLS algorithm. The results encourage the use of adaptive techniques to suppress noise due to power line frequency and its harmonics which occur frequently in biomedical measurements.

  16. Adaptive Data Filtering of Inertial Sensors with Variable Bandwidth

    Directory of Open Access Journals (Sweden)

    Mushfiqul Alam

    2015-02-01

    Full Text Available MEMS (micro-electro-mechanical system-based inertial sensors, i.e., accelerometers and angular rate sensors, are commonly used as a cost-effective solution for the purposes of navigation in a broad spectrum of terrestrial and aerospace applications. These tri-axial inertial sensors form an inertial measurement unit (IMU, which is a core unit of navigation systems. Even if MEMS sensors have an advantage in their size, cost, weight and power consumption, they suffer from bias instability, noisy output and insufficient resolution. Furthermore, the sensor’s behavior can be significantly affected by strong vibration when it operates in harsh environments. All of these constitute conditions require treatment through data processing. As long as the navigation solution is primarily based on using only inertial data, this paper proposes a novel concept in adaptive data pre-processing by using a variable bandwidth filtering. This approach utilizes sinusoidal estimation to continuously adapt the filtering bandwidth of the accelerometer’s data in order to reduce the effects of vibration and sensor noise before attitude estimation is processed. Low frequency vibration generally limits the conditions under which the accelerometers can be used to aid the attitude estimation process, which is primarily based on angular rate data and, thus, decreases its accuracy. In contrast, the proposed pre-processing technique enables using accelerometers as an aiding source by effective data smoothing, even when they are affected by low frequency vibration. Verification of the proposed concept is performed on simulation and real-flight data obtained on an ultra-light aircraft. The results of both types of experiments confirm the suitability of the concept for inertial data pre-processing.

  17. Modeling of Rate-Dependent Hysteresis Using a GPO-Based Adaptive Filter

    Science.gov (United States)

    Zhang, Zhen; Ma, Yaopeng

    2016-01-01

    A novel generalized play operator-based (GPO-based) nonlinear adaptive filter is proposed to model rate-dependent hysteresis nonlinearity for smart actuators. In the proposed filter, the input signal vector consists of the output of a tapped delay line. GPOs with various thresholds are used to construct a nonlinear network and connected with the input signals. The output signal of the filter is composed of a linear combination of signals from the output of GPOs. The least-mean-square (LMS) algorithm is used to adjust the weights of the nonlinear filter. The modeling results of four adaptive filter methods are compared: GPO-based adaptive filter, Volterra filter, backlash filter and linear adaptive filter. Moreover, a phenomenological operator-based model, the rate-dependent generalized Prandtl-Ishlinskii (RDGPI) model, is compared to the proposed adaptive filter. The various rate-dependent modeling methods are applied to model the rate-dependent hysteresis of a giant magnetostrictive actuator (GMA). It is shown from the modeling results that the GPO-based adaptive filter can describe the rate-dependent hysteresis nonlinear of the GMA more accurately and effectively. PMID:26861349

  18. Theory of affine projection algorithms for adaptive filtering

    CERN Document Server

    Ozeki, Kazuhiko

    2016-01-01

    This book focuses on theoretical aspects of the affine projection algorithm (APA) for adaptive filtering. The APA is a natural generalization of the classical, normalized least-mean-squares (NLMS) algorithm. The book first explains how the APA evolved from the NLMS algorithm, where an affine projection view is emphasized. By looking at those adaptation algorithms from such a geometrical point of view, we can find many of the important properties of the APA, e.g., the improvement of the convergence rate over the NLMS algorithm especially for correlated input signals. After the birth of the APA in the mid-1980s, similar algorithms were put forward by other researchers independently from different perspectives. This book shows that they are variants of the APA, forming a family of APAs. Then it surveys research on the convergence behavior of the APA, where statistical analyses play important roles. It also reviews developments of techniques to reduce the computational complexity of the APA, which are important f...

  19. Performance Improvement of the Goertzel Algorithm in Estimating of Protein Coding Regions Using Modified Anti-notch Filter and Linear Predictive Coding Model.

    Science.gov (United States)

    Farsani, Mahsa Saffari; Sahhaf, Masoud Reza Aghabozorgi; Abootalebi, Vahid

    2016-01-01

    The aim of this paper is to improve the performance of the conventional Goertzel algorithm in determining the protein coding regions in deoxyribonucleic acid (DNA) sequences. First, the symbolic DNA sequences are converted into numerical signals using electron ion interaction potential method. Then by combining the modified anti-notch filter and linear predictive coding model, we proposed an efficient algorithm to achieve the performance improvement in the Goertzel algorithm for estimating genetic regions. Finally, a thresholding method is applied to precisely identify the exon and intron regions. The proposed algorithm is applied to several genes, including genes available in databases BG570 and HMR195 and the results are compared to other methods based on the nucleotide level evaluation criteria. Results demonstrate that our proposed method reduces the number of incorrect nucleotides which are estimated to be in the noncoding region. In addition, the area under the receiver operating characteristic curve has improved by the factor of 1.35 and 1.12 in HMR195 and BG570 datasets respectively, in comparison with the conventional Goertzel algorithm.

  20. Simultaneous Learning and Filtering without Delusions: A Bayes-Optimal Derivation of Combining Predictive Inference and AdaptiveFiltering

    Directory of Open Access Journals (Sweden)

    Jan eKneissler

    2015-04-01

    Full Text Available Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF. PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than ten-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.

  1. Adaptive kernels in approximate filtering of state-space models

    Czech Academy of Sciences Publication Activity Database

    Dedecius, Kamil

    2017-01-01

    Roč. 31, č. 6 (2017), s. 938-952 ISSN 0890-6327 R&D Projects: GA ČR(CZ) GP14-06678P Institutional support: RVO:67985556 Keywords : filtering * nonlinear filters * Bayesian filtering * sequential Monte Carlo * approximate filtering Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.708, year: 2016 http:// library .utia.cs.cz/separaty/2016/AS/dedecius-0466448.pdf

  2. The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation.

    Science.gov (United States)

    Gao, Siwei; Liu, Yanheng; Wang, Jian; Deng, Weiwen; Oh, Heekuck

    2016-07-16

    This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix 'R' and the system noise V-C matrix 'Q'. Then, the global filter uses R to calculate the information allocation factor 'β' for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively.

  3. Optimal adaptive normalized matched filter for large antenna arrays

    KAUST Repository

    Kammoun, Abla

    2016-09-13

    This paper focuses on the problem of detecting a target in the presence of a compound Gaussian clutter with unknown statistics. To this end, we focus on the design of the adaptive normalized matched filter (ANMF) detector which uses the regularized Tyler estimator (RTE) built from N-dimensional observations x, · · ·, x in order to estimate the clutter covariance matrix. The choice for the RTE is motivated by its possessing two major attributes: first its resilience to the presence of outliers, and second its regularization parameter that makes it more suitable to handle the scarcity in observations. In order to facilitate the design of the ANMF detector, we consider the regime in which n and N are both large. This allows us to derive closed-form expressions for the asymptotic false alarm and detection probabilities. Based on these expressions, we propose an asymptotically optimal setting for the regularization parameter of the RTE that maximizes the asymptotic detection probability while keeping the asymptotic false alarm probability below a certain threshold. Numerical results are provided in order to illustrate the gain of the proposed detector over a recently proposed setting of the regularization parameter.

  4. Adaptation of a Filter Assembly to Assess Microbial Bioburden of Pressurant Within a Propulsion System

    Science.gov (United States)

    Benardini, James N.; Koukol, Robert C.; Schubert, Wayne W.; Morales, Fabian; Klatte, Marlin F.

    2012-01-01

    A report describes an adaptation of a filter assembly to enable it to be used to filter out microorganisms from a propulsion system. The filter assembly has previously been used for particulates greater than 2 micrometers. Projects that utilize large volumes of nonmetallic materials of planetary protection concern pose a challenge to their bioburden budget, as a conservative specification value of 30 spores per cubic centimeter is typically used. Helium was collected utilizing an adapted filtration approach employing an existing Millipore filter assembly apparatus used by the propulsion team for particulate analysis. The filter holder on the assembly has a 47-mm diameter, and typically a 1.2-5 micrometer pore-size filter is used for particulate analysis making it compatible with commercially available sterilization filters (0.22 micrometers) that are necessary for biological sampling. This adaptation to an existing technology provides a proof-of-concept and a demonstration of successful use in a ground equipment system. This adaptation has demonstrated that the Millipore filter assembly can be utilized to filter out microorganisms from a propulsion system, whereas in previous uses the filter assembly was utilized for particulates greater than 2 micrometers.

  5. Analysis and Design of Notch Filter-Based PLLs for Grid-Connected Applications Electric Power Systems Research

    DEFF Research Database (Denmark)

    Khazraj, Hesam; Silva, Filipe Miguel Faria da; Bak, Claus Leth

    2017-01-01

    applications. Therefore, their performance characteristics are rather unclear. To gain insight about the advantages and disadvantages of NNF-based PLLs (NNF-PLLs), analysis and design of these PLLs is conducted in this paper. This procedure includes: (1) selecting the appropriate number of NNFs inside the PLL...... is at the cost of a rather considerable increase in the PLL implementation complexity and computational effort, particularly when ANFs have their own frequency estimation mechanism. The non-adaptive NFs (NNFs), contrary to ANFs, are easy to implement. They, however, have received a little attention in PLL...

  6. [The application of adaptive algorithm and wavelet transform in the filtering of ECG signal].

    Science.gov (United States)

    Zhang, Jingzhou; Zhang, Guanglei; Dai, Guanzhong

    2006-10-01

    Electrocardiographic (ECG) signal are a kind of basic physiological signals of human body, and are very important in clinical diagnosis. But the ECG signals from body surface are often interfered by noises such as 50 Hz noise, baseline displacemant, electromyography (EMG) noise and edv. These noises bring obstacle to the diagnosis of cardiovascular diseases. To eliminate the ECG signals noises mentioned above,this paper adopts LMS adaptive algorithm and wavelet transform theory to design three kinds of digital adaptive filters-adaptive noise cancellation filter, wavelet transform filter and adaptive signal dividing filter to filter the corresponding noises. The results show that the three kinds of noises existing in the ECG signal have been efficiently eliminated.

  7. Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction

    OpenAIRE

    Sekihara, Kensuke; Sahani, Maneesh; Nagarajan, Srikantan S

    2005-01-01

    This paper discusses the location bias and the spatial resolution in the reconstruction of a single dipole source by various spatial filtering techniques used for neuromagnetic imaging. We first analyze the location bias for several representative adaptive and non-adaptive spatial filters using their resolution kernels. This analysis theoretically validates previously reported empirical findings that standardized low-resolution electromagnetic tomography (sLORETA) has no location bias. We als...

  8. Adaptive Filtering to Enhance Noise Immunity of Impedance and Admittance Spectroscopy: Comparison with Fourier Transformation

    Science.gov (United States)

    Stupin, Daniil D.; Koniakhin, Sergei V.; Verlov, Nikolay A.; Dubina, Michael V.

    2017-05-01

    The time-domain technique for impedance spectroscopy consists of computing the excitation voltage and current response Fourier images by fast or discrete Fourier transformation and calculating their relation. Here we propose an alternative method for excitation voltage and current response processing for deriving a system impedance spectrum based on a fast and flexible adaptive filtering method. We show the equivalence between the problem of adaptive filter learning and deriving the system impedance spectrum. To be specific, we express the impedance via the adaptive filter weight coefficients. The noise-canceling property of adaptive filtering is also justified. Using the RLC circuit as a model system, we experimentally show that adaptive filtering yields correct admittance spectra and elements ratings in the high-noise conditions when the Fourier-transform technique fails. Providing the additional sensitivity of impedance spectroscopy, adaptive filtering can be applied to otherwise impossible-to-interpret time-domain impedance data. The advantages of adaptive filtering are justified with practical living-cell impedance measurements.

  9. An Adjoint-Based Adaptive Ensemble Kalman Filter

    KAUST Repository

    Song, Hajoon

    2013-10-01

    A new hybrid ensemble Kalman filter/four-dimensional variational data assimilation (EnKF/4D-VAR) approach is introduced to mitigate background covariance limitations in the EnKF. The work is based on the adaptive EnKF (AEnKF) method, which bears a strong resemblance to the hybrid EnKF/three-dimensional variational data assimilation (3D-VAR) method. In the AEnKF, the representativeness of the EnKF ensemble is regularly enhanced with new members generated after back projection of the EnKF analysis residuals to state space using a 3D-VAR [or optimal interpolation (OI)] scheme with a preselected background covariance matrix. The idea here is to reformulate the transformation of the residuals as a 4D-VAR problem, constraining the new member with model dynamics and the previous observations. This should provide more information for the estimation of the new member and reduce dependence of the AEnKF on the assumed stationary background covariance matrix. This is done by integrating the analysis residuals backward in time with the adjoint model. Numerical experiments are performed with the Lorenz-96 model under different scenarios to test the new approach and to evaluate its performance with respect to the EnKF and the hybrid EnKF/3D-VAR. The new method leads to the least root-mean-square estimation errors as long as the linear assumption guaranteeing the stability of the adjoint model holds. It is also found to be less sensitive to choices of the assimilation system inputs and parameters.

  10. Tap-length optimization of adaptive filters used in stereophonic acoustic echo cancellation

    DEFF Research Database (Denmark)

    Kar, Asutosh; Swamy, M.N.S.

    2017-01-01

    the complexity of the tapped delay line structure for FIR adaptive filters. To overcome this problem, there is a need for an optimum tap-length-estimation algorithm that provides better convergence for the adaptive filters used in SAEC. This paper presents a solution to the problem of balancing convergence...... of acoustic echo paths. The tap-length optimization is applied to a single long adaptive filter with thousands of coefficients to decrease the total number of weights, which in turn reduces the computational load. To further increase the convergence rate, the proposed tap-length-optimization algorithm...

  11. An adaptive Kalman filter approach for cardiorespiratory signal extraction and fusion of non-contacting sensors.

    Science.gov (United States)

    Foussier, Jerome; Teichmann, Daniel; Jia, Jing; Misgeld, Berno; Leonhardt, Steffen

    2014-05-09

    Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min(-1) (0.3 min(-1)) and -0.7 bpm (1.7 bpm) (compared to -0.2 min(-1) (0.4 min(-1)) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed

  12. Distortion analysis of subband adaptive filtering methods for FMRI active noise control systems.

    Science.gov (United States)

    Milani, Ali A; Panahi, Issa M; Briggs, Richard

    2007-01-01

    Delayless subband filtering structure, as a high performance frequency domain filtering technique, is used for canceling broadband fMRI noise (8 kHz bandwidth). In this method, adaptive filtering is done in subbands and the coefficients of the main canceling filter are computed by stacking the subband weights together. There are two types of stacking methods called FFT and FFT-2. In this paper, we analyze the distortion introduced by these two stacking methods. The effect of the stacking distortion on the performance of different adaptive filters in FXLMS algorithm with non-minimum phase secondary path is explored. The investigation is done for different adaptive algorithms (nLMS, APA and RLS), different weight stacking methods, and different number of subbands.

  13. Adaptive oriented PDEs filtering methods based on new controlling speed function for discontinuous optical fringe patterns

    Science.gov (United States)

    Zhou, Qiuling; Tang, Chen; Li, Biyuan; Wang, Linlin; Lei, Zhenkun; Tang, Shuwei

    2018-01-01

    The filtering of discontinuous optical fringe patterns is a challenging problem faced in this area. This paper is concerned with oriented partial differential equations (OPDEs)-based image filtering methods for discontinuous optical fringe patterns. We redefine a new controlling speed function to depend on the orientation coherence. The orientation coherence can be used to distinguish the continuous regions and the discontinuous regions, and can be calculated by utilizing fringe orientation. We introduce the new controlling speed function to the previous OPDEs and propose adaptive OPDEs filtering models. According to our proposed adaptive OPDEs filtering models, the filtering in the continuous and discontinuous regions can be selectively carried out. We demonstrate the performance of the proposed adaptive OPDEs via application to the simulated and experimental fringe patterns, and compare our methods with the previous OPDEs.

  14. A biological inspired fuzzy adaptive window median filter (FAWMF) for enhancing DNA signal processing.

    Science.gov (United States)

    Ahmad, Muneer; Jung, Low Tan; Bhuiyan, Al-Amin

    2017-10-01

    Digital signal processing techniques commonly employ fixed length window filters to process the signal contents. DNA signals differ in characteristics from common digital signals since they carry nucleotides as contents. The nucleotides own genetic code context and fuzzy behaviors due to their special structure and order in DNA strand. Employing conventional fixed length window filters for DNA signal processing produce spectral leakage and hence results in signal noise. A biological context aware adaptive window filter is required to process the DNA signals. This paper introduces a biological inspired fuzzy adaptive window median filter (FAWMF) which computes the fuzzy membership strength of nucleotides in each slide of window and filters nucleotides based on median filtering with a combination of s-shaped and z-shaped filters. Since coding regions cause 3-base periodicity by an unbalanced nucleotides' distribution producing a relatively high bias for nucleotides' usage, such fundamental characteristic of nucleotides has been exploited in FAWMF to suppress the signal noise. Along with adaptive response of FAWMF, a strong correlation between median nucleotides and the Π shaped filter was observed which produced enhanced discrimination between coding and non-coding regions contrary to fixed length conventional window filters. The proposed FAWMF attains a significant enhancement in coding regions identification i.e. 40% to 125% as compared to other conventional window filters tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms. This study proves that conventional fixed length window filters applied to DNA signals do not achieve significant results since the nucleotides carry genetic code context. The proposed FAWMF algorithm is adaptive and outperforms significantly to process DNA signal contents. The algorithm applied to variety of DNA datasets produced noteworthy discrimination between coding and non-coding regions contrary

  15. Microwave Photonic Filters for Interference Cancellation and Adaptive Beamforming

    Science.gov (United States)

    Chang, John

    Wireless communication has experienced an explosion of growth, especially in the past half- decade, due to the ubiquity of wireless devices, such as tablets, WiFi-enabled devices, and especially smartphones. Proliferation of smartphones with powerful processors and graphic chips have given an increasing amount of people the ability to access anything from anywhere. Unfortunately, this ease of access has greatly increased mobile wireless bandwidth and have begun to stress carrier networks and spectra. Wireless interference cancellation will play a big role alongside the popularity of wire- less communication. In this thesis, we will investigate optical signal processing methods for wireless interference cancellation methods. Optics provide the perfect backdrop for interference cancellation. Mobile wireless data is already aggregated and transported through fiber backhaul networks in practice. By sandwiching the signal processing stage between the receiver and the fiber backhaul, processing can easily be done locally in one location. Further, optics offers the advantages of being instantaneously broadband and size, weight, and power (SWAP). We are primarily concerned with two methods for interference cancellation, based on microwave photonic filters, in this thesis. The first application is for a co-channel situation, in which a transmitter and receiver are co-located and transmitting at the same frequency. A novel analog optical technique extended for multipath interference cancellation of broadband signals is proposed and experimentally demonstrated in this thesis. The proposed architecture was able to achieve a maximum of 40 dB of cancellation over 200 MHz and 50 dB of cancellation over 10 MHz. The broadband nature of the cancellation, along with its depth, demonstrates both the precision of the optical components and the validity of the architecture. Next, we are interested in a scenario with dynamically changing interference, which requires an adaptive photonic

  16. Model Adaptation for Prognostics in a Particle Filtering Framework

    Data.gov (United States)

    National Aeronautics and Space Administration — One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated....

  17. Multi-template Scale-Adaptive Kernelized Correlation Filters

    KAUST Repository

    Bibi, Adel Aamer

    2015-12-07

    This paper identifies the major drawbacks of a very computationally efficient and state-of-the-art-tracker known as the Kernelized Correlation Filter (KCF) tracker. These drawbacks include an assumed fixed scale of the target in every frame, as well as, a heuristic update strategy of the filter taps to incorporate historical tracking information (i.e. simple linear combination of taps from the previous frame). In our approach, we update the scale of the tracker by maximizing over the posterior distribution of a grid of scales. As for the filter update, we prove and show that it is possible to use all previous training examples to update the filter taps very efficiently using fixed-point optimization. We validate the efficacy of our approach on two tracking datasets, VOT2014 and VOT2015.

  18. Improving the response of accelerometers for automotive applications by using LMS adaptive filters: Part II.

    Science.gov (United States)

    Hernandez, Wilmar; de Vicente, Jesús; Sergiyenko, Oleg Y; Fernández, Eduardo

    2010-01-01

    In this paper, the fast least-mean-squares (LMS) algorithm was used to both eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications, and improve the convergence rate of the filtering process based on the conventional LMS algorithm. The response of the accelerometer under test was corrupted by process and measurement noise, and the signal processing stage was carried out by using both conventional filtering, which was already shown in a previous paper, and optimal adaptive filtering. The adaptive filtering process relied on the LMS adaptive filtering family, which has shown to have very good convergence and robustness properties, and here a comparative analysis between the results of the application of the conventional LMS algorithm and the fast LMS algorithm to solve a real-life filtering problem was carried out. In short, in this paper the piezoresistive accelerometer was tested for a multi-frequency acceleration excitation. Due to the kind of test conducted in this paper, the use of conventional filtering was discarded and the choice of one adaptive filter over the other was based on the signal-to-noise ratio improvement and the convergence rate.

  19. Improving the Response of Accelerometers for Automotive Applications by Using LMS Adaptive Filters: Part II

    Directory of Open Access Journals (Sweden)

    Eduardo Fernández

    2010-01-01

    Full Text Available In this paper, the fast least-mean-squares (LMS algorithm was used to both eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications, and improve the convergence rate of the filtering process based on the conventional LMS algorithm. The response of the accelerometer under test was corrupted by process and measurement noise, and the signal processing stage was carried out by using both conventional filtering, which was already shown in a previous paper, and optimal adaptive filtering. The adaptive filtering process relied on the LMS adaptive filtering family, which has shown to have very good convergence and robustness properties, and here a comparative analysis between the results of the application of the conventional LMS algorithm and the fast LMS algorithm to solve a real-life filtering problem was carried out. In short, in this paper the piezoresistive accelerometer was tested for a multi-frequency acceleration excitation. Due to the kind of test conducted in this paper, the use of conventional filtering was discarded and the choice of one adaptive filter over the other was based on the signal-to-noise ratio improvement and the convergence rate.

  20. A pilot study on slit lamp-adapted optical coherence tomography imaging of trabeculectomy filtering blebs.

    NARCIS (Netherlands)

    Theelen, T.; Wesseling, P.; Keunen, J.E.E.; Klevering, B.J.

    2007-01-01

    BACKGROUND: Our study aims to identify anatomical characteristics of glaucoma filtering blebs by means of slit lamp-adapted optical coherence tomography (SL-OCT) and to identify new parameters for the functional prognosis of the filter in the early post-operative period. METHODS: Patients with

  1. Nonlinear diffusion filtering methods locally adapted to data features

    Science.gov (United States)

    Kollár, Michal; Čunderlík, Róbert; Mikula, Karol

    2017-04-01

    The contribution deals with nonlinear diffusion filtering methods on a planar surface. These methods represent an extension of the simple linear diffusion filtering by the nonlinear diffusivity coefficient. This coefficient represents a function which depends on data features such as gradient and local or global extrema of data. In the case of the regularized surface Perona-Malik model, method mostly used in image processing, the diffusivity coefficient represents the edge detector function. If we use the nonlinear diffusion filtering influenced by the Laplace operator, local extrema detector function affects the diffusion process. We use a finite-volume method to approximate numerically the nonlinear parabolic partial differential equation on uniform rectangle grid and finite difference method to approximate gradients and Laplacians. Numerical experiments present nonlinear diffusion filtering of artificial data and real measurements in upcoming filtering software with real-time filtered data visualization widget. Real measurements represent GOCE satellite observations, satellite-only MDT data, and high-resolution altimetry-derived gravity data. They aim to point out the main advantage of the nonlinear diffusion models which, on the contrary to linear models, preserve important structures of processed data.

  2. A New Adaptive Square-Root Unscented Kalman Filter for Nonlinear Systems with Additive Noise

    Directory of Open Access Journals (Sweden)

    Yong Zhou

    2015-01-01

    Full Text Available The Kalman filter (KF, extended KF, and unscented KF all lack a self-adaptive capacity to deal with system noise. This paper describes a new adaptive filtering approach for nonlinear systems with additive noise. Based on the square-root unscented KF (SRUKF, traditional Maybeck’s estimator is modified and extended to nonlinear systems. The square root of the process noise covariance matrix Q or that of the measurement noise covariance matrix R is estimated straightforwardly. Because positive semidefiniteness of Q or R is guaranteed, several shortcomings of traditional Maybeck’s algorithm are overcome. Thus, the stability and accuracy of the filter are greatly improved. In addition, based on three different nonlinear systems, a new adaptive filtering technique is described in detail. Specifically, simulation results are presented, where the new filter was applied to a highly nonlinear model (i.e., the univariate nonstationary growth model (UNGM. The UNGM is compared with the standard SRUKF to demonstrate its superior filtering performance. The adaptive SRUKF (ASRUKF algorithm can complete direct recursion and calculate the square roots of the variance matrixes of the system state and noise, which ensures the symmetry and nonnegative definiteness of the matrixes and greatly improves the accuracy, stability, and self-adaptability of the filter.

  3. Adaptive Filter Design Using Type-2 Fuzzy Cerebellar Model Articulation Controller.

    Science.gov (United States)

    Lin, Chih-Min; Yang, Ming-Shu; Chao, Fei; Hu, Xiao-Min; Zhang, Jun

    2016-10-01

    This paper aims to propose an efficient network and applies it as an adaptive filter for the signal processing problems. An adaptive filter is proposed using a novel interval type-2 fuzzy cerebellar model articulation controller (T2FCMAC). The T2FCMAC realizes an interval type-2 fuzzy logic system based on the structure of the CMAC. Due to the better ability of handling uncertainties, type-2 fuzzy sets can solve some complicated problems with outstanding effectiveness than type-1 fuzzy sets. In addition, the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so that the convergence of the filtering error can be guaranteed. In order to demonstrate the performance of the proposed adaptive T2FCMAC filter, it is tested in signal processing applications, including a nonlinear channel equalization system, a time-varying channel equalization system, and an adaptive noise cancellation system. The advantages of the proposed filter over the other adaptive filters are verified through simulations.

  4. Texture segmentation using adaptive Gabor filters based on HVS

    Science.gov (United States)

    Bi, Sheng; Liang, Dequn

    2006-02-01

    A texture segmentation algorithm based on HVS (Human Visual System) is proposed in this paper. Psychophysical and Neurophysiological conclusions have supported the hypothesis that the processing of afferent pictorial information in the HVS (the visual cortex in particular) involves two stages: the preattentive stage, and the focused attention stage. To simulate the preattentive stage of HVS, ring and wedge filtering methods are used to segment coarsely and the texture number in the input image is gotten. As texture is the repeating patterns of local variations in image intensity, we can use a part of the texture as the whole region representation. The inscribed squares in the coarse regions are transformed respectively to frequency domain and each spectrum is analyzed in detail. New texture measurements based on the Fourier spectrums are given. Through analyzing the measurements of the texture, including repeatability directionality and regularity, we can extract the feature, and determine the parameters of the Gabor filter-bank. Then to simulate the focused attention stage of HVS, the determined Gabor filter-bank is used to filter the original input image to produce fine segmentation regions. This approach performs better in computational complexity and feature extraction than the fixed parameters and fixed stages Gabor filter-bank approaches.

  5. SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

    Energy Technology Data Exchange (ETDEWEB)

    Iliopoulos, AS; Sun, X [Duke University, Durham, NC (United States); Floros, D [Aristotle University of Thessaloniki (Greece); Zhang, Y; Yin, FF; Ren, L [Duke University Medical Center, Durham, NC (United States); Pitsianis, N [Aristotle University of Thessaloniki (Greece); Duke University, Durham, NC (United States)

    2016-06-15

    Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well as histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial

  6. Gain optimized cosine transform domain LMS algorithm for adaptive filtering of EEG.

    Science.gov (United States)

    Olkkonen, H; Pesola, P; Valjakka, A; Tuomisto, L

    1999-03-01

    The most common adaptive filtering method is based on the least mean square (LMS) algorithm, which updates the filter coefficients by a gradient based method. The convergence properties of the LMS algorithm can be improved by updating the filter coefficients in the frequency domain. This work presents a new LMS algorithm, which updates the filter coefficients in the cosine transform domain. Instead of a constant gain factor in the coefficient updating the present method uses a time-varying optimized gain factor. This yields a considerably improved convergence performance. The algorithm was applied to the EEG activity analysis of freely behaving rats.

  7. Adaptive imaging spectrometer in a time-domain filtering architecturedaptive Imaging Spectrometer in a Time-Domain Filtering Architecture

    Science.gov (United States)

    Jiao, Yang; Bhalotra, Sameer R.; Kung, Helen L.; Miller, David A. B.

    2003-08-01

    We demonstrate an imaging spectrometer with 30nm resolution that utilizes a novel time-domain filtering architecture. The architecture is based on a pixel by pixel integration of the interferogram signal mixed with reference waveforms. The system can be adapted in real time to discriminate between LED sources of different wavelengths, perform signal processing on the spectra, as well as discriminate between highly overlapping, broadband spectral features in a scene illuminated by a tungsten lamp. Unlike a conventional spectral signature discrimination system, which needs a dedicated computation subsystem running a discrimination algorithm, the time-domain filtering architecture embeds much of the computation in the filtering, which will aid the design of integrated miniaturized spectral signature discrimination systems.

  8. A model for radar images and its application to adaptive digital filtering of multiplicative noise.

    Science.gov (United States)

    Frost, V S; Stiles, J A; Shanmugan, K S; Holtzman, J C

    1982-02-01

    Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.

  9. Cancellation of artifacts in ECG signals using a normalized adaptive neural filter.

    Science.gov (United States)

    Wu, Yunfeng; Rangayyan, Rangaraj M; Ng, Sin-Chun

    2007-01-01

    Denoising electrocardiographic (ECG) signals is an essential procedure prior to their analysis. In this paper, we present a normalized adaptive neural filter (NANF) for cancellation of artifacts in ECG signals. The normalized filter coefficients are updated by the steepest-descent algorithm; the adaptation process is designed to minimize the difference between second-order estimated output values and the desired artifact-free ECG signals. Empirical results with benchmark data show that the adaptive artifact canceller that includes the NANF can effectively remove muscle-contraction artifacts and high-frequency noise in ambulatory ECG recordings, leading to a high signal-to-noise ratio. Moreover, the performance of the NANF in terms of the root-mean-squared error, normalized correlation coefficient, and filtered artifact entropy is significantly better than that of the popular least-mean-square (LMS) filter.

  10. Real-time 3D adaptive filtering for portable imaging systems

    Science.gov (United States)

    Bockenbach, Olivier; Ali, Murtaza; Wainwright, Ian; Nadeski, Mark

    2015-03-01

    Portable imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often not able to run with sufficient performance on a portable platform. In recent years, advanced multicore DSPs have been introduced that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms like 3D adaptive filtering, improving the image quality of portable medical imaging devices. In this study, the performance of a 3D adaptive filtering algorithm on a digital signal processor (DSP) is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec.

  11. Signal-to-noise ratio adaptive post-filtering method for intelligibility enhancement of telephone speech.

    Science.gov (United States)

    Jokinen, Emma; Yrttiaho, Santeri; Pulakka, Hannu; Vainio, Martti; Alku, Paavo

    2012-12-01

    Post-filtering can be utilized to improve the quality and intelligibility of telephone speech. Previous studies have shown that energy reallocation with a high-pass type filter works effectively in improving the intelligibility of speech in difficult noise conditions. The present study introduces a signal-to-noise ratio adaptive post-filtering method that utilizes energy reallocation to transfer energy from the first formant to higher frequencies. The proposed method adapts to the level of the background noise so that, in favorable noise conditions, the post-filter has a flat frequency response and the effect of the post-filtering is increased as the level of the ambient noise increases. The performance of the proposed method is compared with a similar post-filtering algorithm and unprocessed speech in subjective listening tests which evaluate both intelligibility and listener preference. The results indicate that both of the post-filtering methods maintain the quality of speech in negligible noise conditions and are able to provide intelligibility improvement over unprocessed speech in adverse noise conditions. Furthermore, the proposed post-filtering algorithm performs better than the other post-filtering method under evaluation in moderate to difficult noise conditions, where intelligibility improvement is mostly required.

  12. DSP based adaptive hysteresis-band current controlled active filter ...

    African Journals Online (AJOL)

    The use of non-linear loads critically affects the quality of supply by drawing harmonic currents and reactive power from the electrical distribution system. Active power filters are the most viable solution for solving such power quality problems in compliance with the harmonic standards. This article presents a digital signal ...

  13. Adaptive filtering for stochastic volatility by using exact sampling

    NARCIS (Netherlands)

    Aihara, ShinIchi; Bagchi, Arunabha; Saha, S.

    2013-01-01

    We study the sequential identification problem for Bates stochastic volatility model, which is widely used as the model of a stock in finance. By using the exact simulation method, a particle filter for estimating stochastic volatility is constructed. The systems parameters are sequentially

  14. Localization bias and spatial resolution of adaptive and non-adaptive spatial filters for MEG source reconstruction.

    Science.gov (United States)

    Sekihara, Kensuke; Sahani, Maneesh; Nagarajan, Srikantan S

    2005-05-01

    This paper discusses the location bias and the spatial resolution in the reconstruction of a single dipole source by various spatial filtering techniques used for neuromagnetic imaging. We first analyze the location bias for several representative adaptive and non-adaptive spatial filters using their resolution kernels. This analysis theoretically validates previously reported empirical findings that standardized low-resolution electromagnetic tomography (sLORETA) has no location bias. We also find that the minimum-variance spatial filter does exhibit bias in the reconstructed location of a single source, but that this bias is eliminated by using the normalized lead field. We then focus on the comparison of sLORETA and the lead-field normalized minimum-variance spatial filter, and analyze the effect of noise on source location bias. We find that the signal-to-noise ratio (SNR) in the measurements determines whether the sLORETA reconstruction has source location bias, while the lead-field normalized minimum-variance spatial filter has no location bias even in the presence of noise. Finally, we compare the spatial resolution for sLORETA and the minimum-variance filter, and show that the minimum-variance filter attains much higher resolution than sLORETA does. The results of these analyses are validated by numerical experiments as well as by reconstructions based on two sets of evoked magnetic responses.

  15. The role of adaptive immunity as an ecological filter on the gut microbiota in zebrafish.

    Science.gov (United States)

    Stagaman, Keaton; Burns, Adam R; Guillemin, Karen; Bohannan, Brendan Jm

    2017-07-01

    All animals live in intimate association with communities of microbes, collectively referred to as their microbiota. Certain host traits can influence which microbial taxa comprise the microbiota. One potentially important trait in vertebrate animals is the adaptive immune system, which has been hypothesized to act as an ecological filter, promoting the presence of some microbial taxa over others. Here we surveyed the intestinal microbiota of 68 wild-type zebrafish, with functional adaptive immunity, and 61 rag1 - zebrafish, lacking functional B- and T-cell receptors, to test the role of adaptive immunity as an ecological filter on the intestinal microbiota. In addition, we tested the robustness of adaptive immunity's filtering effects to host-host interaction by comparing the microbiota of fish populations segregated by genotype to those containing both genotypes. The presence of adaptive immunity individualized the gut microbiota and decreased the contributions of neutral processes to gut microbiota assembly. Although mixing genotypes led to increased phylogenetic diversity in each, there was no significant effect of adaptive immunity on gut microbiota composition in either housing condition. Interestingly, the most robust effect on microbiota composition was co-housing within a tank. In all, these results suggest that adaptive immunity has a role as an ecological filter of the zebrafish gut microbiota, but it can be overwhelmed by other factors, including transmission of microbes among hosts.

  16. Independent motion detection with a rival penalized adaptive particle filter

    Science.gov (United States)

    Becker, Stefan; Hübner, Wolfgang; Arens, Michael

    2014-10-01

    Aggregation of pixel based motion detection into regions of interest, which include views of single moving objects in a scene is an essential pre-processing step in many vision systems. Motion events of this type provide significant information about the object type or build the basis for action recognition. Further, motion is an essential saliency measure, which is able to effectively support high level image analysis. When applied to static cameras, background subtraction methods achieve good results. On the other hand, motion aggregation on freely moving cameras is still a widely unsolved problem. The image flow, measured on a freely moving camera is the result from two major motion types. First the ego-motion of the camera and second object motion, that is independent from the camera motion. When capturing a scene with a camera these two motion types are adverse blended together. In this paper, we propose an approach to detect multiple moving objects from a mobile monocular camera system in an outdoor environment. The overall processing pipeline consists of a fast ego-motion compensation algorithm in the preprocessing stage. Real-time performance is achieved by using a sparse optical flow algorithm as an initial processing stage and a densely applied probabilistic filter in the post-processing stage. Thereby, we follow the idea proposed by Jung and Sukhatme. Normalized intensity differences originating from a sequence of ego-motion compensated difference images represent the probability of moving objects. Noise and registration artefacts are filtered out, using a Bayesian formulation. The resulting a posteriori distribution is located on image regions, showing strong amplitudes in the difference image which are in accordance with the motion prediction. In order to effectively estimate the a posteriori distribution, a particle filter is used. In addition to the fast ego-motion compensation, the main contribution of this paper is the design of the probabilistic

  17. Efficient implementation of adaptive filters using TMS320C6713 DSP platform

    Directory of Open Access Journals (Sweden)

    Diogo Kaoru Takayama

    2011-06-01

    Full Text Available This paper presents a methodology for accelerated development of solution associated to adaptive filtering using Matlab/Simulink, Code Composer Studio and DSK 6713 digital signal processing (DSP technologies. The purpose of this methodology is to provide an efficient and rapid method to develop and test adaptive filters in DSPs. The methodology development represents a very important tool for the engineer in charge of design-simulation-implementation of adaptive filters. Another important benefit is that it avoids low level hardware work that can be tedious and time consuming. An example of application is presented in this paper in order to illustrate the feasibility of this methodology. The methodology is applied in order to implement an adaptive filter in the DSP platform. The project steps are discussed in details, including the methods of transforming the Matlab code into DSP code. The results are analyzed in terms of accuracy and convergence speed. The TMS320C6713 development kit supplied by Spectrum Digital Inc., that includes a float point DSP, was used to implement the adaptive filter.

  18. Predicting respiratory tumor motion with multi-dimensional adaptive filters and support vector regression

    Energy Technology Data Exchange (ETDEWEB)

    Riaz, Nadeem; Wiersma, Rodney; Mao Weihua; Xing Lei [Department of Radiation Oncology, Stanford University, 875 Blake Wilbur Drive, Stanford, CA 94305-5847 (United States); Shanker, Piyush; Gudmundsson, Olafur; Widrow, Bernard [Department of Electrical Engineering, Stanford University, Stanford, CA 94305 (United States)], E-mail: nriaz@stanford.edu

    2009-10-07

    Intra-fraction tumor tracking methods can improve radiation delivery during radiotherapy sessions. Image acquisition for tumor tracking and subsequent adjustment of the treatment beam with gating or beam tracking introduces time latency and necessitates predicting the future position of the tumor. This study evaluates the use of multi-dimensional linear adaptive filters and support vector regression to predict the motion of lung tumors tracked at 30 Hz. We expand on the prior work of other groups who have looked at adaptive filters by using a general framework of a multiple-input single-output (MISO) adaptive system that uses multiple correlated signals to predict the motion of a tumor. We compare the performance of these two novel methods to conventional methods like linear regression and single-input, single-output adaptive filters. At 400 ms latency the average root-mean-square-errors (RMSEs) for the 14 treatment sessions studied using no prediction, linear regression, single-output adaptive filter, MISO and support vector regression are 2.58, 1.60, 1.58, 1.71 and 1.26 mm, respectively. At 1 s, the RMSEs are 4.40, 2.61, 3.34, 2.66 and 1.93 mm, respectively. We find that support vector regression most accurately predicts the future tumor position of the methods studied and can provide a RMSE of less than 2 mm at 1 s latency. Also, a multi-dimensional adaptive filter framework provides improved performance over single-dimension adaptive filters. Work is underway to combine these two frameworks to improve performance.

  19. Robust Adaptive Filter for Small Satellite Attitude Estimation Based on Magnetometer and Gyro

    Directory of Open Access Journals (Sweden)

    Zhankui Zeng

    2014-01-01

    Full Text Available Based on magnetometer and gyro measurement, a sequential scheme is proposed to determine the orbit and attitude of small satellite simultaneously. In order to reduce the impact of orbital errors on attitude estimation, a robust adaptive Kalman filter is developed. It uses a scale factor and an adaptive factor, which are constructed by Huber function and innovation sequence, respectively, to adjust the covariance matrix of system state and observational noise, change the weights of predicted and measured parameters, get suitable Kalman filter gain and approximate optimal filtering results. Numerical simulations are carried out and the proposed filter is approved to be robust for the noise disturbance and parameter uncertainty and can provide higher accuracy attitude estimation.

  20. Optimizing Cost of Continuous Overlapping Queries over Data Streams by Filter Adaption

    KAUST Repository

    Xie, Qing

    2016-01-12

    The problem we aim to address is the optimization of cost management for executing multiple continuous queries on data streams, where each query is defined by several filters, each of which monitors certain status of the data stream. Specially the filter can be shared by different queries and expensive to evaluate. The conventional objective for such a problem is to minimize the overall execution cost to solve all queries, by planning the order of filter evaluation in shared strategy. However, in streaming scenario, the characteristics of data items may change in process, which can bring some uncertainty to the outcome of individual filter evaluation, and affect the plan of query execution as well as the overall execution cost. In our work, considering the influence of the uncertain variation of data characteristics, we propose a framework to deal with the dynamic adjustment of filter ordering for query execution on data stream, and focus on the issues of cost management. By incrementally monitoring and analyzing the results of filter evaluation, our proposed approach can be effectively adaptive to the varied stream behavior and adjust the optimal ordering of filter evaluation, so as to optimize the execution cost. In order to achieve satisfactory performance and efficiency, we also discuss the trade-off between the adaptivity of our framework and the overhead incurred by filter adaption. The experimental results on synthetic and two real data sets (traffic and multimedia) show that our framework can effectively reduce and balance the overall query execution cost and keep high adaptivity in streaming scenario.

  1. Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering.

    Science.gov (United States)

    Sudeep, P V; Issac Niwas, S; Palanisamy, P; Rajan, Jeny; Xiaojun, Yu; Wang, Xianghong; Luo, Yuemei; Liu, Linbo

    2016-04-01

    Optical coherence tomography (OCT) has continually evolved and expanded as one of the most valuable routine tests in ophthalmology. However, noise (speckle) in the acquired images causes quality degradation of OCT images and makes it difficult to analyze the acquired images. In this paper, an iterative approach based on bilateral filtering is proposed for speckle reduction in multiframe OCT data. Gamma noise model is assumed for the observed OCT image. First, the adaptive version of the conventional bilateral filter is applied to enhance the multiframe OCT data and then the bias due to noise is reduced from each of the filtered frames. These unbiased filtered frames are then refined using an iterative approach. Finally, these refined frames are averaged to produce the denoised OCT image. Experimental results on phantom images and real OCT retinal images demonstrate the effectiveness of the proposed filter. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Adaptive-Fuzzy Controller Based Shunt Active Filter for Power Line Conditioners

    Directory of Open Access Journals (Sweden)

    KamalaKanta Mahapatra

    2011-08-01

    Full Text Available This paper presents a novel Fuzzy Logic Controller (FLC in conjunction with Phase Locked Loop (PLL based shunt active filter for Power Line Conditioners (PLCs to improve the power quality in the distribution system. The active filter is implemented with current controlled Voltage Source Inverter (VSI for compensating current harmonics and reactive power at the point of common coupling. The VSI gate control switching pulses are derived from proposed Adaptive-Fuzzy-Hysteresis Current Controller (HCC and this method calculates the hysteresis bandwidth effectively using fuzzy logic. The bandwidth can be adjusted based on compensation current variation, which is used to optimize the required switching frequency and improves active filter substantially. These shunt active power filter system is investigated and verified under steady and transient-state with non-linear load conditions. This shunt active filter is in compliance with IEEE 519 and IEC 61000-3 recommended harmonic standards.

  3. A study of infrared spectroscopy de-noising based on LMS adaptive filter

    Science.gov (United States)

    Mo, Jia-qing; Lv, Xiao-yi; Yu, Xiao

    2015-12-01

    Infrared spectroscopy has been widely used, but which often contains a lot of noise, so the spectral characteristic of the sample is seriously affected. Therefore the de-noising is very important in the spectrum analysis and processing. In the study of infrared spectroscopy, the least mean square (LMS) adaptive filter was applied in the field firstly. LMS adaptive filter algorithm can reserve the detail and envelope of the effective signal when the method was applied to infrared spectroscopy of breast cancer which signal-to-noise ratio (SNR) is lower than 10 dB, contrast and analysis the result with result of wavelet transform and ensemble empirical mode decomposition (EEMD). The three evaluation standards (SNR, root mean square error (RMSE) and the correlation coefficient (ρ)) fully proved de-noising advantages of LMS adaptive filter in infrared spectroscopy of breast cancer.

  4. Adaptive Matrices and Filters for Color Texture Classification

    NARCIS (Netherlands)

    Giotis, Ioannis; Bunte, Kerstin; Petkov, Nicolai; Biehl, Michael

    In this paper we introduce an integrative approach towards color texture classification and recognition using a supervised learning framework. Our approach is based on Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure, which is defined in the Fourier domain,

  5. Seasonal signal capturing in time series of up coordinates by means of adaptive filters

    Science.gov (United States)

    Yalvac, S.; Ustun, A.

    2013-12-01

    Digital filters, is a system that performs mathematical operations on a sampled or discrete time signals. Adaptive filters designed for noise canceling are capable tools of decomposing correlated parts of data sets. This kind of filters which optimize itself using Least Mean Square (LMS) algorithm is a powerful tool for understand the truth hidden into the complex data sets like time series in Geosciences. The complex data sets such as CGPS (Continuously operating reference station) station's time series can be understood better with adaptive noise canceling by means of decompose coherent (seasonal effect, tectonic plate motion) and incoherent (noise; site-specific effects) parts of data. In this study, it is aimed to model the subsidence caused by groundwater withdrawal based on the seasonal correlation between consecutive years of CGPS time series. For this purpose, two stations where located into subsidence area of 3 year time series have analyzed with adaptive noise canceling filter. According to the results, the annual movement of these two stations have strong relationship. Also, subsidence behavior are correlated with annual rainfall data. BELD station one year filtered movement KAMN station one year filtered movements

  6. Enhancing obstetric and gynecology ultrasound images by adaptation of the speckle reducing anisotropic diffusion filter.

    Science.gov (United States)

    Munteanu, Cristian; Morales, Francisco Cabrera; Fernández, Javier González; Rosa, Agostinho; Déniz, Luís Gómez

    2008-07-01

    So far there is no ideal speckle reduction filtering technique that is capable of enhancing and reducing the level of noise in medical ultrasound (US) images, while efficiently responding to medical experts' validation criteria which quite often include a subjective component. This paper presents an interactive tool called evolutionary speckle reducing anisotropic diffusion filter (EVOSRAD) that performs adaptive speckle filtering on ultrasound B-mode still images. The medical expert runs the algorithm interactively, having a permanent control over the output, and guiding the filtering process towards obtaining enhanced images that agree to his/her subjective quality criteria. We employ an interactive evolutionary algorithm (IGA) to adapt on-line the parameters of a speckle reducing anisotropic diffusion (SRAD) filter. For a given input US image, the algorithm evolves the parameters of the SRAD filter according to subjective criteria of the medical expert who runs the interactive algorithm. The method and its validation are applied to a test bed comprising both real and simulated obstetrics and gynecology (OB/GYN) ultrasound images. The potential of the method is analyzed in comparison to other speckle reduction filters: the original SRAD filter, the anisotropic diffusion, offset and median filters. Results obtained show the good potential of the method on several classes of OB/GYN ultrasound images, as well as on a synthetic image simulating a real fetal US image. Quality criteria for the evaluation and validation of the method include subjective scoring given by the medical expert who runs the interactive method, as well as objective global and local quality criteria. The method presented allows the medical expert to design its own filters according to the degree of medical expertise as well as to particular and often subjective assessment criteria. A filter is designed for a given class of ultrasound images and for a given medical expert who will later use the

  7. Multiple Iteration of Weight Updates for Least Mean Square Adaptive Filter in Active Noise Control Application

    Directory of Open Access Journals (Sweden)

    Mustafa Rahimie

    2017-01-01

    Full Text Available The method of least mean square (LMS is the commonly used algorithm in Adaptive filter due to its simplicity and robustness in implementation. In Active Noise Control application, a filtered reference signal is used prior to LMS algorithm to overcome the constraint on stability and convergence performance of the system due to the existence of the auxiliary path. This is known as Filtered-X LMS algorithm. In conventional Filtered-X LMS algorithm, each filter weight is updated once on every audio sample. This paper proposes the improved version of Filtered-X LMS algorithm with the use of multiple iteration of filter weight on every sample of audio signal. The proposed work uses field programmable gate arrays to realize real-time simulation on hardware for the noise signal of 500 Hz. Results from the real-time hardware simulations have shown much faster error convergence and better adaptation performance for different selections of learning constant μ, as compared with the conventional method.

  8. Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI.

    Science.gov (United States)

    Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

    2017-04-01

    Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We introduce new algorithms for reducing EEG artifacts due to simultaneous fMRI The algorithms combine a reference layer and adaptive filtering Several

  9. An Application Specific Instruction Set Processor (ASIP) for Adaptive Filters in Neural Prosthetics.

    Science.gov (United States)

    Xin, Yao; Li, Will X Y; Zhang, Zhaorui; Cheung, Ray C C; Song, Dong; Berger, Theodore W

    2015-01-01

    Neural coding is an essential process for neuroprosthetic design, in which adaptive filters have been widely utilized. In a practical application, it is needed to switch between different filters, which could be based on continuous observations or point process, when the neuron models, conditions, or system requirements have changed. As candidates of coding chip for neural prostheses, low-power general purpose processors are not computationally efficient especially for large scale neural population coding. Application specific integrated circuits (ASICs) do not have flexibility to switch between different adaptive filters while the cost for design and fabrication is formidable. In this research work, we explore an application specific instruction set processor (ASIP) for adaptive filters in neural decoding activity. The proposed architecture focuses on efficient computation for the most time-consuming matrix/vector operations among commonly used adaptive filters, being able to provide both flexibility and throughput. Evaluation and implementation results are provided to demonstrate that the proposed ASIP design is area-efficient while being competitive to commercial CPUs in computational performance.

  10. A globally stable autopilot with wave filter using only yaw angle measurements

    Directory of Open Access Journals (Sweden)

    Trygve Lauvdal

    1996-04-01

    Full Text Available A stable minimum phase transfer function from rudder angle to yaw angle is used to design a globally stable adaptive ship autopilot. First-order wave disturbances in yaw are filtered by applying a notch filter. Integral action is introduced by using a reference model technique. Global stability is proven for the total system which include the yaw rate observer, the parameter update law, the feedback controller, the notch filter and the integral part of the controller. The simulation results showed that the performance is excellent, even with no a priori knowledge of the ship parameters.

  11. Adaptive Collaborative Gaussian Mixture Probability Hypothesis Density Filter for Multi-Target Tracking.

    Science.gov (United States)

    Yang, Feng; Wang, Yongqi; Chen, Hao; Zhang, Pengyan; Liang, Yan

    2016-10-11

    In this paper, an adaptive collaborative Gaussian Mixture Probability Hypothesis Density (ACo-GMPHD) filter is proposed for multi-target tracking with automatic track extraction. Based on the evolutionary difference between the persistent targets and the birth targets, the measurements are adaptively partitioned into two parts, persistent and birth measurement sets, for updating the persistent and birth target Probability Hypothesis Density, respectively. Furthermore, the collaboration mechanism of multiple probability hypothesis density (PHDs) is established, where tracks can be automatically extracted. Simulation results reveal that the proposed filter yields considerable computational savings in processing requirements and significant improvement in tracking accuracy.

  12. An Experimental Assessment of Transverse Adaptive Fir Filters as Applied to Vibrating Structures Identification

    Directory of Open Access Journals (Sweden)

    Daniel A. Castello

    2005-01-01

    Full Text Available The present work is aimed at assessing the performance of adaptive Finite Impulse Response (FIR filters on the identification of vibrating structures. Four adaptive algorithms were used: Least Mean Squares (LMS, Normalized Least Mean Squares (NLMS, Transform-Domain Least Mean Squares (TD – LMS and Set-Membership Binormalized Data-Reusing LMS Algorithm (SM – BNDRLMS. The capability of these filters to perform the identification of vibrating structures is shown on real experiments. The first experiment consists of an aluminum cantilever beam containing piezoelectric sensors and actuators and the second one is a steel pinned-pinned beam instrumented with accelerometers and an electromechanical shaker.

  13. Performance Analysis of Adaptive Volterra Filters in the Finite-Alphabet Input Case

    Directory of Open Access Journals (Sweden)

    Jaïdane Mériem

    2004-01-01

    Full Text Available This paper deals with the analysis of adaptive Volterra filters, driven by the LMS algorithm, in the finite-alphabet inputs case. A tailored approach for the input context is presented and used to analyze the behavior of this nonlinear adaptive filter. Complete and rigorous mean square analysis is provided without any constraining independence assumption. Exact transient and steady-state performances expressed in terms of critical step size, rate of transient decrease, optimal step size, excess mean square error in stationary mode, and tracking nonstationarities are deduced.

  14. SIMULATION AND PERFORMANCE ANALYASIS OF ADAPTIVE FILTER IN NOISE CANCELLATION

    OpenAIRE

    RAJ KUMAR THENUA,; S.K. AGARWAL

    2010-01-01

    Noise problems in the environment have gained attention due to the tremendous growth of technology that has led to noisy engines, heavy machinery, high speed wind buffeting and other noise sources. The problem of controlling the noise level has become the focus of a tremendous amount of research over the years. In last few years various adaptive algorithms are developed for noise cancellation. In this paper we present an implementation of LMS (Least Mean Square), NLMS (Normalized Least Mean S...

  15. Instantaneous Attitude Determination Based on Original Multi-antenna Observations Using Adaptively Robust Kalman Filtering

    Directory of Open Access Journals (Sweden)

    GAN Yu

    2015-09-01

    Full Text Available Attitude determination directly by carrier phase observation makes optimal use of observation and attitude constraints. The phase models based on misalignment angle and multiplicative quaternion error are derived. The state models for attitude estimation with and without external angular rate sensors are both erected. The attitude errors are estimated by adaptively robust filtering, in which the adaptive factors of ambiguity and attitude error are decided respectively following the idea of multi adaptive factor filtering. The factor of attitude is determined by a three-section function containing Ratio. Adaptively robust filtering makes the best use of constraint and historical information, fusing them in the calculation of float solution. As the accuracy of float solution and the structure of covariance matrix are improved greatly, the fix solution can be searched efficiently using LAMBDA (least-squares ambiguity decorrelation adjustment method merely, perfectly fulfilling the real-time requirement. Field test of a ship-based three-antenna attitude system is used to validate the proposed method. It is showed that direct attitude determination based on adaptively robust filtering has obvious advantages in efficiency and reliability.

  16. Median Modified Wiener Filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra

    KAUST Repository

    Cannistraci, Carlo Vittorio

    2015-01-26

    Denoising multidimensional NMR-spectra is a fundamental step in NMR protein structure determination. The state-of-the-art method uses wavelet-denoising, which may suffer when applied to non-stationary signals affected by Gaussian-white-noise mixed with strong impulsive artifacts, like those in multi-dimensional NMR-spectra. Regrettably, Wavelet\\'s performance depends on a combinatorial search of wavelet shapes and parameters; and multi-dimensional extension of wavelet-denoising is highly non-trivial, which hampers its application to multidimensional NMR-spectra. Here, we endorse a diverse philosophy of denoising NMR-spectra: less is more! We consider spatial filters that have only one parameter to tune: the window-size. We propose, for the first time, the 3D extension of the median-modified-Wiener-filter (MMWF), an adaptive variant of the median-filter, and also its novel variation named MMWF*. We test the proposed filters and the Wiener-filter, an adaptive variant of the mean-filter, on a benchmark set that contains 16 two-dimensional and three-dimensional NMR-spectra extracted from eight proteins. Our results demonstrate that the adaptive spatial filters significantly outperform their non-adaptive versions. The performance of the new MMWF* on 2D/3D-spectra is even better than wavelet-denoising. Noticeably, MMWF* produces stable high performance almost invariant for diverse window-size settings: this signifies a consistent advantage in the implementation of automatic pipelines for protein NMR-spectra analysis.

  17. FPGA/NIOS Implementation of an Adaptive FIR Filter Using Linear Prediction to Reduce Narrow-Band RFI for Radio Detection of Cosmic Rays

    Science.gov (United States)

    Szadkowski, Zbigniew; Fraenkel, E. D.; van den Berg, Ad M.

    2013-10-01

    with the EP4CE115F29C7 from the Cyclone IV family and the EP3C120F780C7 from the Cyclone III family at a 170 MHz sampling rate, a 12-bit I/O resolution, and an internal 30-bit dynamic range. Most of the slow floating-point NIOS calculations have been moved to the FPGA logic segments as extended fixed-point operations, which significantly reduced the refreshing time of the coefficients used in the LP. We conclude that the LP is a viable alternative to other methods such as non-adaptive methods involving digital notch filters or multiple time-to-frequency domain conversions using an FFT procedure.

  18. Design of an Adapter for Air Outlet Filter on the M431 Chemical Agent Detector

    Science.gov (United States)

    1990-08-01

    lank SUMMARY SRI International has developed an adapter that will allow an outlet air filter to be easily attah Cd to and removed from the exhaust port...AGENT DETECTOR E1LECTE f EO-. -- _j Larry S. Gu~lman Thomas P. Low SRI INTERNATIONAL Menlo Park, CA 94025-3493 August 1990 U.S. ARMY ARMAMEN NJ...projected operating temperatures. SRI has investigated adapter design alternatives, including the selection of appropriate materials and methods of

  19. AN ADAPTIVE MORPHOLOGICAL MEAN FILTER FOR VERY HIGH-RESOLUTION REMOTE SENSING IMAGE PROCESSING

    Directory of Open Access Journals (Sweden)

    Z. Lv

    2017-09-01

    Full Text Available Very high resolution (VHR remote sensing imagery can reveal the ground object in greater detail, depicting their color, shape, size and structure. However, VHR also leads much original noise in spectra, and this original noise may reduce the reliability of the classification’s result. This paper presents an Adaptive Morphological Mean Filter (AMMF for smoothing the original noise of VHR imagery and improving the classification’s performance. AMMF is a shape-adaptive filter which is constructed by detecting gradually the spectral similarity between a kernel-anchored pixel and its contextual pixels through an extension-detector with 8-neighbouring pixels, and the spectral value of the kernel-anchored pixel is instead by the mean of group pixels within the adaptive region. The classification maps based on the AMMF are compared with the classification of VHR images based on the homologous filter processing, such as Mean Filter (MF and Median Filter(MedF. The experimental results suggest the following: 1 VHR image processed using AMMF can not only preserve the detail information among inter-classes but also smooth the noise within intra-class; 2 The proposed AMMF processing can improve the classification’s performance of VHR image, and it obtains a better visual performance and accuracy while comparing with MF and MedF.

  20. Adaptive Conflict-Free Optimization of Rule Sets for Network Security Packet Filtering Devices

    Directory of Open Access Journals (Sweden)

    Andrea Baiocchi

    2015-01-01

    Full Text Available Packet filtering and processing rules management in firewalls and security gateways has become commonplace in increasingly complex networks. On one side there is a need to maintain the logic of high level policies, which requires administrators to implement and update a large amount of filtering rules while keeping them conflict-free, that is, avoiding security inconsistencies. On the other side, traffic adaptive optimization of large rule lists is useful for general purpose computers used as filtering devices, without specific designed hardware, to face growing link speeds and to harden filtering devices against DoS and DDoS attacks. Our work joins the two issues in an innovative way and defines a traffic adaptive algorithm to find conflict-free optimized rule sets, by relying on information gathered with traffic logs. The proposed approach suits current technology architectures and exploits available features, like traffic log databases, to minimize the impact of ACO development on the packet filtering devices. We demonstrate the benefit entailed by the proposed algorithm through measurements on a test bed made up of real-life, commercial packet filtering devices.

  1. New Design Method of UWB Microstrip Filters Using Adaptive Genetic Algorithms with Defected Ground Structures

    Directory of Open Access Journals (Sweden)

    Amir Reza Dastkhosh

    2010-01-01

    Full Text Available The effects of adaptive genetic algorithms (AGAs and defected ground structures (DGSs on performance optimization of tapered microstrip filter are investigated. The proposed structure achieves an ultra wide stopband with high attenuation within a small surface area, as well as 45% smaller size, in comparison with conventional filters. The parameters of the filter are optimized using in-home AGA code. In the proposed AGA algorithm, the crossover and mutation probabilities are adaptively changed according to the value of individual fitness. Then by utilizing the proposed DGS, a compact S-band lowpass filter with ultra-wide spurious free window is obtained. The proposed filter achieves an insertion loss of 0.8 dB from DC up to 4 GHz and 21 dB rejection in the stopband from 4.3 up to 60 GHz. The fabricated and measured results exhibit good agreement with the simulated results. They demonstrate that combining AGA and DGS yields best possible response for this group of filters.

  2. IIR filtering based adaptive active vibration control methodology with online secondary path modeling using PZT actuators

    Science.gov (United States)

    Boz, Utku; Basdogan, Ipek

    2015-12-01

    Structural vibrations is a major cause for noise problems, discomfort and mechanical failures in aerospace, automotive and marine systems, which are mainly composed of plate-like structures. In order to reduce structural vibrations on these structures, active vibration control (AVC) is an effective approach. Adaptive filtering methodologies are preferred in AVC due to their ability to adjust themselves for varying dynamics of the structure during the operation. The filtered-X LMS (FXLMS) algorithm is a simple adaptive filtering algorithm widely implemented in active control applications. Proper implementation of FXLMS requires availability of a reference signal to mimic the disturbance and model of the dynamics between the control actuator and the error sensor, namely the secondary path. However, the controller output could interfere with the reference signal and the secondary path dynamics may change during the operation. This interference problem can be resolved by using an infinite impulse response (IIR) filter which considers feedback of the one or more previous control signals to the controller output and the changing secondary path dynamics can be updated using an online modeling technique. In this paper, IIR filtering based filtered-U LMS (FULMS) controller is combined with online secondary path modeling algorithm to suppress the vibrations of a plate-like structure. The results are validated through numerical and experimental studies. The results show that the FULMS with online secondary path modeling approach has more vibration rejection capabilities with higher convergence rate than the FXLMS counterpart.

  3. Ultrasound computed tomography by frequency-shift low-pass filtering and least mean square adaptive filtering

    Science.gov (United States)

    Wang, Shanshan; Song, Junjie; Peng, Yang; Zhou, Liang; Ding, Mingyue; Yuchi, Ming

    2017-03-01

    In recent years, many research studies have been carried out on ultrasound computed tomography (USCT) for improving the detection and management of breast cancer. This paper investigates a signal pre-processing method based on frequency-shift low-pass filtering (FSLF) and least mean square adaptive filtering (LMSAF) for USCT image quality enhancement (proposed in our previous work). FSLF is designed base on Zoom Fast Fourier Transform algorithm (ZFFT) for processing the ultrasound signals in the frequency domain, while LMSAPF is based on the least mean square (LMS) algorithm in the time domain. Through the combination of the two filters, the ultrasound image is expected to have less noises and artifacts, and higher resolution and contrast. The proposed method was verified with the radio-frequency (RF) data of the nylon threads and the breast phantom captured by the USCT system developed in the Medical Ultrasound Laboratory. Experimental results show that the reconstructed images of nylon threads by the proposed method had narrower main lobe width and lower side lobe level comparing to the delay-and-sum (DAS). The background noises and artifacts could also be efficiently restrained. The reconstructed image of breast phantom by the proposed method had a higher resolution and the contrast ratio (CR) could be enhanced for about 12dB to 18dB at different region of interest (ROI).

  4. Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

    Directory of Open Access Journals (Sweden)

    Bingbing Gao

    2018-02-01

    Full Text Available This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system integrated navigation.

  5. A biophysical model of adaptive noise filtering in the shark brain.

    Science.gov (United States)

    Bratby, Peter; Montgomery, John; Sneyd, James

    2014-02-01

    Sharks detect their prey using an extremely sensitive electrosensory system that is capable of distinguishing weak external stimuli from a relatively strong background noise generated by the animal itself. Experiments indicate that part of the shark's hindbrain, the dorsal octavolateralis nucleus (DON), is responsible for extracting the external stimulus using an adaptive filter mechanism to suppress signals correlated with the shark's breathing motion. The DON's principal neuron integrates input from afferents as well as many thousands of parallel fibres transmitting, inter alia, breathing-correlated motor command signals. There are a number of models in the literature, studying how this adaptive filtering mechanisms occurs, but most of them are based on a spike-train model approach.This paper presents a biophysically based computational simulation which demonstrates a mechanism for adaptive noise filtering in the DON. A spatial model of the neuron uses the Hodgkin-Huxley equations to simulate the propagation of action potentials along the dendrites. Synaptic inputs are modelled by applied currents at various positions along the dendrites, whose input conductances are varied according to a simple learning rule.Simulation results show that the model is able to demonstrate adaptive filtering in agreement with previous experimental and modelling studies. Furthermore, the spatial nature of the model does not greatly affect its learning properties, and in its present form is effectively equivalent to an isopotential model which does not incorporate a spatial element.

  6. An adaptive Multiplicative Extened Kalman Filter for Attitude Estimation of Marine Satellite Tracking Antenna

    DEFF Research Database (Denmark)

    Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar

    2016-01-01

    , an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...

  7. On frequency domain adaptive filters using the overlap-add method

    NARCIS (Netherlands)

    Sommen, P.C.W.; Jayasinghe, J.A.K.S.

    1988-01-01

    The authors introduce a frequency-domain adaptive filter (FDAF) configuration using the overlap-add method which has the same complexity and convergence behavior as the overlap-save configuration. It is shown that an FDAF using the overlap-add method can be realized with the same number of DFTs

  8. Adaptive computer-based spatial-filtering method for more accurate estimation of the surface velocity of debris flow.

    Science.gov (United States)

    Uddin, M S; Inaba, H; Itakura, Y; Yoshida, Y; Kasahara, M

    1999-11-10

    An adaptive computer-based spatial-filtering velocimeter to measure the surface velocity of a natural debris flow with high accuracy is described that can adjust the filter parameters, specifically, the slit width of the filter, based on the surface-pattern characteristics of the flow. A computer simulation confirms the effectiveness of this technique. The surface velocity of a natural debris flow at the Mt. Yakedake Volcano, Japan, was estimated by this adaptive method, and the results were compared with those obtained by two other methods: hardware-based spatial filtering and normal computer-based spatial filtering.

  9. Usefulness of noise adaptive non-linear gaussian filter in FDG-PET study.

    Science.gov (United States)

    Nagayoshi, Makoto; Murase, Kenya; Fujino, Kouichi; Uenishi, Yusuke; Kawamata, Minoru; Nakamura, Yukio; Kitamura, Keishi; Higuchi, Ichiro; Oku, Naohiko; Hatazawa, Jun

    2005-09-01

    In positron emission tomography (PET) studies, shortening transmission (TR) scan time can improve patient comfort and increase scanner throughput. However, PET images from short TR scans may be degraded due to the statistical noise included in the TR image. The purpose of this study was to apply non-linear Gaussian (NLG) and noise adaptive NLG (ANLG) filters to TR images, and to evaluate the extent of noise reduction by the ANLG filter in comparison with that by the NLG filter using phantom and clinical studies. In phantom studies, pool phantoms of various diameters and injected doses of 2-deoxy-2-[18F]fluoro-D-glucose (FDG) were used and the coefficients of variation (CVs) of the counts in the TR images processed with the NLG and ANLG filters were compared. In clinical studies, two normal volunteers and 13 patients with tumors were studied. In volunteer studies, the CV values in the liver were compared. In patient studies, the standardized uptake values (SUVs) of tumors in the emission images were obtained after processing the TR images using the NLG and ANLG filters. In phantom studies, the CV values in the TR images processed with the ANLG filter were smaller than those in the images processed with the NLG filter. When using the ANLG filter, their dependency on the phantom size, injected dose of FDG and TR scan time was smaller than when using the NLG filter. In volunteer studies, the CV values in the images processed with the ANLG filter were smaller than those in the images processed with the NLG filter, and were almost constant regardless of the TR scan time. In patient studies, there was an excellent correlation between the SUVs obtained from the images with a TR scan time of 7 min processed with the NLG filter (x) and those obtained from the images with a TR scan time of 4 min processed with the ANLG filter (y) (r = 0.995, y = 1.034x - 0.075). Our results suggest that the ANLG filter is effective and useful for noise reduction in TR images and shortening TR

  10. Common spatial pattern patches - an optimized filter ensemble for adaptive brain-computer interfaces.

    Science.gov (United States)

    Sannelli, Claudia; Vidaurre, Carmen; Muller, Klaus-Robert; Blankertz, Benjamin

    2010-01-01

    Laplacian filters are commonly used in Brain Computer Interfacing (BCI). When only data from few channels are available, or when, like at the beginning of an experiment, no previous data from the same user is available complex features cannot be used. In this case band power features calculated from Laplacian filtered channels represents an easy, robust and general feature to control a BCI, since its calculation does not involve any class information. For the same reason, the performance obtained with Laplacian features is poor in comparison to subject-specific optimized spatial filters, such as Common Spatial Patterns (CSP) analysis, which, on the other hand, can be used just in a later phase of the experiment, since they require a considerable amount of training data in order to enroll a stable and good performance. This drawback is particularly evident in case of poor performing BCI users, whose data is highly non-stationary and contains little class relevant information. Therefore, Laplacian filtering is preferred to CSP, e.g., in the initial period of co-adaptive calibration, a novel BCI paradigm designed to alleviate the problem of BCI illiteracy. In fact, in the co-adaptive calibration design the experiment starts with a subject-independent classifier and simple features are needed in order to obtain a fast adaptation of the classifier to the newly acquired user's data. Here, the use of an ensemble of local CSP patches (CSPP) is proposed, which can be considered as a compromise between Laplacians and CSP: CSPP needs less data and channels than CSP, while being superior to Laplacian filtering. This property is shown to be particularly useful for the co-adaptive calibration design and is demonstrated on off-line data from a previous co-adaptive BCI study.

  11. Automatic speech signal segmentation based on the innovation adaptive filter

    Directory of Open Access Journals (Sweden)

    Makowski Ryszard

    2014-06-01

    Full Text Available Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006, and it is a modified version of Brandt’s algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.

  12. Combined adaptive multiple subtraction based on optimized event tracing and extended wiener filtering

    Science.gov (United States)

    Tan, Jun; Song, Peng; Li, Jinshan; Wang, Lei; Zhong, Mengxuan; Zhang, Xiaobo

    2017-06-01

    The surface-related multiple elimination (SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.

  13. Motion artifact removal from photoplethysmographic signals by combining temporally constrained independent component analysis and adaptive filter.

    Science.gov (United States)

    Peng, Fulai; Zhang, Zhengbo; Gou, Xiaoming; Liu, Hongyun; Wang, Weidong

    2014-04-24

    The calculation of arterial oxygen saturation (SpO2) relies heavily on the amplitude information of the high-quality photoplethysmographic (PPG) signals, which could be contaminated by motion artifacts (MA) during monitoring. A new method combining temporally constrained independent component analysis (cICA) and adaptive filters is presented here to extract the clean PPG signals from the MA corrupted PPG signals with the amplitude information reserved. The underlying PPG signal could be extracted from the MA contaminated PPG signals automatically by using cICA algorithm. Then the amplitude information of the PPG signals could be recovered by using adaptive filters. Compared with conventional ICA algorithms, the proposed approach is permutation and scale ambiguity-free. Numerical examples with both synthetic datasets and real-world MA corrupted PPG signals demonstrate that the proposed method could remove the MA from MA contaminated PPG signals more effectively than the two existing FFT-LMS and moving average filter (MAF) methods. This paper presents a new method which combines the cICA algorithm and adaptive filter to extract the underlying PPG signals from the MA contaminated PPG signals with the amplitude information reserved. The new method could be used in the situations where one wants to extract the interested source automatically from the mixed observed signals with the amplitude information reserved. The results of study demonstrated the efficacy of this proposed method.

  14. Artifact reduction of compressed images and video combining adaptive fuzzy filtering and directional anisotropic diffusion

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Forchhammer, Søren; Korhonen, Jari

    2011-01-01

    and ringing artifacts, we have applied directional anisotropic diffusion. Besides that, the selection of the adaptive threshold parameter for the diffusion coefficient has also improved the performance of the algorithm. Experimental results on JPEG compressed images as well as MJPEG and H.264 compressed......Fuzzy filtering is one of the recently developed methods for reducing distortion in compressed images and video. In this paper, we combine the powerful anisotropic diffusion equations with fuzzy filtering in order to reduce the impact of artifacts. Based on the directional nature of the blocking...

  15. Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

    Science.gov (United States)

    Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

    2014-05-01

    In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

  16. Adaptive filtering and feed-forward control for suppression of vibration and jitter

    Science.gov (United States)

    Anderson, Eric H.; Blankinship, Ross L.; Fowler, Leslie P.; Glaese, Roger M.; Janzen, Paul C.

    2007-04-01

    This paper describes the use of adaptive filtering to control vibration and optical jitter. Adaptive filtering is a class of signal processing techniques developed over the last several decades and applied since to applications ranging from communications to image processing. Basic concepts in adaptive filtering and feedforward control are reviewed. A series of examples in vibration, motion and jitter control, including cryocoolers, ground-based active optics systems, flight motion simulators, wind turbines and airborne optical beam control systems, illustrates the effectiveness of the adaptive methods. These applications make use of information and signals that originate from system disturbances and minimize the correlations between disturbance information and error and performance measures. The examples incorporate a variety of disturbance types including periodic, multi-tonal, broadband stationary and non-stationary. Control effectiveness with slowly-varying narrowband disturbances originating from cryocoolers can be extraordinary, reaching 60 dB of reduction or rejection. In other cases, performance improvements are only 30-50%, but such reductions effectively complement feedback servo performance in many applications.

  17. Modified Log-LMS adaptive filter with low signal distortion for biomedical applications.

    Science.gov (United States)

    Jiao, Yuzhong; Cheung, Rex Y P; Mok, Mark P C

    2012-01-01

    Life signals from human body, e.g. heartbeat or electrocardiography (ECG), are usually weak and susceptible to external noise and interference. Adaptive filter is a good tool to reduce the influence of ambient noise/interference on the life signals. Least mean squares (LMS) algorithm, as one of most popular adaptive algorithms for active noise cancellation (ANC) by adaptive filtering, has the advantage of easy implementation. In order to further decrease the complexity of LMS algorithm based adaptive filter, a Log-LMS algorithm was proposed, which quantized signals by the function of log2. The algorithm can replace multipliers by simple shifting. However, both LMS algorithm and Log-LMS algorithm have the disadvantage of serious signal distortion in biomedical applications. In this paper, a modified Log-LMS algorithm is presented, which divides the convergence process into two different stages, and utilizes different quantization method in each stage. Two scenarios of biomedical applications are used for analysis, 1) using stethoscope in emergence medical helicopter and 2) measuring ECG under power line interference. The simulated results show that the modified algorithm can achieve fast convergence and low signal distortion in processing periodic life signals.

  18. Reference layer adaptive filtering (RLAF) for EEG artifact reduction in simultaneous EEG-fMRI

    Science.gov (United States)

    Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R.

    2017-04-01

    Objective. Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) combines advantages of both methods, namely high temporal resolution of EEG and high spatial resolution of fMRI. However, EEG quality is limited due to severe artifacts caused by fMRI scanners. Approach. To improve EEG data quality substantially, we introduce methods that use a reusable reference layer EEG cap prototype in combination with adaptive filtering. The first method, reference layer adaptive filtering (RLAF), uses adaptive filtering with reference layer artifact data to optimize artifact subtraction from EEG. In the second method, multi band reference layer adaptive filtering (MBRLAF), adaptive filtering is performed on bandwidth limited sub-bands of the EEG and the reference channels. Main results. The results suggests that RLAF outperforms the baseline method, average artifact subtraction, in all settings and also its direct predecessor, reference layer artifact subtraction (RLAS), in lower (<35 Hz) frequency ranges. MBRLAF is computationally more demanding than RLAF, but highly effective in all EEG frequency ranges. Effectivity is determined by visual inspection, as well as root-mean-square voltage reduction and power reduction of EEG provided that physiological EEG components such as occipital EEG alpha power and visual evoked potentials (VEP) are preserved. We demonstrate that both, RLAF and MBRLAF, improve VEP quality. For that, we calculate the mean-squared-distance of single trial VEP to the mean VEP and estimate single trial VEP classification accuracies. We found that the average mean-squared-distance is lowest and the average classification accuracy is highest after MBLAF. RLAF was second best. Significance. In conclusion, the results suggests that RLAF and MBRLAF are potentially very effective in improving EEG quality of simultaneous EEG-fMRI. Highlights We present a new and reusable reference layer cap prototype for simultaneous EEG-fMRI We

  19. Adaptive Laplacian filtering for sensorimotor rhythm-based brain-computer interfaces

    Science.gov (United States)

    Lu, Jun; McFarland, Dennis J.; Wolpaw, Jonathan R.

    2013-02-01

    Objective. Sensorimotor rhythms (SMRs) are 8-30 Hz oscillations in the electroencephalogram (EEG) recorded from the scalp over sensorimotor cortex that change with movement and/or movement imagery. Many brain-computer interface (BCI) studies have shown that people can learn to control SMR amplitudes and can use that control to move cursors and other objects in one, two or three dimensions. At the same time, if SMR-based BCIs are to be useful for people with neuromuscular disabilities, their accuracy and reliability must be improved substantially. These BCIs often use spatial filtering methods such as common average reference (CAR), Laplacian (LAP) filter or common spatial pattern (CSP) filter to enhance the signal-to-noise ratio of EEG. Here, we test the hypothesis that a new filter design, called an ‘adaptive Laplacian (ALAP) filter’, can provide better performance for SMR-based BCIs. Approach. An ALAP filter employs a Gaussian kernel to construct a smooth spatial gradient of channel weights and then simultaneously seeks the optimal kernel radius of this spatial filter and the regularization parameter of linear ridge regression. This optimization is based on minimizing the leave-one-out cross-validation error through a gradient descent method and is computationally feasible. Main results. Using a variety of kinds of BCI data from a total of 22 individuals, we compare the performances of ALAP filter to CAR, small LAP, large LAP and CSP filters. With a large number of channels and limited data, ALAP performs significantly better than CSP, CAR, small LAP and large LAP both in classification accuracy and in mean-squared error. Using fewer channels restricted to motor areas, ALAP is still superior to CAR, small LAP and large LAP, but equally matched to CSP. Significance. Thus, ALAP may help to improve the accuracy and robustness of SMR-based BCIs.

  20. A pilot study on slit lamp-adapted optical coherence tomography imaging of trabeculectomy filtering blebs.

    Science.gov (United States)

    Theelen, Thomas; Wesseling, Pieter; Keunen, Jan E E; Klevering, B Jeroen

    2007-06-01

    Our study aims to identify anatomical characteristics of glaucoma filtering blebs by means of slit lamp-adapted optical coherence tomography (SL-OCT) and to identify new parameters for the functional prognosis of the filter in the early post-operative period. Patients with primary open-angle glaucoma, aged 18 years and older, scheduled for primary trabeculectomy at the Department of Ophthalmology, Radboud University Nijmegen Medical Centre, were considered for our study. All patients underwent standardized trabeculectomy with intra-operative application of mitomycin C. The filtering blebs were evaluated clinically and with SL-OCT on day 1 and 1, 2, 4 and 12 weeks following surgery. The resulting data were analysed and weighed against surgical success. To better understand the SL-OCT data a small comparative histologic study was performed. The study included 20 eyes of 20 patients. After completion of our study, 15 eyes of 15 patients (mean age+/-SD 67 +/- 16 years) were eligible for data analysis and 5 eyes missed at least one follow-up visit. Filtering surgery was considered successful (intraocular pressure visualisation of the sclera below the filtering zone was better defined in failures compared with successful filtering blebs ("shading" phenomenon). We observed no differences in the volume and clinical aspect of the blebs in the successful group compared with the unsuccessful group. Successful filtering blebs show characteristic optical properties on SL-OCT. These phenomena suggest a diffusely enhanced fluid content and the presence of intra-bleb drainage channels in functional filtering blebs.

  1. An Adaptive Filtering Algorithm Based on Genetic Algorithm-Backpropagation Network

    Directory of Open Access Journals (Sweden)

    Kai Hu

    2013-01-01

    Full Text Available A new image filtering algorithm is proposed. GA-BPN algorithm uses genetic algorithm (GA to decide weights in a back propagation neural network (BPN. It has better global optimal characteristics than traditional optimal algorithm. In this paper, we used GA-BPN to do image noise filter researching work. Firstly, this paper uses training samples to train GA-BPN as the noise detector. Then, we utilize the well-trained GA-BPN to recognize noise pixels in target image. And at last, an adaptive weighted average algorithm is used to recover noise pixels recognized by GA-BPN. Experiment data shows that this algorithm has better performance than other filters.

  2. An adaptive nonlocal filtering for low-dose CT in both image and projection domains

    Directory of Open Access Journals (Sweden)

    Yingmei Wang

    2015-04-01

    Full Text Available An important problem in low-dose CT is the image quality degradation caused by photon starvation. There are a lot of algorithms in sinogram domain or image domain to solve this problem. In view of strong self-similarity contained in the special sinusoid-like strip data in the sinogram space, we propose a novel non-local filtering, whose average weights are related to both the image FBP (filtered backprojection reconstructed from restored sinogram data and the image directly FBP reconstructed from noisy sinogram data. In the process of sinogram restoration, we apply a non-local method with smoothness parameters adjusted adaptively to the variance of noisy sinogram data, which makes the method much effective for noise reduction in sinogram domain. Simulation experiments show that our proposed method by filtering in both image and projection domains has a better performance in noise reduction and details preservation in reconstructed images.

  3. Train velocity estimation method based on an adaptive filter with fuzzy logic

    Science.gov (United States)

    Pichlík, Petr; Zděnek, Jiří

    2017-03-01

    The train velocity is difficult to determine when the velocity is measured only on the driven or braked locomotive wheelsets. In this case, the calculated train velocity is different from the actual train velocity due to slip velocity or skid velocity respectively. The train velocity is needed for a locomotive controller proper work. For this purpose, an adaptive filter that is tuned by a fuzzy logic is designed and described in the paper. The filter calculates the train longitudinal velocity based on locomotive wheelset velocity. The fuzzy logic is used for the tuning of the filter according to actual wheelset acceleration and wheelset jerk. The simulation results are based on real measured data on a freight train. The results show that the calculated velocity corresponds to the actual train velocity.

  4. A self-adaptive anti-vibration pipeline-filtering algorithm

    Science.gov (United States)

    Wu, Houde; Wang, Bin; Zhao, Ming; Xu, Wenhai

    2015-03-01

    The mobile pipeline-filtering algorithm is a real-time algorithm that performs well in detecting small dim targets, but it is particularly sensitive to interframe vibration of sequence images. When searching for small dim targets at sea based on an infrared imaging system, irregular and random vibration of the airborne imaging platform causes huge interference problems for the mobile pipeline-filtering. This paper puts forward a pipeline-filtering algorithm that has a good performance on self-adaptive anti-vibration. In the block matching method using the normalized cross-correlations coefficient (NCC), the interframe vibration of sequence images is acquired in real time and used to correct coordinates of the single-frame detection results, and then the corrected detection results are used to complete the mobile pipelinefiltering. Experimental results show that the algorithm can overcome the problem of interframe vibration of sequence images, thus realizing accurate detection of small dim maritime targets.

  5. Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms

    National Research Council Canada - National Science Library

    Radek Martinek; Radana Kahankova; Homer Nazeran; Jaromir Konecny; Janusz Jezewski; Petr Janku; Petr Bilik; Jan Zidek; Jan Nedoma; Marcel Fajkus

    2017-01-01

    ...) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adaptive filters...

  6. Ultrasound Small Vessel Imaging With Block-Wise Adaptive Local Clutter Filtering.

    Science.gov (United States)

    Song, Pengfei; Manduca, Armando; Trzasko, Joshua D; Chen, Shigao

    2017-01-01

    Robust clutter filtering is essential for ultrasound small vessel imaging. Eigen-based clutter filtering techniques have recently shown great improvement in clutter rejection over conventional clutter filters in small animals. However, for in vivo human imaging, eigen-based clutter filtering can be challenging due to the complex spatially-varying tissue and noise characteristics. To address this challenge, we present a novel block-wise adaptive singular value decomposition (SVD) based clutter filtering technique. The proposed method divides the global plane wave data into overlapped local spatial segments, within which tissue signals are assumed to be locally coherent and noise locally stationary. This, in turn, enables effective separation of tissue, blood and noise via SVD. For each block, the proposed method adaptively determines the singular value cutoff thresholds based on local data statistics. Processing results from each block are redundantly combined to improve both the signal-to-noise-ratio (SNR) and the contrast-to-noise-ratio (CNR) of the small vessel perfusion image. Experimental results show that the proposed method achieved more than two-fold increase in SNR and more than three-fold increase in CNR in dB scale over the conventional global SVD filtering technique for an in vivo human native kidney study. The proposed method also showed substantial improvement in suppression of the depth-dependent background noise and better rejection of near field tissue clutter. The effects of different processing block size and block overlap percentage were systematically investigated as well as the tradeoff between imaging quality and computational cost.

  7. Command Filtered Adaptive Fuzzy Neural Network Backstepping Control for Marine Power System

    Directory of Open Access Journals (Sweden)

    Xin Zhang

    2014-01-01

    Full Text Available In order to retrain chaotic oscillation of marine power system which is excited by periodic electromagnetism perturbation, a novel command-filtered adaptive fuzzy neural network backstepping control method is designed. First, the mathematical model of marine power system is established based on the two parallel nonlinear model. Then, main results of command-filtered adaptive fuzzy neural network backstepping control law are given. And the Lyapunov stability theory is applied to prove that the system can remain closed-loop asymptotically stable with this controller. Finally, simulation results indicate that the designed controller can suppress chaotic oscillation with fast convergence speed that makes the system return to the equilibrium point quickly; meanwhile, the parameter which induces chaotic oscillation can also be discriminated.

  8. Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping

    Directory of Open Access Journals (Sweden)

    Shi-Qiang Yang

    2008-06-01

    Full Text Available This paper presents a novel video enhancement system based on an adaptive spatio-temporal connective (ASTC noise filter and an adaptive piecewise mapping function (APMF. For ill-exposed videos or those with much noise, we first introduce a novel local image statistic to identify impulse noise pixels, and then incorporate it into the classical bilateral filter to form ASTC, aiming to reduce the mixture of the most two common types of noises—Gaussian and impulse noises in spatial and temporal directions. After noise removal, we enhance the video contrast with APMF based on the statistical information of frame segmentation results. The experiment results demonstrate that, for diverse low-quality videos corrupted by mixed noise, underexposure, overexposure, or any mixture of the above, the proposed system can automatically produce satisfactory results.

  9. Video Enhancement Using Adaptive Spatio-Temporal Connective Filter and Piecewise Mapping

    Directory of Open Access Journals (Sweden)

    Wang Chao

    2008-01-01

    Full Text Available This paper presents a novel video enhancement system based on an adaptive spatio-temporal connective (ASTC noise filter and an adaptive piecewise mapping function (APMF. For ill-exposed videos or those with much noise, we first introduce a novel local image statistic to identify impulse noise pixels, and then incorporate it into the classical bilateral filter to form ASTC, aiming to reduce the mixture of the most two common types of noises—Gaussian and impulse noises in spatial and temporal directions. After noise removal, we enhance the video contrast with APMF based on the statistical information of frame segmentation results. The experiment results demonstrate that, for diverse low-quality videos corrupted by mixed noise, underexposure, overexposure, or any mixture of the above, the proposed system can automatically produce satisfactory results.

  10. An Adaptive Unscented Particle Filter Algorithm through Relative Entropy for Mobile Robot Self-Localization

    Directory of Open Access Journals (Sweden)

    Wentao Yu

    2013-01-01

    high. In order to reduce the computation cost of UPF and meanwhile maintain the accuracy, we propose an adaptive unscented particle filter (AUPF algorithm through relative entropy. AUPF can adaptively adjust the number of particles during filtering to reduce the necessary computation and hence improve the real-time capability of UPF. In AUPF, the relative entropy is used to measure the distance between the empirical distribution and the true posterior distribution. The least number of particles for the next step is then decided according to the relative entropy. In order to offset the difference between the proposal distribution, and the true distribution the least number is adjusted thereafter. The ideal performance of AUPF in real robot self-localization is demonstrated.

  11. Robust respiration rate estimation using adaptive Kalman filtering with textile ECG sensor and accelerometer.

    Science.gov (United States)

    Lepine, Nicholas N; Tajima, Takuro; Ogasawara, Takayuki; Kasahara, Ryoichi; Koizumi, Hiroshi

    2016-08-01

    An adaptive Kalman filter-based fusion algorithm capable of estimating respiration rate for unobtrusive respiratory monitoring is proposed. Using both signal characteristics and a priori information, the Kalman filter is adaptively optimized to improve accuracy. Furthermore, the system is able to combine the respiration-related signals extracted from a textile ECG sensor and an accelerometer to create a single robust measurement. We measured derived respiratory rates and, when compared to a reference, found root-mean-square error of 2.11 breaths-per-minute (BrPM) while lying down, 2.30 BrPM while sitting, 5.97 BrPM while walking, and 5.98 BrPM while running. These results demonstrate that the proposed system is applicable to unobtrusive monitoring for various applications.

  12. Sealing Clay Text Segmentation Based on Radon-Like Features and Adaptive Enhancement Filters

    Directory of Open Access Journals (Sweden)

    Xia Zheng

    2015-01-01

    Full Text Available Text extraction is a key issue in sealing clay research. The traditional method based on rubbings increases the risk of sealing clay damage and is unfavorable to sealing clay protection. Therefore, using digital image of sealing clay, a new method for text segmentation based on Radon-like features and adaptive enhancement filters is proposed in this paper. First, adaptive enhancement LM filter bank is used to get the maximum energy image; second, the edge image of the maximum energy image is calculated; finally, Radon-like feature images are generated by combining maximum energy image and its edge image. The average image of Radon-like feature images is segmented by the image thresholding method. Compared with 2D Otsu, GA, and FastFCM, the experiment result shows that this method can perform better in terms of accuracy and completeness of the text.

  13. Fuzzy adaptive interacting multiple model nonlinear filter for integrated navigation sensor fusion.

    Science.gov (United States)

    Tseng, Chien-Hao; Chang, Chih-Wen; Jwo, Dah-Jing

    2011-01-01

    In this paper, the application of the fuzzy interacting multiple model unscented Kalman filter (FUZZY-IMMUKF) approach to integrated navigation processing for the maneuvering vehicle is presented. The unscented Kalman filter (UKF) employs a set of sigma points through deterministic sampling, such that a linearization process is not necessary, and therefore the errors caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. The nonlinear filters naturally suffer, to some extent, the same problem as the EKF for which the uncertainty of the process noise and measurement noise will degrade the performance. As a structural adaptation (model switching) mechanism, the interacting multiple model (IMM), which describes a set of switching models, can be utilized for determining the adequate value of process noise covariance. The fuzzy logic adaptive system (FLAS) is employed to determine the lower and upper bounds of the system noise through the fuzzy inference system (FIS). The resulting sensor fusion strategy can efficiently deal with the nonlinear problem for the vehicle navigation. The proposed FUZZY-IMMUKF algorithm shows remarkable improvement in the navigation estimation accuracy as compared to the relatively conventional approaches such as the UKF and IMMUKF.

  14. Adaptive filter design based on the LMS algorithm for delay elimination in TCR/FC compensators.

    Science.gov (United States)

    Hooshmand, Rahmat Allah; Torabian Esfahani, Mahdi

    2011-04-01

    Thyristor controlled reactor with fixed capacitor (TCR/FC) compensators have the capability of compensating reactive power and improving power quality phenomena. Delay in the response of such compensators degrades their performance. In this paper, a new method based on adaptive filters (AF) is proposed in order to eliminate delay and increase the response of the TCR compensator. The algorithm designed for the adaptive filters is performed based on the least mean square (LMS) algorithm. In this design, instead of fixed capacitors, band-pass LC filters are used. To evaluate the filter, a TCR/FC compensator was used for nonlinear and time varying loads of electric arc furnaces (EAFs). These loads caused occurrence of power quality phenomena in the supplying system, such as voltage fluctuation and flicker, odd and even harmonics and unbalancing in voltage and current. The above design was implemented in a realistic system model of a steel complex. The simulation results show that applying the proposed control in the TCR/FC compensator efficiently eliminated delay in the response and improved the performance of the compensator in the power system. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

  15. Assessment of auditory processing disorder in children using an adaptive filtered speech test.

    Science.gov (United States)

    Rickard, Natalie A; Heidtke, Uta J; O'Beirne, Greg A

    2013-10-01

    One type of test commonly used to assess auditory processing disorder (APD) is the 'filtered words test' (FWT), in which a monaural, low-redundancy speech sample is distorted by using filtering to modify its frequency content. One limitation of the various existing FWTs is that they are performed using a constant level of low-pass filtering, making them prone to ceiling and floor effects that compromise their efficiency and accuracy. A recently developed computer-based test, the University of Canterbury Adaptive Speech Test- Filtered Words (UCAST-FW), uses an adaptive procedure intended to improve the efficiency and sensitivity of the test over its constant-level counterparts. The UCAST-FW was administered to school-aged children to investigate the ability of the test to distinguish between children with and without APD. Fifteen children aged 7-13 diagnosed with APD, and an aged-matched control group of 10 children with no history of listening difficulties. Data obtained demonstrates a significant difference between the UCAST-FW results obtained by children with APD and those with normal auditory processing. These findings provide evidence that the UCAST-FW may discriminate between children with and without APD with greater sensitivity than its constant-level counterparts.

  16. Removal of Cardiopulmonary Resuscitation Artifacts with an Enhanced Adaptive Filtering Method: An Experimental Trial

    Directory of Open Access Journals (Sweden)

    Yushun Gong

    2014-01-01

    Full Text Available Current automated external defibrillators mandate interruptions of chest compression to avoid the effect of artifacts produced by CPR for reliable rhythm analyses. But even seconds of interruption of chest compression during CPR adversely affects the rate of restoration of spontaneous circulation and survival. Numerous digital signal processing techniques have been developed to remove the artifacts or interpret the corrupted ECG with promising result, but the performance is still inadequate, especially for nonshockable rhythms. In the present study, we suppressed the CPR artifacts with an enhanced adaptive filtering method. The performance of the method was evaluated by comparing the sensitivity and specificity for shockable rhythm detection before and after filtering the CPR corrupted ECG signals. The dataset comprised 283 segments of shockable and 280 segments of nonshockable ECG signals during CPR recorded from 22 adult pigs that experienced prolonged cardiac arrest. For the unfiltered signals, the sensitivity and specificity were 99.3% and 46.8%, respectively. After filtering, a sensitivity of 93.3% and a specificity of 96.0% were achieved. This animal trial demonstrated that the enhanced adaptive filtering method could significantly improve the detection of nonshockable rhythms without compromising the ability to detect a shockable rhythm during uninterrupted CPR.

  17. State of Charge Estimation of Lithium-Ion Batteries Using an Adaptive Cubature Kalman Filter

    Directory of Open Access Journals (Sweden)

    Bizhong Xia

    2015-06-01

    Full Text Available Accurate state of charge (SOC estimation is of great significance for a lithium-ion battery to ensure its safe operation and to prevent it from over-charging or over-discharging. However, it is difficult to get an accurate value of SOC since it is an inner sate of a battery cell, which cannot be directly measured. This paper presents an Adaptive Cubature Kalman filter (ACKF-based SOC estimation algorithm for lithium-ion batteries in electric vehicles. Firstly, the lithium-ion battery is modeled using the second-order resistor-capacitor (RC equivalent circuit and parameters of the battery model are determined by the forgetting factor least-squares method. Then, the Adaptive Cubature Kalman filter for battery SOC estimation is introduced and the estimated process is presented. Finally, two typical driving cycles, including the Dynamic Stress Test (DST and New European Driving Cycle (NEDC are applied to evaluate the performance of the proposed method by comparing with the traditional extended Kalman filter (EKF and cubature Kalman filter (CKF algorithms. Experimental results show that the ACKF algorithm has better performance in terms of SOC estimation accuracy, convergence to different initial SOC errors and robustness against voltage measurement noise as compared with the traditional EKF and CKF algorithms.

  18. Fuzzy Adaptive Interacting Multiple Model Nonlinear Filter for Integrated Navigation Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Dah-Jing Jwo

    2011-02-01

    Full Text Available In this paper, the application of the fuzzy interacting multiple model unscented Kalman filter (FUZZY-IMMUKF approach to integrated navigation processing for the maneuvering vehicle is presented. The unscented Kalman filter (UKF employs a set of sigma points through deterministic sampling, such that a linearization process is not necessary, and therefore the errors caused by linearization as in the traditional extended Kalman filter (EKF can be avoided. The nonlinear filters naturally suffer, to some extent, the same problem as the EKF for which the uncertainty of the process noise and measurement noise will degrade the performance. As a structural adaptation (model switching mechanism, the interacting multiple model (IMM, which describes a set of switching models, can be utilized for determining the adequate value of process noise covariance. The fuzzy logic adaptive system (FLAS is employed to determine the lower and upper bounds of the system noise through the fuzzy inference system (FIS. The resulting sensor fusion strategy can efficiently deal with the nonlinear problem for the vehicle navigation. The proposed FUZZY-IMMUKF algorithm shows remarkable improvement in the navigation estimation accuracy as compared to the relatively conventional approaches such as the UKF and IMMUKF.

  19. Adaptive RBF Neural Network Control for Three-Phase Active Power Filter

    Directory of Open Access Journals (Sweden)

    Juntao Fei

    2013-05-01

    Full Text Available Abstract An adaptive radial basis function (RBF neural network control system for three-phase active power filter (APF is proposed to eliminate harmonics. Compensation current is generated to track command current so as to eliminate the harmonic current of non-linear load and improve the quality of the power system. The asymptotical stability of the APF system can be guaranteed with the proposed adaptive neural network strategy. The parameters of the neural network can be adaptively updated to achieve the desired tracking task. The simulation results demonstrate good performance, for example showing small current tracking error, reduced total harmonic distortion (THD, improved accuracy and strong robustness in the presence of parameters variation and nonlinear load. It is shown that the adaptive RBF neural network control system for three-phase APF gives better control than hysteresis control.

  20. Application of adaptive noise cancellation to Coast Guard voice communications

    Science.gov (United States)

    Peterson, B. B.; Dykstra, K. U.; Sakahara, M. D.

    1985-03-01

    A variety of approaches to the digital filtering of voice signals corrupted by background engine noise are presented. These approaches include the standard Least Mean Square adaptive noise cancellation algorithm, an optimum fixed weight filter, a special type of notch filter and frequency domain adaptive noise cancellation. The filters have been implemented both off-line using FORTRAN programs on an LSI-11/2 microcomputer, and in real time using thee Texas Instruments TMS 320 microprocessor and in PDP-11 assembly language using an LSI-11/2. Frequency domain adaptive filtering was seen to be superior to the LMS time domain algorithm because its much greater computational efficiency allowed the analysis of much longer filters. A digital filter that exploits the engine noise by having a notch at each harmonic was seen to be more effective than any of the adaptive filters. The digital filter equations are derived, starting with a particular periodic reference input. This adaptive filter is shown to be, in reality, an infinite impulse response, time invariant filter.

  1. Sensorless control of salient PMSM with adaptive integrator and resistance online identification using strong tracking filter

    Science.gov (United States)

    Ma, Shaokang; Wu, Peijun; Ji, Jinhu; Li, Xuchun

    2016-02-01

    This article presents a sensorless control approach of salient PMSM with an online parameter identifier. Adaptive Integrator is proposed and utilised for the estimation of active flux and rotor position. As a result, integrator overflow caused by DC offset is avoided. Meanwhile, an online stator resistance identification algorithm using strong tracking filter is employed, and the identified stator resistance is fed back to the estimating algorithm. Thus, the estimating algorithm can calculate the rotor position correctly. Simulations and experimental results validate the feasibility of both adaptive integrator and the parameter identification method.

  2. Cultural evolutionary design of adaptive wavelet filters based on lifting scheme for micro-instruments

    CERN Document Server

    Manna, C; Romanucci, Carmine; Zanesco, Antonio; Arpaia, Pasquale

    2010-01-01

    An evolutionary procedure based on cultural algorithms for the optimal design of adaptive wavelet filters based on lifting scheme is proposed. Numerical results of characterization, based on statistical experiment design, as well as validation, based on the comparison with a genetic optimization algorithm, are presented. Experimental results of the validation on two case studies for reducing uncertainty arising from noise in on-field corrosion rate measurements are highlighted. (C) 2010 Elsevier Ltd. All rights reserved.

  3. On-chip implementation of Extended Kalman Filter for adaptive battery states monitoring

    OpenAIRE

    Nejad, S.; Gladwin, D.T.; Stone, D. A.

    2016-01-01

    This paper reports the development and implementation of an adaptive lithium-ion battery monitoring system. The monitoring algorithm is based on the nonlinear Dual Extended Kalman Filter (DEKF), which allows for simultaneous states and parameters estimation. The hardware platform consists of an ARM cortex-M0 processor with six embedded analogue-to-digital converters (ADCs) for data acquisition. Two definitions for online state-of-health (SOH) characterisation are presented; one energy-based a...

  4. Biohybrid control of general linear systems using the adaptive filter model of cerebellum

    Directory of Open Access Journals (Sweden)

    Emma D. Wilson

    2015-07-01

    Full Text Available The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems such as the vestibulo-ocular reflex (VOR and to sensory processing problems such as the adaptive cancellation of reafferent noise. It has also been successfully applied to problems in robotics such as adaptive camera stabilisation and sensor noise cancellation. In previous applications to inverse control problems the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity control of this plant results in unstable learning and control. To be more generally useful in engineering problems it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC scheme, which stabilises the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks.

  5. The Study of Phase-Based Optical Flow Technique Using an Adaptive Bilateral Filter

    Science.gov (United States)

    Lee, Ju Hwan; Park, Sung Yun; Kim, Sung Jae; Kim, Sung Min

    The purpose of this study is to propose an advanced phase-based optical flow method with improved tracking accuracy for motion flow. The proposed method is mainly based on adaptive bilateral filtering (ABF) and Gabor based spatial filtering. ABF aims to preserve the maximum boundary information of the original image, while the spatial filtering aims to accurately compute the local variations. Our method tracks the optical flow in three stages. Firstly, the input images are filtered by using ABF and a spatial filter to remove noises and to preserve the maximum contour information. The component velocities are then computed based on the phase gradient of each pixel. Secondly, irregular pixels are eliminated, if the phase differences are not linear over the image frames. Lastly, the entire velocity is derived by integrating the component velocities of each pixel. In order to evaluate the tracking accuracy of the proposed method, we have examined its performance for synthetic and realistic images for which the ground truth data were known. As a result, it was observed that the proposed technique offers higher accuracy than the existing optical flow methods.

  6. Neural network-aided variational Bayesian adaptive cubature Kalman filtering for nonlinear state estimation

    Science.gov (United States)

    Miao, Zhiyong; Shi, Hongyang; Zhang, Yi; Xu, Fan

    2017-10-01

    In this paper, a new variational Bayesian adaptive cubature Kalman filter (VBACKF) is proposed for nonlinear state estimation. Although the conventional VBACKF performs better than cubature Kalman filtering (CKF) in solving nonlinear systems with time-varying measurement noise, its performance may degrade due to the uncertainty of the system model. To overcome this drawback, a multilayer feed-forward neural network (MFNN) is used to aid the conventional VBACKF, generalizing it to attain higher estimation accuracy and robustness. In the proposed neural-network-aided variational Bayesian adaptive cubature Kalman filter (NN-VBACKF), the MFNN is used to turn the state estimation of the VBACKF adaptively, and it is used for both state estimation and in the online training paradigm simultaneously. To evaluate the performance of the proposed method, it is compared with CKF and VBACKF via target tracking problems. The simulation results demonstrate that the estimation accuracy and robustness of the proposed method are better than those of the CKF and VBACKF.

  7. An Adaptive Least-Error Squares Filter-Based Phase-Locked Loop for Synchronization and Signal Decomposition Purposes

    DEFF Research Database (Denmark)

    Golestan, Saeed; Ebrahimzadeh, Esmaeil; Guerrero, Josep M.

    2017-01-01

    most of the control algorithms, designing PLLs involves a tradeoff between the accuracy and dynamic response, and improving this tradeoff is what recent research efforts have focused on. These efforts are often based on designing advanced filters and using them as a preprocessing tool before the PLL...... input. A filtering technique that has received a little attention for this purpose is the least-error squares (LES)-based filter. In this paper, an adaptive LES filter-based PLL, briefly called the LES-PLL, for the synchronization and signal decomposition purposes is presented. The proposed LES filter...

  8. A Novel Adaptive H∞ Filtering Method with Delay Compensation for the Transfer Alignment of Strapdown Inertial Navigation Systems.

    Science.gov (United States)

    Lyu, Weiwei; Cheng, Xianghong

    2017-11-28

    Transfer alignment is always a key technology in a strapdown inertial navigation system (SINS) because of its rapidity and accuracy. In this paper a transfer alignment model is established, which contains the SINS error model and the measurement model. The time delay in the process of transfer alignment is analyzed, and an H∞ filtering method with delay compensation is presented. Then the H∞ filtering theory and the robust mechanism of H∞ filter are deduced and analyzed in detail. In order to improve the transfer alignment accuracy in SINS with time delay, an adaptive H∞ filtering method with delay compensation is proposed. Since the robustness factor plays an important role in the filtering process and has effect on the filtering accuracy, the adaptive H∞ filter with delay compensation can adjust the value of robustness factor adaptively according to the dynamic external environment. The vehicle transfer alignment experiment indicates that by using the adaptive H∞ filtering method with delay compensation, the transfer alignment accuracy and the pure inertial navigation accuracy can be dramatically improved, which demonstrates the superiority of the proposed filtering method.

  9. Designing Fuzzy Adaptive Nonlinear Filter for Land Vehicle Ultra-Tightly Coupled Integrated Navigation Sensor Fusion

    Directory of Open Access Journals (Sweden)

    Chien-Hao TSENG

    2011-05-01

    Full Text Available Traditional GPS/INS integration designs adopt a loosely or tightly coupled architecture, for which the GPS receiver may lose lock due to the interference/jamming scenarios and high dynamic environments. This paper presents a sensor fusion method based on the combination of unscented Kalman filter (UKF and Fuzzy Logic Adaptive System (FLAS for the ultra-tightly coupled GPS/INS integrated navigation. An ultra-tight GPS/INS architecture involves the integration of I and Q (in-phase and quadrature components from the correlator of a GPS receiver with the INS data. The UKF employs a set of sigma points through deterministic sampling, such that the linearization process is not necessary, and therefore the error caused by linearization as in the traditional extended Kalman filter (EKF can be avoided. The nonlinear filters naturally suffer, to some extent, the same problem as the EKF for which the uncertainty of the process noise and measurement noise will degrade the performance. The fuzzy logic adaptive system (FLAS has been one of the approaches to prevent divergence problem of the filter when precise knowledge on the system models are not available. Though the use of fuzzy inference system (FIS, the FLAS has been incorporated into the UKF as a mechanism for timely detecting the dynamical changes and implementing the on-line tuning of the process noise covariance by monitoring the innovation information, and therefore improves the estimation performance. The results show that the proposed fuzzy adaptive UKF algorithm can effectively improve the navigation estimation accuracy as compared to the relatively conventional approaches such as the UKF and EKF.

  10. Implementation of Adaptive Unsharp Masking as a Pre-filtering Method for Watermark Detection and Extraction

    Directory of Open Access Journals (Sweden)

    Onur Jane

    2016-01-01

    Full Text Available Digital watermarking has been one of the focal points of research interests in order to provide multimedia security in the last decade. Watermark data, belonging to the user, are embedded on an original work such as text, audio, image, and video and thus, product ownership can be proved. Various robust watermarking algorithms have been developed in order to extract/detect the watermark against such attacks. Although watermarking algorithms in the transform domain differ from others by different combinations of transform techniques, it is difficult to decide on an algorithm for a specific application. Therefore, instead of developing a new watermarking algorithm with different combinations of transform techniques, we propose a novel and effective watermark extraction and detection method by pre-filtering, namely Adaptive Unsharp Masking (AUM. In spite of the fact that Unsharp Masking (UM based pre-filtering is used for watermark extraction/detection in the literature by causing the details of the watermarked image become more manifest, effectiveness of UM may decrease in some cases of attacks. In this study, AUM has been proposed for pre-filtering as a solution to the disadvantages of UM. Experimental results show that AUM performs better up to 11\\% in objective quality metrics than that of the results when pre-filtering is not used. Moreover; AUM proposed for pre-filtering in the transform domain image watermarking is as effective as that of used in image enhancement and can be applied in an algorithm-independent way for pre-filtering in transform domain image watermarking.

  11. Sampled-Data Kalman Filtering and Multiple Model Adaptive Estimation for Infinite-Dimensional Continuous-Time Systems

    National Research Council Canada - National Science Library

    Sallberg, Scott A

    2007-01-01

    Kalman filtering and multiple model adaptive estimation (MMAE) methods have been applied by researchers in several engineering disciplines to a multitude of problems featuring a linear (or mildly nonlinear...

  12. Rotational Kinematics Model Based Adaptive Particle Filter for Robust Human Tracking in Thermal Omnidirectional Vision

    Directory of Open Access Journals (Sweden)

    Yazhe Tang

    2015-01-01

    Full Text Available This paper presents a novel surveillance system named thermal omnidirectional vision (TOV system which can work in total darkness with a wild field of view. Different to the conventional thermal vision sensor, the proposed vision system exhibits serious nonlinear distortion due to the effect of the quadratic mirror. To effectively model the inherent distortion of omnidirectional vision, an equivalent sphere projection is employed to adaptively calculate parameterized distorted neighborhood of an object in the image plane. With the equivalent projection based adaptive neighborhood calculation, a distortion-invariant gradient coding feature is proposed for thermal catadioptric vision. For robust tracking purpose, a rotational kinematic modeled adaptive particle filter is proposed based on the characteristic of omnidirectional vision, which can handle multiple movements effectively, including the rapid motions. Finally, the experiments are given to verify the performance of the proposed algorithm for human tracking in TOV system.

  13. Adaptive filtering of microarray gene expression data based on Gaussian mixture decomposition

    Science.gov (United States)

    2013-01-01

    Background DNA microarrays are used for discovery of genes expressed differentially between various biological conditions. In microarray experiments the number of analyzed samples is often much lower than the number of genes (probe sets) which leads to many false discoveries. Multiple testing correction methods control the number of false discoveries but decrease the sensitivity of discovering differentially expressed genes. Concerning this problem, filtering methods for improving the power of detection of differentially expressed genes were proposed in earlier papers. These techniques are two-step procedures, where in the first step some pool of non-informative genes is removed and in the second step only the pool of the retained genes is used for searching for differentially expressed genes. Results A very important parameter to choose is the proportion between the sizes of the pools of removed and retained genes. A new method, which we propose, allow to determine close to optimal threshold values for sample means and sample variances for gene filtering. The method is adaptive and based on the decomposition of the histogram of gene expression means or variances into mixture of Gaussian components. Conclusions By performing analyses of several publicly available datasets and simulated datasets we demonstrate that our adaptive method increases sensitivity of finding differentially expressed genes compared to previous methods of filtering microarray data based on using fixed threshold values. PMID:23510016

  14. Improving the response of accelerometers for automotive applications by using LMS adaptive filters.

    Science.gov (United States)

    Hernandez, Wilmar; de Vicente, Jesús; Sergiyenko, Oleg; Fernández, Eduardo

    2010-01-01

    In this paper, the least-mean-squares (LMS) algorithm was used to eliminate noise corrupting the important information coming from a piezoresisitive accelerometer for automotive applications. This kind of accelerometer is designed to be easily mounted in hard to reach places on vehicles under test, and they usually feature ranges from 50 to 2,000 g (where is the gravitational acceleration, 9.81 m/s(2)) and frequency responses to 3,000 Hz or higher, with DC response, durable cables, reliable performance and relatively low cost. However, here we show that the response of the sensor under test had a lot of noise and we carried out the signal processing stage by using both conventional and optimal adaptive filtering. Usually, designers have to build their specific analog and digital signal processing circuits, and this fact increases considerably the cost of the entire sensor system and the results are not always satisfactory, because the relevant signal is sometimes buried in a broad-band noise background where the unwanted information and the relevant signal sometimes share a very similar frequency band. Thus, in order to deal with this problem, here we used the LMS adaptive filtering algorithm and compare it with others based on the kind of filters that are typically used for automotive applications. The experimental results are satisfactory.

  15. Adaptive Spatial Filtering of Interferometric Data Stack Oriented to Distributed Scatterers

    Science.gov (United States)

    Zhang, Y.; Xie, C.; Shao, Y.; Yuan, M.

    2013-07-01

    Standard interferometry poses a challenge in non-urban areas due to temporal and spatial decorrelation of the radar signal, where there is high signal noise. Techniques such as Small Baseline Subset Algorithm (SBAS) have been proposed to make use of multiple interferometric combinations to alleviate the problem. However, the interferograms used in SBAS are multilooked with a boxcar (rectangle) filter to reduce phase noise, resulting in a loss of resolution and signal superstition from different objects. In this paper, we proposed a modified adaptive spatial filtering algorithm for accurate estimation of interferogram and coherence without resolution loss even in rural areas, to better support the deformation monitoring with time series interferometric synthetic aperture radar (InSAR) technique. The implemented method identifies the statistically homogenous pixels in a neighbourhood based on the goodness-of-fit test, and then applies an adaptive spatial filtering of interferograms. Three statistical tests for the identification of distributed targets will be presented, applied to real data. PALSAR data of the yellow river delta in China is used for demonstrating the effectiveness of this algorithm in rural areas.

  16. Data assimilation for unsaturated flow models with restart adaptive probabilistic collocation based Kalman filter

    Energy Technology Data Exchange (ETDEWEB)

    Man, Jun; Li, Weixuan; Zeng, Lingzao; Wu, Laosheng

    2016-06-01

    The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a relatively large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the polynomial chaos to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so-called "curse of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF could be even more computationally expensive than EnKF. Motivated by most recent developments in uncertainty quantification, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problems. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected. The "restart" technology is used to eliminate the inconsistency between model parameters and states. The performance of RAPCKF is tested with numerical cases of unsaturated flow models. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.

  17. Hybrid Adaptive Filter development for the minimisation of transient fluctuations superimposed on electrotelluric field recordings mainly by magnetic storms

    Directory of Open Access Journals (Sweden)

    A. Konstantaras

    2006-01-01

    Full Text Available The method of Hybrid Adaptive Filtering (HAF aims to recover the recorded electric field signals from anomalies of magnetotelluric origin induced mainly by magnetic storms. An adaptive filter incorporating neuro-fuzzy technology has been developed to remove any significant distortions from the equivalent magnetic field signal, as retrieved from the original electric field signal by reversing the magnetotelluric method. Testing with further unseen data verifies the reliability of the model and demonstrates the effectiveness of the HAF method.

  18. Hybrid Adaptive Filter development for the minimisation of transient fluctuations superimposed on electrotelluric field recordings mainly by magnetic storms

    OpenAIRE

    Konstantaras, A.; Varley, M. R.; Vallianatos, F.; Makris, J. P.; Collins, G.; Holifield, P.

    2006-01-01

    The method of Hybrid Adaptive Filtering (HAF) aims to recover the recorded electric field signals from anomalies of magnetotelluric origin induced mainly by magnetic storms. An adaptive filter incorporating neuro-fuzzy technology has been developed to remove any significant distortions from the equivalent magnetic field signal, as retrieved from the original electric field signal by reversing the magnetotelluric method. Testing with further unseen data verifies the reliability of the model an...

  19. Hybrid Adaptive Filter development for the minimisation of transient fluctuations superimposed on electrotelluric field recordings mainly by magnetic storms

    OpenAIRE

    A. Konstantaras; M. R. Varley; F. Vallianatos; J. P. Makris; G. Collins; P.  Holifield

    2006-01-01

    International audience; The method of Hybrid Adaptive Filtering (HAF) aims to recover the recorded electric field signals from anomalies of magnetotelluric origin induced mainly by magnetic storms. An adaptive filter incorporating neuro-fuzzy technology has been developed to remove any significant distortions from the equivalent magnetic field signal, as retrieved from the original electric field signal by reversing the magnetotelluric method. Testing with further unseen data verifies the rel...

  20. Hybrid Adaptive Filter development for the minimisation of transient fluctuations superimposed on electrotelluric field recordings mainly by magnetic storms

    Science.gov (United States)

    Konstantaras, A.; Varley, M. R.; Vallianatos, F.; Makris, J. P.; Collins, G.; Holifield, P.

    2006-10-01

    The method of Hybrid Adaptive Filtering (HAF) aims to recover the recorded electric field signals from anomalies of magnetotelluric origin induced mainly by magnetic storms. An adaptive filter incorporating neuro-fuzzy technology has been developed to remove any significant distortions from the equivalent magnetic field signal, as retrieved from the original electric field signal by reversing the magnetotelluric method. Testing with further unseen data verifies the reliability of the model and demonstrates the effectiveness of the HAF method.

  1. Adaptive hybrid likelihood model for visual tracking based on Gaussian particle filter

    Science.gov (United States)

    Wang, Yong; Tan, Yihua; Tian, Jinwen

    2010-07-01

    We present a new scheme based on multiple-cue integration for visual tracking within a Gaussian particle filter framework. The proposed method integrates the color, shape, and texture cues of an object to construct a hybrid likelihood model. During the measurement step, the likelihood model can be switched adaptively according to environmental changes, which improves the object representation to deal with the complex disturbances, such as appearance changes, partial occlusions, and significant clutter. Moreover, the confidence weights of the cues are adjusted online through the estimation using a particle filter, which ensures the tracking accuracy and reliability. Experiments are conducted on several real video sequences, and the results demonstrate that the proposed method can effectively track objects in complex scenarios. Compared with previous similar approaches through some quantitative and qualitative evaluations, the proposed method performs better in terms of tracking robustness and precision.

  2. Rapid Transfer Alignment of MEMS SINS Based on Adaptive Incremental Kalman Filter.

    Science.gov (United States)

    Chu, Hairong; Sun, Tingting; Zhang, Baiqiang; Zhang, Hongwei; Chen, Yang

    2017-01-14

    In airborne MEMS SINS transfer alignment, the error of MEMS IMU is highly environment-dependent and the parameters of the system model are also uncertain, which may lead to large error and bad convergence of the Kalman filter. In order to solve this problem, an improved adaptive incremental Kalman filter (AIKF) algorithm is proposed. First, the model of SINS transfer alignment is defined based on the "Velocity and Attitude" matching method. Then the detailed algorithm progress of AIKF and its recurrence formulas are presented. The performance and calculation amount of AKF and AIKF are also compared. Finally, a simulation test is designed to verify the accuracy and the rapidity of the AIKF algorithm by comparing it with KF and AKF. The results show that the AIKF algorithm has better estimation accuracy and shorter convergence time, especially for the bias of the gyroscope and the accelerometer, which can meet the accuracy and rapidity requirement of transfer alignment.

  3. Fuzzy adaptive strong tracking scaled unscented Kalman filter for initial alignment of large misalignment angles

    Science.gov (United States)

    Li, Jing; Song, Ningfang; Yang, Gongliu; Jiang, Rui

    2016-07-01

    In the initial alignment process of strapdown inertial navigation system (SINS), large misalignment angles always bring nonlinear problem, which can usually be processed using the scaled unscented Kalman filter (SUKF). In this paper, the problem of large misalignment angles in SINS alignment is further investigated, and the strong tracking scaled unscented Kalman filter (STSUKF) is proposed with fixed parameters to improve convergence speed, while these parameters are artificially constructed and uncertain in real application. To further improve the alignment stability and reduce the parameters selection, this paper proposes a fuzzy adaptive strategy combined with STSUKF (FUZZY-STSUKF). As a result, initial alignment scheme of large misalignment angles based on FUZZY-STSUKF is designed and verified by simulations and turntable experiment. The results show that the scheme improves the accuracy and convergence speed of SINS initial alignment compared with those based on SUKF and STSUKF.

  4. Waveform frequency notching

    Energy Technology Data Exchange (ETDEWEB)

    Doerry, Armin W.; Andrews, John

    2017-05-09

    The various technologies presented herein relate to incorporating one or more notches into a radar spectrum, whereby the notches relate to one or more frequencies for which no radar transmission is to occur. An instantaneous frequency is monitored and if the frequency is determined to be of a restricted frequency, then a radar signal can be modified. Modification can include replacing the signal with a signal having a different instantaneous amplitude, a different instantaneous phase, etc. The modification can occur in a WFS prior to a DAC, as well as prior to a sin ROM component and/or a cos ROM component. Further, the notch can be dithered to enable formation of a deep notch. The notch can also undergo signal transitioning to enable formation of a deep notch. The restricted frequencies can be stored in a LUT against which an instantaneous frequency can be compared.

  5. A Frequency-Domain Adaptive Matched Filter for Active Sonar Detection.

    Science.gov (United States)

    Zhao, Zhishan; Zhao, Anbang; Hui, Juan; Hou, Baochun; Sotudeh, Reza; Niu, Fang

    2017-07-04

    The most classical detector of active sonar and radar is the matched filter (MF), which is the optimal processor under ideal conditions. Aiming at the problem of active sonar detection, we propose a frequency-domain adaptive matched filter (FDAMF) with the use of a frequency-domain adaptive line enhancer (ALE). The FDAMF is an improved MF. In the simulations in this paper, the signal to noise ratio (SNR) gain of the FDAMF is about 18.6 dB higher than that of the classical MF when the input SNR is -10 dB. In order to improve the performance of the FDAMF with a low input SNR, we propose a pre-processing method, which is called frequency-domain time reversal convolution and interference suppression (TRC-IS). Compared with the classical MF, the FDAMF combined with the TRC-IS method obtains higher SNR gain, a lower detection threshold, and a better receiver operating characteristic (ROC) in the simulations in this paper. The simulation results show that the FDAMF has higher processing gain and better detection performance than the classical MF under ideal conditions. The experimental results indicate that the FDAMF does improve the performance of the MF, and can adapt to actual interference in a way. In addition, the TRC-IS preprocessing method works well in an actual noisy ocean environment.

  6. Notch signaling and ageing.

    Science.gov (United States)

    Polychronidou, Eleftheria; Vlachakis, Dimitrios; Vlamos, Panayiotis; Baumann, Marc; Kossida, Sophia

    2015-01-01

    Notch signaling is a master controller of the neural stem cell and neural development maintaining a significant role in the normal brain function. Notch genes are involved in embryogenesis, nervous system, and cardiovascular and endocrine function. On the other side, there are studies representing the involvement of Notch mutations in sporadic Alzheimer disease, other neurodegenerative diseases such as Down syndrome, Pick's and Prion's disease, and CADASIL. This manuscript attempts to present a holistic view of the positive or negative contribution of Notch signaling in the adult brain, and at the same time to present and promote the promising research fields of study.

  7. Estimation, filtering and adaptative control of a waste water processing process; Estimation, filtrage et commande adaptive d`un procede de traitement des eaux usees

    Energy Technology Data Exchange (ETDEWEB)

    Ben Youssef, C.; Dahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Rols, J.L. [Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)

    1995-12-31

    Controlling the process of a fixed bed bioreactor imply solving filtering and adaptative control problems. Estimation processes have been developed for unmeasurable parameters. An adaptative non linear control has been built, instead of conventional approaches trying to linearize the system and apply a linear control system. (D.L.) 10 refs.

  8. Improved prediction error filters for adaptive feedback cancellation in hearing aids

    DEFF Research Database (Denmark)

    Ngo, Kim; van Waterschoot, Toon; Christensen, Mads Græsbøll

    2013-01-01

    and the loudspeaker signal caused by the closed signal loop, in particular when the near-end signal is spectrally colored as is the case for a speech signal. This paper adopts a prediction-error method (PEM)-based approach to AFC, which is based on the use of decorrelating prediction error filters (PEFs). We propose......Acoustic feedback is a well-known problem in hearing aids, caused by the undesired acoustic coupling between the hearing aid loudspeaker and microphone. Acoustic feedback produces annoying howling sounds and limits the maximum achievable hearing aid amplification. This paper is focused on adaptive...

  9. LMI Design of Frequency Selective LMS Adaptive Filters and Its Application to Active Noise Control

    Science.gov (United States)

    Wakasa, Yuji; Izumi, Tatsuya; Yamamoto, Yutaka

    Recently, a frequency selective adaptive filter design method for active noise control has been proposed based on the so-called least mean square algorithm. However, this method does not sufficiently exploit the degree of freedom of the step parameter of the recursive rule in the case where a priori information on an uncertain plant is available. This paper proposes a design method of the step parameter such that noise cancellation is guaranteed against the plant uncertainty. The design problem of the step parameter is reduced to an optimization problem involving linear matrix inequalities and is efficiently solvable. Experimental results are provided to illustrate the effectiveness of the proposed method.

  10. Performance and stochastic stability of the adaptive fading extended Kalman filter with the matrix forgetting factor

    Directory of Open Access Journals (Sweden)

    Biçer Cenker

    2016-01-01

    Full Text Available In this paper, the stability of the adaptive fading extended Kalman filter with the matrix forgetting factor when applied to the state estimation problem with noise terms in the non–linear discrete–time stochastic systems has been analysed. The analysis is conducted in a similar manner to the standard extended Kalman filter’s stability analysis based on stochastic framework. The theoretical results show that under certain conditions on the initial estimation error and the noise terms, the estimation error remains bounded and the state estimation is stable.

  11. Target-adaptive polarimetric synthetic aperture radar target discrimination using maximum average correlation height filters.

    Science.gov (United States)

    Sadjadi, Firooz A; Mahalanobis, Abhijit

    2006-05-01

    We report the development of a technique for adaptive selection of polarization ellipse tilt and ellipticity angles such that the target separation from clutter is maximized. From the radar scattering matrix [S] and its complex components, in phase and quadrature phase, the elements of the Mueller matrix are obtained. Then, by means of polarization synthesis, the radar cross section of the radar scatters are obtained at different transmitting and receiving polarization states. By designing a maximum average correlation height filter, we derive a target versus clutter distance measure as a function of four transmit and receive polarization state angles. The results of applying this method on real synthetic aperture radar imagery indicate a set of four transmit and receive angles that lead to maximum target versus clutter discrimination. These optimum angles are different for different targets. Hence, by adaptive control of the state of polarization of polarimetric radar, one can noticeably improve the discrimination of targets from clutter.

  12. Temporal Scalability through Adaptive -Band Filter Banks for Robust H.264/MPEG-4 AVC Video Coding

    Directory of Open Access Journals (Sweden)

    Pau G

    2006-01-01

    Full Text Available This paper presents different structures that use adaptive -band hierarchical filter banks for temporal scalability. Open-loop and closed-loop configurations are introduced and illustrated using existing video codecs. In particular, it is shown that the H.264/MPEG-4 AVC codec allows us to introduce scalability by frame shuffling operations, thus keeping backward compatibility with the standard. The large set of shuffling patterns introduced here can be exploited to adapt the encoding process to the video content features, as well as to the user equipment and transmission channel characteristics. Furthermore, simulation results show that this scalability is obtained with no degradation in terms of subjective and objective quality in error-free environments, while in error-prone channels the scalable versions provide increased robustness.

  13. Adaptive filtering methods for identifying cross-frequency couplings in human EEG.

    Directory of Open Access Journals (Sweden)

    Jérôme Van Zaen

    Full Text Available Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.

  14. Quaternion-Based Kalman Filter for AHRS Using an Adaptive-Step Gradient Descent Algorithm

    Directory of Open Access Journals (Sweden)

    Li Wang

    2015-09-01

    Full Text Available This paper presents a quaternion-based Kalman filter for real-time estimation of the orientation of a quadrotor. Quaternions are used to represent rotation relationship between navigation frame and body frame. Processing of a 3-axis accelerometer using Adaptive-Step Gradient Descent (ASGD produces a computed quaternion input to the Kalman filter. The step-size in GD is set in direct proportion to the physical orientation rate. Kalman filter combines 3-axis gyroscope and computed quaternion to determine pitch and roll angles. This combination overcomes linearization error of the measurement equations and reduces the calculation cost. 3-axis magnetometer is separated from ASGD to independently calculate yaw angle for Attitude Heading Reference System (AHRS. This AHRS algorithm is able to remove the magnetic distortion impact. Experiments are carried out in the small-size flight controller and the real world flying test shows the proposed AHRS algorithm is adequate for the real-time estimation of the orientation of a quadrotor.

  15. Three-State Locally Adaptive Texture Preserving Filter for Radar and Optical Image Processing

    Directory of Open Access Journals (Sweden)

    Jaakko T. Astola

    2005-05-01

    Full Text Available Textural features are one of the most important types of useful information contained in images. In practice, these features are commonly masked by noise. Relatively little attention has been paid to texture preserving properties of noise attenuation methods. This stimulates solving the following tasks: (1 to analyze the texture preservation properties of various filters; and (2 to design image processing methods capable to preserve texture features well and to effectively reduce noise. This paper deals with examining texture feature preserving properties of different filters. The study is performed for a set of texture samples and different noise variances. The locally adaptive three-state schemes are proposed for which texture is considered as a particular class. For “detection” of texture regions, several classifiers are proposed and analyzed. As shown, an appropriate trade-off of the designed filter properties is provided. This is demonstrated quantitatively for artificial test images and is confirmed visually for real-life images.

  16. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array

    Science.gov (United States)

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J.; Urbas, Augustine

    2016-10-01

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed “algorithmic spectrometry”. We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme.

  17. Experimental Demonstration of Adaptive Infrared Multispectral Imaging using Plasmonic Filter Array.

    Science.gov (United States)

    Jang, Woo-Yong; Ku, Zahyun; Jeon, Jiyeon; Kim, Jun Oh; Lee, Sang Jun; Park, James; Noyola, Michael J; Urbas, Augustine

    2016-10-10

    In our previous theoretical study, we performed target detection using a plasmonic sensor array incorporating the data-processing technique termed "algorithmic spectrometry". We achieved the reconstruction of a target spectrum by extracting intensity at multiple wavelengths with high resolution from the image data obtained from the plasmonic array. The ultimate goal is to develop a full-scale focal plane array with a plasmonic opto-coupler in order to move towards the next generation of versatile infrared cameras. To this end, and as an intermediate step, this paper reports the experimental demonstration of adaptive multispectral imagery using fabricated plasmonic spectral filter arrays and proposed target detection scenarios. Each plasmonic filter was designed using periodic circular holes perforated through a gold layer, and an enhanced target detection strategy was proposed to refine the original spectrometry concept for spatial and spectral computation of the data measured from the plasmonic array. Both the spectrum of blackbody radiation and a metal ring object at multiple wavelengths were successfully reconstructed using the weighted superposition of plasmonic output images as specified in the proposed detection strategy. In addition, plasmonic filter arrays were theoretically tested on a target at extremely high temperature as a challenging scenario for the detection scheme.

  18. Research of fetal ECG extraction using wavelet analysis and adaptive filtering.

    Science.gov (United States)

    Wu, Shuicai; Shen, Yanni; Zhou, Zhuhuang; Lin, Lan; Zeng, Yanjun; Gao, Xiaofeng

    2013-10-01

    Extracting clean fetal electrocardiogram (ECG) signals is very important in fetal monitoring. In this paper, we proposed a new method for fetal ECG extraction based on wavelet analysis, the least mean square (LMS) adaptive filtering algorithm, and the spatially selective noise filtration (SSNF) algorithm. First, abdominal signals and thoracic signals were processed by stationary wavelet transform (SWT), and the wavelet coefficients at each scale were obtained. For each scale, the detail coefficients were processed by the LMS algorithm. The coefficient of the abdominal signal was taken as the original input of the LMS adaptive filtering system, and the coefficient of the thoracic signal as the reference input. Then, correlations of the processed wavelet coefficients were computed. The threshold was set and noise components were removed with the SSNF algorithm. Finally, the processed wavelet coefficients were reconstructed by inverse SWT to obtain fetal ECG. Twenty cases of simulated data and 12 cases of clinical data were used. Experimental results showed that the proposed method outperforms the LMS algorithm: (1) it shows improvement in case of superposition R-peaks of fetal ECG and maternal ECG; (2) noise disturbance is eliminated by incorporating the SSNF algorithm and the extracted waveform is more stable; and (3) the performance is proven quantitatively by SNR calculation. The results indicated that the proposed algorithm can be used for extracting fetal ECG from abdominal signals. © 2013 Elsevier Ltd. All rights reserved.

  19. AMA- and RWE- Based Adaptive Kalman Filter for Denoising Fiber Optic Gyroscope Drift Signal.

    Science.gov (United States)

    Yang, Gongliu; Liu, Yuanyuan; Li, Ming; Song, Shunguang

    2015-10-23

    An improved double-factor adaptive Kalman filter called AMA-RWE-DFAKF is proposed to denoise fiber optic gyroscope (FOG) drift signal in both static and dynamic conditions. The first factor is Kalman gain updated by random weighting estimation (RWE) of the covariance matrix of innovation sequence at any time to ensure the lowest noise level of output, but the inertia of KF response increases in dynamic condition. To decrease the inertia, the second factor is the covariance matrix of predicted state vector adjusted by RWE only when discontinuities are detected by adaptive moving average (AMA).The AMA-RWE-DFAKF is applied for denoising FOG static and dynamic signals, its performance is compared with conventional KF (CKF), RWE-based adaptive KF with gain correction (RWE-AKFG), AMA- and RWE- based dual mode adaptive KF (AMA-RWE-DMAKF). Results of Allan variance on static signal and root mean square error (RMSE) on dynamic signal show that this proposed algorithm outperforms all the considered methods in denoising FOG signal.

  20. An Adaptive Approach to Mitigate Background Covariance Limitations in the Ensemble Kalman Filter

    KAUST Repository

    Song, Hajoon

    2010-07-01

    A new approach is proposed to address the background covariance limitations arising from undersampled ensembles and unaccounted model errors in the ensemble Kalman filter (EnKF). The method enhances the representativeness of the EnKF ensemble by augmenting it with new members chosen adaptively to add missing information that prevents the EnKF from fully fitting the data to the ensemble. The vectors to be added are obtained by back projecting the residuals of the observation misfits from the EnKF analysis step onto the state space. The back projection is done using an optimal interpolation (OI) scheme based on an estimated covariance of the subspace missing from the ensemble. In the experiments reported here, the OI uses a preselected stationary background covariance matrix, as in the hybrid EnKF–three-dimensional variational data assimilation (3DVAR) approach, but the resulting correction is included as a new ensemble member instead of being added to all existing ensemble members. The adaptive approach is tested with the Lorenz-96 model. The hybrid EnKF–3DVAR is used as a benchmark to evaluate the performance of the adaptive approach. Assimilation experiments suggest that the new adaptive scheme significantly improves the EnKF behavior when it suffers from small size ensembles and neglected model errors. It was further found to be competitive with the hybrid EnKF–3DVAR approach, depending on ensemble size and data coverage.

  1. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

    Directory of Open Access Journals (Sweden)

    Maryam M Shanechi

    2016-04-01

    Full Text Available Much progress has been made in brain-machine interfaces (BMI using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA. However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC model of the brain's behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user's motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was

  2. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

    Science.gov (United States)

    Shanechi, Maryam M; Orsborn, Amy L; Carmena, Jose M

    2016-04-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain's behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user's motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter

  3. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering

    Science.gov (United States)

    Carmena, Jose M.

    2016-01-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain’s behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user’s motor intention during CLDA—a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to

  4. An innovations-based noise cancelling technique on inverse kepstrum whitening filter and adaptive FIR filter in beamforming structure

    National Research Council Canada - National Science Library

    Jeong, Jinsoo

    2011-01-01

    ...) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal...

  5. Research on the Random Shock Vibration Test Based on the Filter-X LMS Adaptive Inverse Control Algorithm

    Directory of Open Access Journals (Sweden)

    Wang Wei

    2016-01-01

    Full Text Available The related theory and algorithm of adaptive inverse control were presented through the research which pointed out the adaptive inverse control strategy could effectively eliminate the noise influence on the system control. Proposed using a frequency domain filter-X LMS adaptive inverse control algorithm, and the control algorithm was applied to the two-exciter hydraulic vibration test system of random shock vibration control process and summarized the process of the adaptive inverse control strategies in the realization of the random shock vibration test. The self-closed-loop and field test show that using the frequency-domain filter-X LMS adaptive inverse control algorithm can realize high precision control of random shock vibration test.

  6. An Improved WiFi/PDR Integrated System Using an Adaptive and Robust Filter for Indoor Localization

    Directory of Open Access Journals (Sweden)

    Zengke Li

    2016-11-01

    Full Text Available Location-based services (LBS are services offered through a mobile device that take into account a device’s geographical location. To provide position information for these services, location is a key process. GNSS (Global Navigation Satellite System can provide sub-meter accuracy in open-sky areas using satellite signals. However, for indoor and dense urban environments, the accuracy deteriorates significantly because of weak signals and dense multipaths. The situation becomes worse in indoor environments where the GNSS signals are unreliable or totally blocked. To improve the accuracy of indoor positioning for location-based services, an improved WiFi/Pedestrian Dead Reckoning (PDR integrated positioning and navigation system using an adaptive and robust filter is presented. The adaptive filter is based on scenario and motion state recognition and the robust filter is based on the Mahalanobis distance. They are combined and used in the WiFi/PDR integrated system to weaken the effect of gross errors on the dynamic and observation models. To validate their performance in the WiFi/PDR integrated system, a real indoor localization experiment is conducted. The results indicate that the adaptive filter is better able to adapt to the circumstances of the dynamic model by adjusting the covariance of the process noise and the robust Kalman filter is able to mitigate the harmful effect of gross errors from the WiFi positioning.

  7. Adaptive UAV attitude estimation employing unscented Kalman Filter, FOAM and low-cost MEMS sensors.

    Science.gov (United States)

    de Marina, Héctor García; Espinosa, Felipe; Santos, Carlos

    2012-01-01

    Navigation employing low cost MicroElectroMechanical Systems (MEMS) sensors in Unmanned Aerial Vehicles (UAVs) is an uprising challenge. One important part of this navigation is the right estimation of the attitude angles. Most of the existent algorithms handle the sensor readings in a fixed way, leading to large errors in different mission stages like take-off aerobatic maneuvers. This paper presents an adaptive method to estimate these angles using off-the-shelf components. This paper introduces an Attitude Heading Reference System (AHRS) based on the Unscented Kalman Filter (UKF) using the Fast Optimal Attitude Matrix (FOAM) algorithm as the observation model. The performance of the method is assessed through simulations. Moreover, field experiments are presented using a real fixed-wing UAV. The proposed low cost solution, implemented in a microcontroller, shows a satisfactory real time performance.

  8. A hybrid robust fault tolerant control based on adaptive joint unscented Kalman filter.

    Science.gov (United States)

    Shabbouei Hagh, Yashar; Mohammadi Asl, Reza; Cocquempot, Vincent

    2017-01-01

    In this paper, a new hybrid robust fault tolerant control scheme is proposed. A robust H∞ control law is used in non-faulty situation, while a Non-Singular Terminal Sliding Mode (NTSM) controller is activated as soon as an actuator fault is detected. Since a linear robust controller is designed, the system is first linearized through the feedback linearization method. To switch from one controller to the other, a fuzzy based switching system is used. An Adaptive Joint Unscented Kalman Filter (AJUKF) is used for fault detection and diagnosis. The proposed method is based on the simultaneous estimation of the system states and parameters. In order to show the efficiency of the proposed scheme, a simulated 3-DOF robotic manipulator is used. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Subband Adaptive Filtering with l1-Norm Constraint for Sparse System Identification

    Directory of Open Access Journals (Sweden)

    Young-Seok Choi

    2013-01-01

    Full Text Available This paper presents a new approach of the normalized subband adaptive filter (NSAF which directly exploits the sparsity condition of an underlying system for sparse system identification. The proposed NSAF integrates a weighted l1-norm constraint into the cost function of the NSAF algorithm. To get the optimum solution of the weighted l1-norm regularized cost function, a subgradient calculus is employed, resulting in a stochastic gradient based update recursion of the weighted l1-norm regularized NSAF. The choice of distinct weighted l1-norm regularization leads to two versions of the l1-norm regularized NSAF. Numerical results clearly indicate the superior convergence of the l1-norm regularized NSAFs over the classical NSAF especially when identifying a sparse system.

  10. Design of Power Cable UAV Intelligent Patrol System Based on Adaptive Kalman Filter Fuzzy PID Control

    Directory of Open Access Journals (Sweden)

    Chen Siyu

    2017-01-01

    Full Text Available Patrol UAV has poor aerial posture stability and is largely affected by anthropic factors, which lead to some shortages such as low power cable tracking precision, captured image loss and inconvenient temperature measurement, etc. In order to solve these disadvantages, this article puts forward a power cable intelligent patrol system. The core innovation of the system is a 360° platform. This collects the position information of power cables by using far infrared sensors and carries out real-time all-direction adjustment of UAV lifting platform through the adaptive Kalman filter fuzzy PID control algorithm, so that the precise tracking of power cables is achieved. An intelligent patrol system is established to detect the faults more accurately, so that a high intelligence degree of power cable patrol system is realized.

  11. Adaptive Kalman filter for indoor localization using Bluetooth Low Energy and inertial measurement unit.

    Science.gov (United States)

    Yoon, Paul K; Zihajehzadeh, Shaghayegh; Bong-Soo Kang; Park, Edward J

    2015-08-01

    This paper proposes a novel indoor localization method using the Bluetooth Low Energy (BLE) and an inertial measurement unit (IMU). The multipath and non-line-of-sight errors from low-power wireless localization systems commonly result in outliers, affecting the positioning accuracy. We address this problem by adaptively weighting the estimates from the IMU and BLE in our proposed cascaded Kalman filter (KF). The positioning accuracy is further improved with the Rauch-Tung-Striebel smoother. The performance of the proposed algorithm is compared against that of the standard KF experimentally. The results show that the proposed algorithm can maintain high accuracy for position tracking the sensor in the presence of the outliers.

  12. Cancellation of artifacts in ECG signals using block adaptive filtering techniques.

    Science.gov (United States)

    Rahman, Mohammad Zia Ur; Shaik, Rafi Ahamed; Reddy, D V Rama Koti

    2011-01-01

    In this chapter, various block-based adaptive filter structures are presented, which estimate the deterministic components of the electrocardiogram (ECG) signal and remove the noise. The familiar Block LMS algorithm (BLMS) and its fast implementation, Fast Block LMS (FBLMS) algorithm, is proposed for removing artifacts preserving the low frequency components and tiny features of the ECG. The proposed implementation is suitable for applications requiring large signal-to-noise ratios with fast convergence rate. Finally, we have applied these algorithms on real ECG signals obtained from the MIT-BIH database and compared its performance with the conventional LMS algorithm. The results show that the performance of the block-based algorithms is superior than the LMS algorithm.

  13. Dim small targets detection based on self-adaptive caliber temporal-spatial filtering

    Science.gov (United States)

    Fan, Xiangsuo; Xu, Zhiyong; Zhang, Jianlin; Huang, Yongmei; Peng, Zhenming

    2017-09-01

    To boost the detect ability of dim small targets, this paper began by using improved anisotropy for background prediction (IABP), followed by target enhancement by improved high-order cumulates (HQS). Finally, on the basis of image pre-processing, to address the problem of missed and wrong detection caused by fixed caliber of traditional pipeline filtering, this paper used targets' multi-frame movement correlation in the time-space domain, combined with the scale-space theory, to propose a temporal-spatial filtering algorithm which allows the caliber to make self-adaptive changes according to the changes of the targets' scale, effectively solving the detection-related issues brought by unchanged caliber and decreased/increased size of the targets. Experiments showed that the improved anisotropic background predication could be loyal to the true background of the original image to the maximum extent, presenting a superior overall performance to other background prediction methods; the improved HQS significantly increased the signal-noise ratio of images; when the signal-noise ratio was lower than 2.6 dB, this detection algorithm could effectively eliminate noise and detect targets. For the algorithm, the lowest signal-to-noise ratio of the detectable target is 0.37.

  14. Local spectral adaptive multitaper method with bilateral filtering for spectrum analysis of mammographic images

    Science.gov (United States)

    Wu, Gang; Mainprize, James G.; Yaffe, Martin J.

    2012-03-01

    Estimation of the image power spectrum is fundamental to the development of a figure of merit for image performance analysis. We are investigating a new multitaper approach to determine power spectra, which provides a combination of low variance and high spectral resolution in the frequency range of interest. To further reduce the variance, the spectrum estimated by the proposed Local Spectral Adaptive Multitaper Method (LSAMTM) is subsequently smoothed in the frequency domain by bilateral filtering, while keeping the spectral resolution intact. This tool will be especially valuable in power spectrum estimation of images that deviate significantly from uniform white noise. The performance of this approach was evaluated in terms of spectral stability, variance reduction, bias and frequency precision. It was also compared to the conventional power spectrum method in several typical situations, including the noise power spectra (NPS) measurements of simulated projection images of a uniform phantom and NPS measurement of real detector images of a uniform phantom for two clinical digital mammography systems. Examination of variance reduction versus spectral resolution and bias indicates that the LSAMTM with bilateral filtering technique is superior to the conventional estimation methods in variance reduction, spectral resolution and in the prevention of spectrum leakage. It has the ability to keep both low variance and narrow spectral linewidth in the frequency range of interest. Up to 87% more variance reduction can be achieved with proper filtration and no sacrifice of frequency precision has been observed.

  15. Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications.

    Science.gov (United States)

    Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

    2017-12-27

    Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

  16. Adaptive Kalman Filter Based on Adjustable Sampling Interval in Burst Detection for Water Distribution System

    Directory of Open Access Journals (Sweden)

    Doo Yong Choi

    2016-04-01

    Full Text Available Rapid detection of bursts and leaks in water distribution systems (WDSs can reduce the social and economic costs incurred through direct loss of water into the ground, additional energy demand for water supply, and service interruptions. Many real-time burst detection models have been developed in accordance with the use of supervisory control and data acquisition (SCADA systems and the establishment of district meter areas (DMAs. Nonetheless, no consideration has been given to how frequently a flow meter measures and transmits data for predicting breaks and leaks in pipes. This paper analyzes the effect of sampling interval when an adaptive Kalman filter is used for detecting bursts in a WDS. A new sampling algorithm is presented that adjusts the sampling interval depending on the normalized residuals of flow after filtering. The proposed algorithm is applied to a virtual sinusoidal flow curve and real DMA flow data obtained from Jeongeup city in South Korea. The simulation results prove that the self-adjusting algorithm for determining the sampling interval is efficient and maintains reasonable accuracy in burst detection. The proposed sampling method has a significant potential for water utilities to build and operate real-time DMA monitoring systems combined with smart customer metering systems.

  17. A Frequency-Domain Adaptive Filter (FDAF) Prediction Error Method (PEM) Framework for Double-Talk-Robust Acoustic Echo Cancellation

    DEFF Research Database (Denmark)

    Gil-Cacho, Jose M.; van Waterschoot, Toon; Moonen, Marc

    2014-01-01

    In this paper, we propose a new framework to tackle the double-talk (DT) problem in acoustic echo cancellation (AEC). It is based on a frequency-domain adaptive filter (FDAF) implementation of the so-called prediction error method adaptive filtering using row operations (PEM-AFROW) leading to the...... regularization (VR) algorithms. The FDAF-PEM-AFROW versions significantly outperform the original versions in every simulation. In terms of computational complexity, the FDAF-PEM-AFROW versions are themselves about two orders of magnitude cheaper than the original versions....

  18. A MIT-Based Nonlinear Adaptive Set-Membership Filter for the Ellipsoidal Estimation of Mobile Robots' States

    Directory of Open Access Journals (Sweden)

    Dalei Song

    2012-10-01

    Full Text Available The adaptive extended set-membership filter (AESMF for nonlinear ellipsoidal estimation suffers a mismatch between real process noise and its set boundaries, which may result in unstable estimation. In this paper, a MIT method-based adaptive set-membership filter, for the optimization of the set boundaries of process noise, is developed and applied to the nonlinear joint estimation of both time-varying states and parameters. As a result of using the proposed MIT-AESMF, the estimation effectiveness and boundary accuracy of traditional AESMF are substantially improved. Simulation results have shown the efficiency and robustness of the proposed method.

  19. A novel adaptive discrete cosine transform-domain filter for gap-inpainting of high resolution PET scanners

    Energy Technology Data Exchange (ETDEWEB)

    Shih, Cheng-Ting; Lin, Hsin-Hon; Chuang, Keh-Shih [Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu 30013, Taiwan (China); Wu, Jay, E-mail: jwu@mail.cmu.edu.tw [Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung 40402, Taiwan (China); Chang, Shu-Jun [Health Physics Division, Institute of Nuclear Energy Research, Atomic Energy Council, Taoyuan 32546, Taiwan (China)

    2014-08-15

    Purpose: Several positron emission tomography (PET) scanners with special detector block arrangements have been developed in recent years to improve the resolution of PET images. However, the discontinuous detector blocks cause gaps in the sinogram. This study proposes an adaptive discrete cosine transform-based (aDCT) filter for gap-inpainting. Methods: The gap-corrupted sinogram was morphologically closed and subsequently converted to the DCT domain. A certain number of the largest coefficients in the DCT spectrum were identified to determine the low-frequency preservation region. The weighting factors for the remaining coefficients were determined by an exponential weighting function. The aDCT filter was constructed and applied to two digital phantoms and a simulated phantom introduced with various levels of noise. Results: For the Shepp-Logan head phantom, the aDCT filter filled the gaps effectively. For the Jaszczak phantom, no secondary artifacts were induced after aDCT filtering. The percent mean square error and mean structure similarity of the aDCT filter were superior to those of the DCT2 filter at all noise levels. For the simulated striatal dopamine innervation study, the aDCT filter recovered the shape of the striatum and restored the striatum to reference activity ratios to the ideal value. Conclusions: The proposed aDCT filter can recover the missing gap data in the sinogram and improve the image quality and quantitative accuracy of PET images.

  20. A novel adaptive discrete cosine transform-domain filter for gap-inpainting of high resolution PET scanners.

    Science.gov (United States)

    Shih, Cheng-Ting; Wu, Jay; Lin, Hsin-Hon; Chang, Shu-Jun; Chuang, Keh-Shih

    2014-08-01

    Several positron emission tomography (PET) scanners with special detector block arrangements have been developed in recent years to improve the resolution of PET images. However, the discontinuous detector blocks cause gaps in the sinogram. This study proposes an adaptive discrete cosine transform-based (aDCT) filter for gap-inpainting. The gap-corrupted sinogram was morphologically closed and subsequently converted to the DCT domain. A certain number of the largest coefficients in the DCT spectrum were identified to determine the low-frequency preservation region. The weighting factors for the remaining coefficients were determined by an exponential weighting function. The aDCT filter was constructed and applied to two digital phantoms and a simulated phantom introduced with various levels of noise. For the Shepp-Logan head phantom, the aDCT filter filled the gaps effectively. For the Jaszczak phantom, no secondary artifacts were induced after aDCT filtering. The percent mean square error and mean structure similarity of the aDCT filter were superior to those of the DCT2 filter at all noise levels. For the simulated striatal dopamine innervation study, the aDCT filter recovered the shape of the striatum and restored the striatum to reference activity ratios to the ideal value. The proposed aDCT filter can recover the missing gap data in the sinogram and improve the image quality and quantitative accuracy of PET images.

  1. Modeling astronomical adaptive optics performance with temporally filtered Wiener reconstruction of slope data.

    Science.gov (United States)

    Correia, Carlos M; Bond, Charlotte Z; Sauvage, Jean-François; Fusco, Thierry; Conan, Rodolphe; Wizinowich, Peter L

    2017-10-01

    We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results presented in Correia and Teixeira [J. Opt. Soc. Am. A31, 2763 (2014)JOAOD60740-323210.1364/JOSAA.31.002763] to the closed-loop case with predictive controllers and generalize the analytical modeling of Rigaut et al. [Proc. SPIE3353, 1038 (1998)PSISDG0277-786X10.1117/12.321649], Flicker [Technical Report (W. M. Keck Observatory, 2007)], and Jolissaint [J. Eur. Opt. Soc.5, 10055 (2010)1990-257310.2971/jeos.2010.10055]. We follow closely the developments of Ellerbroek [J. Opt. Soc. Am. A22, 310 (2005)JOAOD60740-323210.1364/JOSAA.22.000310] and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors while minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that ∼60  nm rms error reduction can be achieved with the distributed Kalman filter embodying antialiasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few λ/D separations (∼1-5λ/D) for a

  2. Development of an adaptive low-pass filtered speech test for the identification of auditory processing disorders.

    Science.gov (United States)

    O'Beirne, Greg A; McGaffin, Andrew J; Rickard, Natalie A

    2012-06-01

    One type of test commonly used to examine auditory processing disorders (APD) is the low-pass filtered speech test (LPFST), of which there are various versions. In LPFSTs, a monaural, low-redundancy speech sample is distorted by using filtering to modify its frequency content. Due to the richness of the neural pathways in the auditory system and the redundancy of acoustic information in spoken language, a normal listener is able to recognize speech even when parts of the signal are missing, whereas this ability is often impaired in listeners with APD. One limitation of the various versions of the LPFST is that they are carried out using a constant level of low-pass filtering (e.g. a fixed 1kHz corner frequency) which makes them prone to ceiling and floor effects. The purpose of this study was to counter these effects by modifying the LPFST using a computer-based adaptive procedure, and to evaluate the performance of normal-hearing participants of varying ages on the test. In this preliminary study, 33 adults and 30 children (aged 8-11 years) with no known history of listening difficulties were tested. The University of Canterbury Adaptive Speech Test (UCAST) platform was used to administer a four-alternative forced-choice adaptive test that altered a low-pass filter (LPF) to track the corner frequency at which participants correctly identified a certain percentage of the word stimuli. Findings on the University of Canterbury Adaptive Speech Test-Filtered Words (UCAST-FW) indicated a significant maturational effect. Adult participants performed significantly better on the UCAST-FW in comparison to the child participants. The UCAST-FW test was reliable over repeated administrations. An adaptive low-pass filtered speech test such as the UCAST-FW is sensitive to maturational changes in auditory processing ability. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  3. Optimal Design of the Adaptive Normalized Matched Filter Detector using Regularized Tyler Estimators

    KAUST Repository

    Kammoun, Abla

    2017-10-25

    This article addresses improvements on the design of the adaptive normalized matched filter (ANMF) for radar detection. It is well-acknowledged that the estimation of the noise-clutter covariance matrix is a fundamental step in adaptive radar detection. In this paper, we consider regularized estimation methods which force by construction the eigenvalues of the covariance estimates to be greater than a positive regularization parameter ρ. This makes them more suitable for high dimensional problems with a limited number of secondary data samples than traditional sample covariance estimates. The motivation behind this work is to understand the effect and properly set the value of ρthat improves estimate conditioning while maintaining a low estimation bias. More specifically, we consider the design of the ANMF detector for two kinds of regularized estimators, namely the regularized sample covariance matrix (RSCM), the regularized Tyler estimator (RTE). The rationale behind this choice is that the RTE is efficient in mitigating the degradation caused by the presence of impulsive noises while inducing little loss when the noise is Gaussian. Based on asymptotic results brought by recent tools from random matrix theory, we propose a design for the regularization parameter that maximizes the asymptotic detection probability under constant asymptotic false alarm rates. Provided Simulations support the efficiency of the proposed method, illustrating its gain over conventional settings of the regularization parameter.

  4. Comparison of adaptive statistical iterative and filtered back projection reconstruction techniques in quantifying coronary calcium.

    Science.gov (United States)

    Takahashi, Masahiro; Kimura, Fumiko; Umezawa, Tatsuya; Watanabe, Yusuke; Ogawa, Harumi

    2016-01-01

    Adaptive statistical iterative reconstruction (ASIR) has been used to reduce radiation dose in cardiac computed tomography. However, change of image parameters by ASIR as compared to filtered back projection (FBP) may influence quantification of coronary calcium. To investigate the influence of ASIR on calcium quantification in comparison to FBP. In 352 patients, CT images were reconstructed using FBP alone, FBP combined with ASIR 30%, 50%, 70%, and ASIR 100% based on the same raw data. Image noise, plaque density, Agatston scores and calcium volumes were compared among the techniques. Image noise, Agatston score, and calcium volume decreased significantly with ASIR compared to FBP (each P ASIR reduced Agatston score by 10.5% to 31.0%. In calcified plaques both of patients and a phantom, ASIR decreased maximum CT values and calcified plaque size. In comparison to FBP, adaptive statistical iterative reconstruction (ASIR) may significantly decrease Agatston scores and calcium volumes. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

  5. Support Vector Regression-Based Adaptive Divided Difference Filter for Nonlinear State Estimation Problems

    Directory of Open Access Journals (Sweden)

    Hongjian Wang

    2014-01-01

    Full Text Available We present a support vector regression-based adaptive divided difference filter (SVRADDF algorithm for improving the low state estimation accuracy of nonlinear systems, which are typically affected by large initial estimation errors and imprecise prior knowledge of process and measurement noises. The derivative-free SVRADDF algorithm is significantly simpler to compute than other methods and is implemented using only functional evaluations. The SVRADDF algorithm involves the use of the theoretical and actual covariance of the innovation sequence. Support vector regression (SVR is employed to generate the adaptive factor to tune the noise covariance at each sampling instant when the measurement update step executes, which improves the algorithm’s robustness. The performance of the proposed algorithm is evaluated by estimating states for (i an underwater nonmaneuvering target bearing-only tracking system and (ii maneuvering target bearing-only tracking in an air-traffic control system. The simulation results show that the proposed SVRADDF algorithm exhibits better performance when compared with a traditional DDF algorithm.

  6. Bayesian filtering in spiking neural networks: noise, adaptation, and multisensory integration.

    Science.gov (United States)

    Bobrowski, Omer; Meir, Ron; Eldar, Yonina C

    2009-05-01

    A key requirement facing organisms acting in uncertain dynamic environments is the real-time estimation and prediction of environmental states, based on which effective actions can be selected. While it is becoming evident that organisms employ exact or approximate Bayesian statistical calculations for these purposes, it is far less clear how these putative computations are implemented by neural networks in a strictly dynamic setting. In this work, we make use of rigorous mathematical results from the theory of continuous time point process filtering and show how optimal real-time state estimation and prediction may be implemented in a general setting using simple recurrent neural networks. The framework is applicable to many situations of common interest, including noisy observations, non-Poisson spike trains (incorporating adaptation), multisensory integration, and state prediction. The optimal network properties are shown to relate to the statistical structure of the environment, and the benefits of adaptation are studied and explicitly demonstrated. Finally, we recover several existing results as appropriate limits of our general setting.

  7. Planetary gearbox fault feature enhancement based on combined adaptive filter method

    Directory of Open Access Journals (Sweden)

    Shuangshu Tian

    2015-12-01

    Full Text Available The reliability of vibration signals acquired from a planetary gear system (the indispensable part of wind turbine gearbox is directly related to the accuracy of fault diagnosis. The complex operation environment leads to lots of interference signals which are included in the vibration signals. Furthermore, both multiple gears meshing with each other and the differences in transmission rout produce strong nonlinearity in the vibration signals, which makes it difficult to eliminate the noise. This article presents a combined adaptive filter method by taking a delayed signal as reference signal, the Self-Adaptive Noise Cancellation method is adopted to eliminate the white noise. In the meanwhile, by applying Gaussian function to transform the input signal into high-dimension feature-space signal, the kernel least mean square algorithm is used to cancel the nonlinear interference. Effectiveness of the method has been verified by simulation signals and test rig signals. By dealing with simulation signal, the signal-to-noise ratio can be improved around 30 dB (white noise and the amplitude of nonlinear interference signal can be depressed up to 50%. Experimental results show remarkable improvements and enhance gear fault features.

  8. Adaptive Gaussian sum squared-root cubature Kalman filter with split-merge scheme for state estimation

    Directory of Open Access Journals (Sweden)

    Liu Yu

    2014-10-01

    Full Text Available The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic systems for improvement of accuracy and consistency. An efficient new algorithm called the adaptive Gaussian-sum square-root cubature Kalman filter (AGSSCKF with a split-merge scheme is proposed. It is developed based on the squared-root extension of newly introduced cubature Kalman filter (SCKF and is built within a Gaussian-sum framework. Based on the condition that the probability density functions of process noises and initial state are denoted by a Gaussian sum using optimization method, a bank of SCKF are used as the sub-filters to estimate state of system with the corresponding weights respectively, which is adaptively updated. The new algorithm consists of an adaptive splitting and merging procedure according to a proposed split-decision model based on the nonlinearity degree of measurement. The results of two simulation scenarios (one-dimensional state estimation and bearings-only tracking show that the proposed filter demonstrates comparable performance to the particle filter with significantly reduced computational cost.

  9. Adaptive linear predictor FIR filter based on the Cyclone V FPGA with HPS to reduce narrow band RFI in AERA radio detection of cosmic rays

    Energy Technology Data Exchange (ETDEWEB)

    Szadkowski, Zbigniew [University of Lodz, Department of Physics and Applied Informatics, 90-236 Lodz, (Poland)

    2015-07-01

    We present the new approach to a filtering of radio frequency interferences (RFI) in the Auger Engineering Radio Array (AERA) which study the electromagnetic part of the Extensive Air Showers. The radio stations can observe radio signals caused by coherent emissions due to geomagnetic radiation and charge excess processes. AERA observes frequency band from 30 to 80 MHz. This range is highly contaminated by human-made RFI. In order to improve the signal to noise ratio RFI filters are used in AERA to suppress this contamination. The first kind of filter used by AERA was the Median one, based on the Fast Fourier Transform (FFT) technique. The second one, which is currently in use, is the infinite impulse response (IIR) notch filter. The proposed new filter is a finite impulse response (FIR) filter based on a linear prediction (LP). A periodic contamination hidden in a registered signal (digitized in the ADC) can be extracted and next subtracted to make signal cleaner. The FIR filter requires a calculation of n=32, 64 or even 128 coefficients (dependent on a required speed or accuracy) by solving of n linear equations with coefficients built from the covariance Toeplitz matrix. This matrix can be solved by the Levinson recursion, which is much faster than the Gauss procedure. The filter has been already tested in the real AERA radio stations on Argentinean pampas with a very successful results. The linear equations were solved either in the virtual soft-core NIOSR processor (implemented in the FPGA chip as a net of logic elements) or in the external Voipac PXA270M ARM processor. The NIOS processor is relatively slow (50 MHz internal clock), calculations performed in an external processor consume a significant amount of time for data exchange between the FPGA and the processor. Test showed a very good efficiency of the RFI suppression for stationary (long-term) contaminations. However, we observed a short-time contaminations, which could not be suppressed either by the

  10. Adaptive Control of Non-Minimum Phase Modal Systems Using Residual Mode Filters2. Parts 1 and 2

    Science.gov (United States)

    Balas, Mark J.; Frost, Susan

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. This paper will be divided into two parts. Here in Part I we will review the basic adaptive control approach and introduce the primary ideas. In Part II, we will present the RMF methodology and complete the proofs of all our results. Also, we will apply the above theoretical results to a simple flexible structure example to illustrate the behavior with and without the residual mode filter.

  11. An adaptive unscented Kalman filter-based adaptive tracking control for wheeled mobile robots with control constrains in the presence of wheel slipping

    Directory of Open Access Journals (Sweden)

    Mingyue Cui

    2016-09-01

    Full Text Available A novel control approach is proposed for trajectory tracking of a wheeled mobile robot with unknown wheels’ slipping. The longitudinal and lateral slipping are considered and processed as three time-varying parameters. The adaptive unscented Kalman filter is then designed to estimate the slipping parameters online, an adaptive adjustment of the noise covariances in the estimation process is implemented using a technique of covariance matching in the adaptive unscented Kalman filter context. Considering the practical physical constrains, a stable tracking control law for this robot system is proposed by the backstepping method. Asymptotic stability is guaranteed by Lyapunov stability theory. Control gains are determined online by applying pole placement method. Simulation and real experiment results show the effectiveness and robustness of the proposed control method.

  12. [Increase in the effectiveness of identifying peaks and feet of the photoplethysmographic pulse to be reconstructed it using adaptive filtering].

    Science.gov (United States)

    Becerra-Luna, Brayans; Martínez-Memije, Raúl; Cartas-Rosado, Raúl; Infante-Vázquez, Oscar

    To improve the identification of peaks and feet in photoplethysmographic (PPG) pulses deformed by myokinetic noise, through the implementation of a modified fingertip and applying adaptive filtering. PPG signals were recordedfrom 10 healthy volunteers using two photoplethysmography systems placed on the index finger of each hand. Recordings lasted three minutes andwere done as follows: during the first minute, both handswere at rest, and for the lasting two minutes only the left hand was allowed to make quasi-periodicmovementsin order to add myokinetic noise. Two methodologies were employed to process the signals off-line. One consisted on using an adaptive filter based onthe Least Mean Square (LMS) algorithm, and the other includeda preprocessing stage in addition to the same LMS filter. Both filtering methods were compared and the one with the lowest error was chosen to assess the improvement in the identification of peaks and feet from PPG pulses. Average percentage errorsobtained wereof 22.94% with the first filtering methodology, and 3.72% withthe second one. On identifying peaks and feet from PPG pulsesbefore filtering, error percentages obtained were of 24.26% and 48.39%, respectively, and once filtered error percentageslowered to 2.02% for peaks and 3.77% for feet. The attenuation of myokinetic noise in PPG pulses through LMS filtering, plusa preprocessing stage, allows increasingthe effectiveness onthe identification of peaks and feet from PPG pulses, which are of great importance for medical assessment. Copyright © 2016 Instituto Nacional de Cardiología Ignacio Chávez. Publicado por Masson Doyma México S.A. All rights reserved.

  13. Conductivity image enhancement in MREIT using adaptively weighted spatial averaging filter

    Science.gov (United States)

    2014-01-01

    Background In magnetic resonance electrical impedance tomography (MREIT), we reconstruct conductivity images using magnetic flux density data induced by externally injected currents. Since we extract magnetic flux density data from acquired MR phase images, the amount of measurement noise increases in regions of weak MR signals. Especially for local regions of MR signal void, there may occur excessive amounts of noise to deteriorate the quality of reconstructed conductivity images. In this paper, we propose a new conductivity image enhancement method as a postprocessing technique to improve the image quality. Methods Within a magnetic flux density image, the amount of noise varies depending on the position-dependent MR signal intensity. Using the MR magnitude image which is always available in MREIT, we estimate noise levels of measured magnetic flux density data in local regions. Based on the noise estimates, we adjust the window size and weights of a spatial averaging filter, which is applied to reconstructed conductivity images. Without relying on a partial differential equation, the new method is fast and can be easily implemented. Results Applying the novel conductivity image enhancement method to experimental data, we could improve the image quality to better distinguish local regions with different conductivity contrasts. From phantom experiments, the estimated conductivity values had 80% less variations inside regions of homogeneous objects. Reconstructed conductivity images from upper and lower abdominal regions of animals showed much less artifacts in local regions of weak MR signals. Conclusion We developed the fast and simple method to enhance the conductivity image quality by adaptively adjusting the weights and window size of the spatial averaging filter using MR magnitude images. Since the new method is implemented as a postprocessing step, we suggest adopting it without or with other preprocessing methods for application studies where conductivity

  14. A family of variable step-size affine projection adaptive filter algorithms using statistics of channel impulse response

    Science.gov (United States)

    Shams Esfand Abadi, Mohammad; AbbasZadeh Arani, Seyed Ali Asghar

    2011-12-01

    This paper extends the recently introduced variable step-size (VSS) approach to the family of adaptive filter algorithms. This method uses prior knowledge of the channel impulse response statistic. Accordingly, optimal step-size vector is obtained by minimizing the mean-square deviation (MSD). The presented algorithms are the VSS affine projection algorithm (VSS-APA), the VSS selective partial update NLMS (VSS-SPU-NLMS), the VSS-SPU-APA, and the VSS selective regressor APA (VSS-SR-APA). In VSS-SPU adaptive algorithms the filter coefficients are partially updated which reduce the computational complexity. In VSS-SR-APA, the optimal selection of input regressors is performed during the adaptation. The presented algorithms have good convergence speed, low steady state mean square error (MSE), and low computational complexity features. We demonstrate the good performance of the proposed algorithms through several simulations in system identification scenario.

  15. Evolutionary scenarios of Notch proteins.

    Science.gov (United States)

    Theodosiou, Athina; Arhondakis, Stilianos; Baumann, Marc; Kossida, Sophia

    2009-07-01

    Notch is a highly conserved family of transmembrane receptors and transcription factors that are key players in several developmental processes. In this study, we identified novel Notch sequences from various species covering from worm to human and conducted a comprehensive phylogenetic analysis in order to confirm and extend the evolutionary history of Notch. Our findings confirm an independent duplication event in Caenorhabditis elegans resulting in two Notch genes and show that the vertebrate Notch genes resulted from two duplication events, both of which occurred before the divergence of teleosts and tetrapoda. Furthermore, we demonstrate that the vertebrate Notch2 group is phylogenetically closer to Notch3 and that Notch2 appeared at the first round of vertebrate duplication events. Moreover, there is evidence that the two Notch1 genes in fish, appeared by a recent duplication of Notch1 in teleost after the divergence of teleost and tetrapoda. Whether this is from ancient whole genome duplication (WGD) or gene duplication remains to be elucidated. The fourth group of Notch (Notch4) was found only in mammals. We suggest two possible scenarios for the origin of the Notch4 subfamily: 1) Notch4 appeared at the time of the two WGDs in the early chordate but has been maintained only in the mammalian lineage and was lost in the other lineages, 2) a recent independent duplication event took place in the mammalian lineage. The increase of the sequencing data from Xenopus tropicalis, Gallus gallus genome projects and of other avian and reptile genomes will shed more light on this event. Nevertheless, the great divergence of Notch4, from the other three Notch genes, suggests a rapid divergence raising questions about the functional implication of this event. In addition, comparison of the organization of Notch syntenic genes among species supports the coordinated rearrangements during evolution for Ntch, PBX, and BRD families that may lead to possible functional

  16. Notch filters for port-Hamiltonian systems

    NARCIS (Netherlands)

    Dirksz, Daniel; Scherpen, Jacquelien M.A.; van der Schaft, Abraham; Steinbuch, M.

    2012-01-01

    Network modeling of lumped-parameter physical systems naturally leads to a geometrically defined class of systems, i.e., port-Hamiltonian (PH) systems [4, 6]. The PH modeling framework describes a large class of (nonlinear) systems including passive mechanical systems, electrical systems,

  17. Notch Filters for Port-Hamiltonian Systems

    NARCIS (Netherlands)

    Dirksz, Danny; Scherpen, Jacquelien M.A.; van der Schaft, Abraham J.; Steinbuch, Maarten

    Many powerful tools exist for control design in the frequency domain, but are theoretically only justified for linear systems. On the other hand, nonlinear control deals with control design methodologies that are theoretically justified for a larger and more realistic class of systems, but primarily

  18. Low-dose MDCT urography: feasibility study of low-tube-voltage technique and adaptive noise reduction filter.

    Science.gov (United States)

    Yanaga, Yumi; Awai, Kazuo; Funama, Yoshinori; Nakaura, Takeshi; Hirai, Toshinori; Roux, Sebastien; Yamashita, Yasuyuki

    2009-09-01

    The purpose of this study was to investigate the feasibility of performance of MDCT urography with low tube voltage and an adaptive noise reduction filter. Thirty-one patients underwent excretory phase (300 seconds after administration of 100 mL of iopamidol) 40-MDCT of the urinary tract at 120 and 80 kVp. The 80-kVp images were postprocessed with an adaptive noise reduction filter. Using a 3-point scale for homogeneity of the urinary tract and sharpness of contour, streak artifacts, and overall image quality, two radiologists evaluated coronal multiplanar reconstruction images generated from 120-kVp, unfiltered 80-kVp, and filtered 80-kVp images. Attenuation values of the abdominal aorta, renal pelvis, renal cortex, psoas muscle, vertebral body, and retroperitoneal fat and image noise of the psoas muscle were measured. The effective radiation dose was estimated for each patient. At visual evaluation of images of the upper urinary tract, the quality of filtered 80-kVp images was comparable with that of 120-kVp images. At evaluation of images of the lower urinary tract, however, filtered 80-kVp images were of inferior quality. Except for those of fat tissue, attenuation values were significantly higher on 80-kVp than on 120-kVp images (paired Student's t test, p urography is feasible with a low-tube-voltage technique and an adaptive noise reduction filter. The technique allows reduction in radiation dose without marked degradation of image quality and can be used in clinical assessment of the renal collecting system and upper ureter. For evaluation of the pelvic ureter and urinary bladder, however, image quality is not sufficient, and a compensatory increase in tube current may be necessary.

  19. Adaptive Fusion Design Using Multiscale Unscented Kalman Filter Approach for Multisensor Data Fusion

    Directory of Open Access Journals (Sweden)

    Huadong Wang

    2015-01-01

    Full Text Available In order to improve the reliability of measurement data, the multisensor data fusion technology has progressed greatly in improving the accuracy of measurement data. This paper utilizes the real-time, recursive, and optimal estimation characteristics of unscented Kalman filter (UKF, as well as the unique advantages of multiscale wavelet transform decomposition in data analysis to effectively integrate observational data from multiple sensors. A new multiscale UKF-based multisensor data fusion algorithm is proposed by combining the UKF with multiscale signal analysis. Firstly, model-based UKF is introduced into the multiple sensors, and then the model is decomposed at multiple scales onto the coarse scale with wavelets. Next, signals decomposed from fine to coarse scales are adjusted using the denoised observational data from corresponding sensors and reconstructed with wavelets to obtain the fused signals. Finally, the processed data are fused using adaptive weighted fusion algorithm. Comparison of simulation and experimental results shows that the proposed method can effectively improve the antijamming capability of the measurement system and ensure the reliability and accuracy of sensor measurement system compared to the use of data fusion algorithm alone.

  20. Flexible Riser Monitoring Using Hybrid Magnetic/Optical Strain Gage Techniques through RLS Adaptive Filtering

    Directory of Open Access Journals (Sweden)

    Pipa Daniel

    2010-01-01

    Full Text Available Flexible riser is a class of flexible pipes which is used to connect subsea pipelines to floating offshore installations, such as FPSOs (floating production/storage/off-loading unit and SS (semisubmersible platforms, in oil and gas production. Flexible risers are multilayered pipes typically comprising an inner flexible metal carcass surrounded by polymer layers and spiral wound steel ligaments, also referred to as armor wires. Since these armor wires are made of steel, their magnetic properties are sensitive to the stress they are subjected to. By measuring their magnetic properties in a nonintrusive manner, it is possible to compare the stress in the armor wires, thus allowing the identification of damaged ones. However, one encounters several sources of noise when measuring electromagnetic properties contactlessly, such as movement between specimen and probe, and magnetic noise. This paper describes the development of a new technique for automatic monitoring of armor layers of flexible risers. The proposed approach aims to minimize these current uncertainties by combining electromagnetic measurements with optical strain gage data through a recursive least squares (RLSs adaptive filter.

  1. Gearbox Fault Features Extraction Using Vibration Measurements and Novel Adaptive Filtering Scheme

    Directory of Open Access Journals (Sweden)

    Ghalib R. Ibrahim

    2012-01-01

    Full Text Available Vibration signals measured from a gearbox are complex multicomponent signals, generated by tooth meshing, gear shaft rotation, gearbox resonance vibration signatures, and a substantial amount of noise. This paper presents a novel scheme for extracting gearbox fault features using adaptive filtering techniques for enhancing condition features, meshing frequency sidebands. A modified least mean square (LMS algorithm is examined and validated using only one accelerometer, instead of using two accelerometers in traditional arrangement, as the main signal and a desired signal is artificially generated from the measured shaft speed and gear meshing frequencies. The proposed scheme is applied to a signal simulated from gearbox frequencies with a numerous values of step size. Findings confirm that 10−5 step size invariably produces more accurate results and there has been a substantial improvement in signal clarity (better signal-to-noise ratio, which makes meshing frequency sidebands more discernible. The developed scheme is validated via a number of experiments carried out using two-stage helical gearbox for a healthy pair of gears and a pair suffering from a tooth breakage with severity fault 1 (25% tooth removal and fault 2 (50% tooth removal under loads (0%, and 80% of the total load. The experimental results show remarkable improvements and enhance gear condition features. This paper illustrates that the new approach offers a more effective way to detect early faults.

  2. RLS adaptive filtering for physiological interference reduction in NIRS brain activity measurement: a Monte Carlo study.

    Science.gov (United States)

    Zhang, Y; Sun, J W; Rolfe, P

    2012-06-01

    The non-invasive measurement of cerebral functional haemodynamics using near-infrared spectroscopy (NIRS) instruments is often affected by physiological interference. The suppression of this interference is crucial for reliable recovery of brain activity measurements because it can significantly affect the signal quality. In this study, we present a recursive least-squares (RLS) algorithm for adaptive filtering to reduce the magnitude of the physiological interference component. To evaluate it, we implemented Monte Carlo simulations based on a five-layer slab model of a human adult head with a multidistance source-detector arrangement, of a short pair and a long pair, for NIRS measurement. We derived measurements by adopting different interoptode distances, which is relevant to the process of optimizing the NIRS probe configuration. Both RLS and least mean squares (LMS) algorithms were used to attempt the removal of physiological interference. The results suggest that the RLS algorithm is more capable of minimizing the effect of physiological interference due to its advantages of faster convergence and smaller mean squared error (MSE). The influence of superficial layer thickness on the performance of the RLS algorithm was also investigated. We found that the near-detector position is an important variable in minimizing the MSE and a short source-detector separation less than 9 mm is robust to superficial layer thickness variation.

  3. Facilitating joint chaos and fractal analysis of biosignals through nonlinear adaptive filtering.

    Directory of Open Access Journals (Sweden)

    Jianbo Gao

    Full Text Available BACKGROUND: Chaos and random fractal theories are among the most important for fully characterizing nonlinear dynamics of complicated multiscale biosignals. Chaos analysis requires that signals be relatively noise-free and stationary, while fractal analysis demands signals to be non-rhythmic and scale-free. METHODOLOGY/PRINCIPAL FINDINGS: To facilitate joint chaos and fractal analysis of biosignals, we present an adaptive algorithm, which: (1 can readily remove nonstationarities from the signal, (2 can more effectively reduce noise in the signals than linear filters, wavelet denoising, and chaos-based noise reduction techniques; (3 can readily decompose a multiscale biosignal into a series of intrinsically bandlimited functions; and (4 offers a new formulation of fractal and multifractal analysis that is better than existing methods when a biosignal contains a strong oscillatory component. CONCLUSIONS: The presented approach is a valuable, versatile tool for the analysis of various types of biological signals. Its effectiveness is demonstrated by offering new important insights into brainwave dynamics and the very high accuracy in automatically detecting epileptic seizures from EEG signals.

  4. Fundamental Active Current Adaptive Linear Neural Networks for Photovoltaic Shunt Active Power Filters

    Directory of Open Access Journals (Sweden)

    Muhammad Ammirrul Atiqi Mohd Zainuri

    2016-05-01

    Full Text Available This paper presents improvement of a harmonics extraction algorithm, known as the fundamental active current (FAC adaptive linear element (ADALINE neural network with the integration of photovoltaic (PV to shunt active power filters (SAPFs as active current source. Active PV injection in SAPFs should reduce dependency on grid supply current to supply the system. In addition, with a better and faster harmonics extraction algorithm, the SAPF should perform well, especially under dynamic PV and load conditions. The role of the actual injection current from SAPF after connecting PVs will be evaluated, and the better effect of using FAC ADALINE will be confirmed. The proposed SAPF was simulated and evaluated in MATLAB/Simulink first. Then, an experimental laboratory prototype was also developed to be tested with a PV simulator (CHROMA 62100H-600S, and the algorithm was implemented using a TMS320F28335 Digital Signal Processor (DSP. From simulation and experimental results, significant improvements in terms of total harmonic distortion (THD, time response and reduction of source power from grid have successfully been verified and achieved.

  5. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  6. Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

    Science.gov (United States)

    Kesrarat, Darun; Patanavijit, Vorapoj

    2017-02-01

    In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow's MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).

  7. Stress concentration at notches

    CERN Document Server

    Savruk, Mykhaylo P

    2017-01-01

    This book compiles solutions of linear theory of elasticity problems for isotropic and anisotropic bodies with sharp and rounded notches. It contains an overview of established and recent achievements, and presents the authors’ original solutions in the field considered with extensive discussion. The volume demonstrates through numerous, useful examples the effectiveness of singular integral equations for obtaining exact solutions of boundary problems of the theory of elasticity for bodies with cracks and notches. Incorporating analytical and numerical solutions of the problems of stress concentrations in solid bodies with crack-like defects, this volume is ideal for scientists and PhD students dealing with the problems of theory of elasticity and fracture mechanics. Stands as a modern and extensive compendium of solutions to the problems of linear theory of elasticity of isotropic and anisotropic bodies with sharp and rounded notches; Adopts a highly reader-friendly layout of tables, charts, approximation ...

  8. A Compact Printed Quadruple Band-Notched UWB Antenna

    Directory of Open Access Journals (Sweden)

    Xiaoyin Li

    2013-01-01

    Full Text Available A novel compact coplanar waveguide- (CPW- fed ultrawideband (UWB printed planar volcano-smoke antenna (PVSA with four band-notches for various wireless applications is proposed and demonstrated. The low-profile antenna consists of a C-shaped parasitic strip to generate a notched band at 8.01~8.55 GHz for the ITU band, two C-shaped slots, and an inverted U-shaped slot etched in the radiator patch to create three notched bands at 5.15~5.35 GHz, 5.75~5.85 GHz, and 7.25~7.75 GHz for filtering the WLAN and X-band satellite signals. Simulated and measured results both confirm that the proposed antenna has a broad bandwidth of 3.1~12 GHz with VSWR < 2 and good omnidirectional radiation patterns with four notched-bands.

  9. An Enhanced UWB-Based Range/GPS Cooperative Positioning Approach Using Adaptive Variational Bayesian Cubature Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Feng Shen

    2015-01-01

    Full Text Available Precise position awareness is a fundamental requirement for advanced applications of emerging intelligent transportation systems, such as collision warning and speed advisory system. However, the achievable level of positioning accuracy using global navigation satellite systems does not meet the requirements of these applications. Fortunately, cooperative positioning (CP techniques can improve the performance of positioning in a vehicular ad hoc network (VANET through sharing the positions between vehicles. In this paper, a novel enhanced CP technique is presented by combining additional range-ultra-wide bandwidth- (UWB- based measurements. Furthermore, an adaptive variational Bayesian cubature Kalman filtering (AVBCKF algorithm is proposed and used in the enhanced CP method, which can add robustness to the time-variant measurement noise. Based on analytical and experimental results, the proposed AVBCKF-based CP method outperforms the cubature Kalman filtering- (CKF- based CP method and extended Kalman filtering- (EKF- based CP method.

  10. Fast, accurate, and robust frequency offset estimation based on modified adaptive Kalman filter in coherent optical communication system

    Science.gov (United States)

    Yang, Yanfu; Xiang, Qian; Zhang, Qun; Zhou, Zhongqing; Jiang, Wen; He, Qianwen; Yao, Yong

    2017-09-01

    We propose a joint estimation scheme for fast, accurate, and robust frequency offset (FO) estimation along with phase estimation based on modified adaptive Kalman filter (MAKF). The scheme consists of three key modules: extend Kalman filter (EKF), lock detector, and FO cycle slip recovery. The EKF module estimates time-varying phase induced by both FO and laser phase noise. The lock detector module makes decision between acquisition mode and tracking mode and consequently sets the EKF tuning parameter in an adaptive manner. The third module can detect possible cycle slip in the case of large FO and make proper correction. Based on the simulation and experimental results, the proposed MAKF has shown excellent estimation performance featuring high accuracy, fast convergence, as well as the capability of cycle slip recovery.

  11. Adaptive Two-Stage Extended Kalman Filter Theory in Application of Sensorless Control for Permanent Magnet Synchronous Motor

    Directory of Open Access Journals (Sweden)

    Boyu Yi

    2013-01-01

    Full Text Available Extended Kalman filters (EKF have been widely used for sensorless field oriented control (FOC in permanent magnet synchronous motor (PMSM. The first key problem associated with EKF is that the estimator requires all the plant dynamics and noise processes are exactly known. To compensate inaccurate model information and improve tracking ability, adaptive fading extended Kalman filtering algorithms have been proposed for the nonlinear system. The second key problem is that the EKF suffers from computational burden and numerical problems when state dimension is large. The two-stage extended Kalman filter (TSEKF with respect to this problem has been extensively studied in the past. Combining the advantages of both AFEKF and TSEKF, this paper presents an adaptive two-stage extended Kalman filter (ATEKF for closed-loop position and speed estimation of a PMSM to achieve sensorless operation. Experimental results demonstrate that the proposed ATEKF algorithm for PMSMs has strong robustness against model uncertainties and very good real-time state tracking ability.

  12. Comparison of adaptive statistical iterative and filtered back projection reconstruction techniques in brain CT

    Energy Technology Data Exchange (ETDEWEB)

    Ren, Qingguo, E-mail: renqg83@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Dewan, Sheilesh Kumar, E-mail: sheilesh_d1@hotmail.com [Department of Geriatrics, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Li, Ming, E-mail: minli77@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Li, Jianying, E-mail: Jianying.Li@med.ge.com [CT Imaging Research Center, GE Healthcare China, Beijing (China); Mao, Dingbiao, E-mail: maodingbiao74@163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China); Wang, Zhenglei, E-mail: Williswang_doc@yahoo.com.cn [Department of Radiology, Shanghai Electricity Hospital, Shanghai 200050 (China); Hua, Yanqing, E-mail: cjr.huayanqing@vip.163.com [Department of Radiology, Hua Dong Hospital of Fudan University, Shanghai 200040 (China)

    2012-10-15

    Purpose: To compare image quality and visualization of normal structures and lesions in brain computed tomography (CT) with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP) reconstruction techniques in different X-ray tube current–time products. Materials and methods: In this IRB-approved prospective study, forty patients (nineteen men, twenty-one women; mean age 69.5 ± 11.2 years) received brain scan at different tube current–time products (300 and 200 mAs) in 64-section multi-detector CT (GE, Discovery CT750 HD). Images were reconstructed with FBP and four levels of ASIR-FBP blending. Two radiologists (please note that our hospital is renowned for its geriatric medicine department, and these two radiologists are more experienced in chronic cerebral vascular disease than in neoplastic disease, so this research did not contain cerebral tumors but as a discussion) assessed all the reconstructed images for visibility of normal structures, lesion conspicuity, image contrast and diagnostic confidence in a blinded and randomized manner. Volume CT dose index (CTDI{sub vol}) and dose-length product (DLP) were recorded. All the data were analyzed by using SPSS 13.0 statistical analysis software. Results: There was no statistically significant difference between the image qualities at 200 mAs with 50% ASIR blending technique and 300 mAs with FBP technique (p > .05). While between the image qualities at 200 mAs with FBP and 300 mAs with FBP technique a statistically significant difference (p < .05) was found. Conclusion: ASIR provided same image quality and diagnostic ability in brain imaging with greater than 30% dose reduction compared with FBP reconstruction technique.

  13. Dental drill noise reduction using a combination of active noise control, passive noise control and adaptive filtering

    OpenAIRE

    Kaymak, E; Atherton, MA; Rotter, K; Millar, B

    2007-01-01

    Dental drills produce a characteristic high frequency, narrow band noise that is uncomfortable for patients and is also known to be harmful to dentists under prolonged exposure. It is therefore desirable to protect the patient and dentist whilst allowing two-way communication. A solution is to use a combination of the three main noise control methods, namely, Passive Noise Control (PNC), Adaptive Filtering (AF) and Active Noise Control (ANC). This paper discusses the application of the three ...

  14. Adaptive filtering of GOCE-derived gravity gradients of the disturbing potential in the context of the space-wise approach

    Science.gov (United States)

    Piretzidis, Dimitrios; Sideris, Michael G.

    2017-09-01

    Filtering and signal processing techniques have been widely used in the processing of satellite gravity observations to reduce measurement noise and correlation errors. The parameters and types of filters used depend on the statistical and spectral properties of the signal under investigation. Filtering is usually applied in a non-real-time environment. The present work focuses on the implementation of an adaptive filtering technique to process satellite gravity gradiometry data for gravity field modeling. Adaptive filtering algorithms are commonly used in communication systems, noise and echo cancellation, and biomedical applications. Two independent studies have been performed to introduce adaptive signal processing techniques and test the performance of the least mean-squared (LMS) adaptive algorithm for filtering satellite measurements obtained by the gravity field and steady-state ocean circulation explorer (GOCE) mission. In the first study, a Monte Carlo simulation is performed in order to gain insights about the implementation of the LMS algorithm on data with spectral behavior close to that of real GOCE data. In the second study, the LMS algorithm is implemented on real GOCE data. Experiments are also performed to determine suitable filtering parameters. Only the four accurate components of the full GOCE gravity gradient tensor of the disturbing potential are used. The characteristics of the filtered gravity gradients are examined in the time and spectral domain. The obtained filtered GOCE gravity gradients show an agreement of 63-84 mEötvös (depending on the gravity gradient component), in terms of RMS error, when compared to the gravity gradients derived from the EGM2008 geopotential model. Spectral-domain analysis of the filtered gradients shows that the adaptive filters slightly suppress frequencies in the bandwidth of approximately 10-30 mHz. The limitations of the adaptive LMS algorithm are also discussed. The tested filtering algorithm can be

  15. Noise Reduction and Gap Filling of fAPAR Time Series Using an Adapted Local Regression Filter

    Directory of Open Access Journals (Sweden)

    Álvaro Moreno

    2014-08-01

    Full Text Available Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted local regression filter (LOESS and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG, smoothing spline (SSP, Interpolation for Data Reconstruction (IDR and adaptive Savitzky-Golay (ASG. This paper evaluates the main advantages and drawbacks of the considered techniques. The results have shown that ASG and the adapted LOESS perform better in recovering fAPAR time series over multiple controlled noisy scenarios. Both methods can robustly reconstruct the fAPAR trajectories, reducing the noise up to 80% in the worst simulation scenario, which might be attributed to the quality control (QC MODIS information incorporated into these filtering algorithms, their flexibility and adaptation to the upper envelope. The adapted LOESS is particularly resistant to outliers. This method clearly outperforms the other considered methods to deal with the high presence of gaps and noise in satellite data records. The low RMSE and biases obtained with the LOESS method (|rMBE| < 8%; rRMSE < 20% reveals an optimal reconstruction even in most extreme situations with long seasonal gaps. An example of application of the LOESS method to fill in invalid values in real MODIS images presenting persistent cloud and snow coverage is also shown. The LOESS approach is recommended in most remote sensing applications, such as gap-filling, cloud-replacement, and observing temporal

  16. Compact tunable microwave filter using retroreflective acousto-optic filtering and delay controls.

    Science.gov (United States)

    Riza, Nabeel A; Ghauri, Farzan N

    2007-03-01

    Programmable broadband rf filters are demonstrated using a compact retroreflective optical design with an acousto-optic tunable filter and a chirped fiber Bragg grating. This design enables fast 34 micros domain analog-mode control of rf filter time delays and weights. Two proof-of-concept filters are demonstrated including a two-tap notch filter with >35 dB notch depth and a four-tap bandpass filter. Both filters have 2-8 GHz tunability and a 34 micros reset time.

  17. Inland notches micromorphology

    Science.gov (United States)

    Brook, Anna; Ben-Binyamin, Atzmon; Shtober-Zisu, Nurit

    2017-04-01

    Inland notches are well known phenomenon in Israel and can be found mostly along the mountainous backbone, developed in hard limestone or dolomite rocks within the Mediterranean climate zone and up to the desert fringe. LiDAR technology presents an opportunity to study the fine scale rock surface within the notch and its texture patterns. De-trending of the LiDAR reconstructed DEM to a local trend, surface roughness, was achieved by fitting a normalized surface to all measured ground points within the roughness neighborhood. Micro-topography plays an important role for modelling geomorphology dynamics, resulting in improved estimates for micro stream lines network and topographic erosion as well as mineral accumulation or deposition. Clearly, dissolution occurs whenever rock and solvent meet; thus water and moisture's crucial role in the decay of carbonate rocks results in texture and roughness variability. Study aims is to generate high resolution normalized DEM models using a terrestrial LiDAR, redefining the texture and roughness within the notch while assessing weathering processes caused by water. Plan curvature is the second derivative of slope taken perpendicular to its direction. It influences convergence and divergence of flow and it emphasizes the ridges and valleys across the surface. Concaved classified areas were tested against all planar curvature areas to distinguish them as unique areas based on their texture co-occurrence measures (GLCM). Overall negative curvature pixels show poor separability, in both TD and JM separation tests, while classes of curvature degree describe a positive trend showing medium and high concavity as unique areas. Study aims to link classified areas as the basic micro infrastructure for water flow, potential runoff flow and further accumulation of minerals. On the other hand, positive values of Plan curvature present the convexity of rock surface to imply diverging flow, thus describing the watershed line within the micro

  18. Adaptive angular-velocity Vold-Kalman filter order tracking - Theoretical basis, numerical implementation and parameter investigation

    Science.gov (United States)

    Pan, M.-Ch.; Chu, W.-Ch.; Le, Duc-Do

    2016-12-01

    The paper presents an alternative Vold-Kalman filter order tracking (VKF_OT) method, i.e. adaptive angular-velocity VKF_OT technique, to extract and characterize order components in an adaptive manner for the condition monitoring and fault diagnosis of rotary machinery. The order/spectral waveforms to be tracked can be recursively solved by using Kalman filter based on the one-step state prediction. The paper comprises theoretical derivation of computation scheme, numerical implementation, and parameter investigation. Comparisons of the adaptive VKF_OT scheme with two other ones are performed through processing synthetic signals of designated order components. Processing parameters such as the weighting factor and the correlation matrix of process noise, and data conditions like the sampling frequency, which influence tracking behavior, are explored. The merits such as adaptive processing nature and computation efficiency brought by the proposed scheme are addressed although the computation was performed in off-line conditions. The proposed scheme can simultaneously extract multiple spectral components, and effectively decouple close and crossing orders associated with multi-axial reference rotating speeds.

  19. Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques.

    Science.gov (United States)

    Singh, Sarabjeet; Kalra, Mannudeep K; Hsieh, Jiang; Licato, Paul E; Do, Synho; Pien, Homer H; Blake, Michael A

    2010-11-01

    To compare image quality and lesion conspicuity on abdominal computed tomographic (CT) images acquired with different x-ray tube current-time products (50-200 mAs) and reconstructed with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP) techniques. Twenty-two patients (mean age, 60.1 years ± 7.3 [standard deviation]; age range, 52.8-67.4 years; mean weight, 78.9 kg ± 18.3; 12 men, 10 women) gave informed consent for this prospective institutional review board-approved and HIPAA-compliant study, which involved the acquisition of four additional image series at multidetector CT. Images were acquired at different tube current-time products (200, 150, 100, and 50 mAs) and encompassed an abdominal lesion over a 10-cm scan length. Images were reconstructed separately with FBP and with three levels of ASIR-FBP blending. Two radiologists reviewed FBP and ASIR images for image quality in a blinded and randomized manner. Volume CT dose index (CTDI(vol)), dose-length product, patient weight, objective noise, and CT numbers were recorded. Data were analyzed by using analysis of variance and the Wilcoxon signed rank test. CTDI(vol) values were 16.8, 12.6, 8.4, and 4.2 mGy for 200, 150, 100, and 50 mAs, respectively (P 22 image series acquired at 4.2 mGy with 70% ASIR. Lesion conspicuity was significantly better at 4.2 mGy on ASIR than on FBP images (observed P < .044), and overall diagnostic confidence changed from unacceptable on FBP to acceptable on ASIR images. ASIR lowers noise and improves diagnostic confidence in and conspicuity of subtle abdominal lesions at 8.4 mGy when images are reconstructed with 30% ASIR blending and at 4.2 mGy in patients weighing 90 kg or less when images are reconstructed with 50% or 70% ASIR blending. © RSNA, 2010.

  20. Radiation dose reduction for chest CT with non-linear adaptive filters.

    Science.gov (United States)

    Singh, Sarabjeet; Digumarthy, Subba R; Back, Anni; Shepard, Jo-anne O; Kalra, Mannudeep K

    2013-03-01

    CT radiation dose reduction results in increased noise or graininess of images which affects the diagnostic information. One of the approaches to lower radiation exposure to patients is to reduce image noise with the use of image processing software in low radiation dose images. To assess image quality and accuracy of non-linear adaptive filters (NLAF) at low dose chest CT. In an IRB approved prospective study, 24 patients (mean age, 63 ± 7.3 years; M:F ratio, 11:13) gave informed consent for acquisition of four additional chest CT image series at 150, 110, 75, and 40 mAs (baseline image series) on a 64-slice MDCT over an identical 10-cm length. NLAF was used to process three low dose (110, 75, and 40 mAs) image series (postprocessed image series). Two radiologists reviewed baseline and postprocessed images in a blinded manner for image quality. Objective noise, CT attenuation values, patient weight, transverse diameters, CTDIvol, and DLP were recorded. Statistical analysis was performed using parametric and non-parametric tests for comparing postprocessed and baseline images. No lesions were missed on baseline or postprocessed CT images (n = 80 lesions, 73 lesions hardening artifacts not affecting diagnostic decision-making (14/22) in both baseline and postprocessed image series. Diagnostic confidence for chest CT was improved to fully confident in postprocessed images at 40 mAs. Compared to baseline images, postprocessing reduced objective noise by 26% (14.2 ± 4.7/19.2 ± 6.4), 31.5% (15.2 ± 4.7/22.2 ± 5.7), and 41.5% (16.9 ± 6/28.9 ± 10.2) at 110 mAs, 75 mAs, and 40 mAs tube current-time product levels. Applications of NLAF can help reduce tube current down to 40 mAs for chest CT while maintaining lesion conspicuity and image quality.

  1. Adaptive Filtering for FSCW Signal-to-noise Ratio Enhancement of SAW Interrogation Units

    Directory of Open Access Journals (Sweden)

    Díaz Luis

    2016-01-01

    Full Text Available A digital filter that improves the signal-to-noise ratio of the response of a FSCW (Frequency Stepped Continuous Wave scheme is presented. An improvement in signal-to-noise ratio represents an enhanced readout distance. This work considers this architecture as an interrogation unit for SAW tags with time and phase encoding. The parameters of the proposed digital filter, which is a non-linear edge preserving filter, were studied and tested for this specific application. An improvement of around 20dB in the SNR level was achieved. This filter preserves the phase of the signal at the time position of the reflectors, which is critical for correct identification of the code in phase encoding schemes.

  2. Notch signaling in the pancreas: patterning and cell fate specification.

    Science.gov (United States)

    Afelik, Solomon; Jensen, Jan

    2013-07-01

    Notch signaling is an evolutionarily conserved mechanism adapted to control binary fate decisions. The first evidence of Notch in pancreatic development focused on its critical role in controlling endocrine fate decisions. Since then, we have come to understand that this signaling system operates iteratively in the pancreas, and is not limited to the control of endocrine fate decision. Notch appears to play a role in early organ development, then during organ domain patterning, and only during a final refinement process, in the control of terminal cell fates. In so doing, Notch receptors and their ligands are under the influence of a wealth of genetic components that together help orchestrate the building of a complex, glandular organ. Copyright © 2012 Wiley Periodicals, Inc.

  3. An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles

    Science.gov (United States)

    Liu, Yahui; Fan, Xiaoqian; Lv, Chen; Wu, Jian; Li, Liang; Ding, Dawei

    2018-02-01

    Information fusion method of INS/GPS navigation system based on filtering technology is a research focus at present. In order to improve the precision of navigation information, a navigation technology based on Adaptive Kalman Filter with attenuation factor is proposed to restrain noise in this paper. The algorithm continuously updates the measurement noise variance and processes noise variance of the system by collecting the estimated and measured values, and this method can suppress white noise. Because a measured value closer to the current time would more accurately reflect the characteristics of the noise, an attenuation factor is introduced to increase the weight of the current value, in order to deal with the noise variance caused by environment disturbance. To validate the effectiveness of the proposed algorithm, a series of road tests are carried out in urban environment. The GPS and IMU data of the experiments were collected and processed by dSPACE and MATLAB/Simulink. Based on the test results, the accuracy of the proposed algorithm is 20% higher than that of a traditional Adaptive Kalman Filter. It also shows that the precision of the integrated navigation can be improved due to the reduction of the influence of environment noise.

  4. NOTCH1, NOTCH3, NOTCH4, and JAG2 protein levels in human endometrial cancer.

    Science.gov (United States)

    Sasnauskienė, Aušra; Jonušienė, Violeta; Krikštaponienė, Aurelija; Butkytė, Stasė; Dabkevičienė, Daiva; Kanopienė, Daiva; Kazbarienė, Birutė; Didžiapetrienė, Janina

    2014-01-01

    Notch signaling is a conserved developmental pathway, which plays an important role in the regulation of cell proliferation, differentiation and death. Deregulation of Notch pathway has been connected with the carcinogenesis in a variety of cancers. The aim of this study was to investigate the level of the Notch signaling pathway proteins (NOTCH1, 3, 4 and JAG2) in the samples from human endometrial cancer. The amount of the Notch receptors NOTCH1, 3, 4 and ligand JAG2 protein was determined by Western blot analysis in the samples from stage I endometrial cancer and adjacent nontumor endometrial tissue of 22 patients. The level of NOTCH4 receptor was 1.7 times lower in stage I endometrial cancer as compared with the healthy tissue of the same patients (P=0.04). The protein level of ligand JAG2 was significantly reduced by 2.5 times in stage IB endometrial adenocarcinoma samples (P=0.01). It was reduced in the majority of stage IB adenocarcinomas. There were no significant changes in the protein amount of NOTCH1 and NOTCH3 receptors comparing stage I endometrial adenocarcinoma and healthy tissues. The reduced amount of NOTCH4 and JAG2 proteins and the decreased level of mRNA coding Notch proteins, as reported in our previous studies, supports the notion that Notch pathway has rather tumor-suppressive than oncogenic role in human endometrial cancer cells. It suggests that Notch pathway activation is a potential therapeutic target. Copyright © 2014 Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  5. Wireless rake-receiver using adaptive filter with a family of partial update algorithms in noise cancellation applications

    Science.gov (United States)

    Fayadh, Rashid A.; Malek, F.; Fadhil, Hilal A.; Aldhaibani, Jaafar A.; Salman, M. K.; Abdullah, Farah Salwani

    2015-05-01

    For high data rate propagation in wireless ultra-wideband (UWB) communication systems, the inter-symbol interference (ISI), multiple-access interference (MAI), and multiple-users interference (MUI) are influencing the performance of the wireless systems. In this paper, the rake-receiver was presented with the spread signal by direct sequence spread spectrum (DS-SS) technique. The adaptive rake-receiver structure was shown with adjusting the receiver tap weights using least mean squares (LMS), normalized least mean squares (NLMS), and affine projection algorithms (APA) to support the weak signals by noise cancellation and mitigate the interferences. To minimize the data convergence speed and to reduce the computational complexity by the previous algorithms, a well-known approach of partial-updates (PU) adaptive filters were employed with algorithms, such as sequential-partial, periodic-partial, M-max-partial, and selective-partial updates (SPU) in the proposed system. The simulation results of bit error rate (BER) versus signal-to-noise ratio (SNR) are illustrated to show the performance of partial-update algorithms that have nearly comparable performance with the full update adaptive filters. Furthermore, the SPU-partial has closed performance to the full-NLMS and full-APA while the M-max-partial has closed performance to the full-LMS updates algorithms.

  6. A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring.

    Science.gov (United States)

    Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

    2017-04-18

    This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio-SNR, Root Mean Square Error-RMSE, Sensitivity-S+, and Positive Predictive Value-PPV.

  7. A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

    Directory of Open Access Journals (Sweden)

    Radek Martinek

    2017-04-01

    Full Text Available This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS, and the Normalized Least Mean Square (NLMS Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs, filtered from abdominal maternal phonocardiograms (mPCGs by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies and quantitative measures such as: Signal-to-Noise Ratio—SNR, Root Mean Square Error—RMSE, Sensitivity—S+, and Positive Predictive Value—PPV.

  8. Study on the State of Health Detection of Li-ion Power Batteries Based on Adaptive Unscented Kalman Filters

    Science.gov (United States)

    Yan, Xiangwu; Deng, Haoran; Wang, Ling; Guo, Qi

    2017-12-01

    It is essential to estimate the state of charge (SOC) and state of health (SOH) of the monomer battery in the electric vehicle li-ion power battery accurately for extending the li-ion power battery life. Based on the battery Thevenin equivalent circuit model, the paper uses adaptive unscented Kalman filter (AUKF) to estimate the inner ohmic resistance and the state of charge in real time, according to the function between the inner ohmic resistance and the state of health, the state of health can be estimated in real time. The battery charged and discharged experiments were done under two different conditions to verify the feasibility and accuracy of this method.

  9. Adaptive wave filtering for dynamic positioning of marine vessels using maximum likelihood identification: Theory and experiments

    Digital Repository Service at National Institute of Oceanography (India)

    Hassani, V.; Sorensen, A.J.; Pascoal, A.M.

    This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. The dynamic model of the vessel captures explicitly the sea state as an uncertain...

  10. A novel methodology for adaptive wave filtering of marine vessels: Theory and experiments

    Digital Repository Service at National Institute of Oceanography (India)

    Hassani, V.; Pascoal, A.M.; Sorensen, A.J.

    This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. The vessel`s dynamic model adopted captures the sea state as an uncertain...

  11. An Adaptive Object Tracking Using Kalman Filter and Probability Product Kernel

    Directory of Open Access Journals (Sweden)

    Hamd Ait Abdelali

    2016-01-01

    Full Text Available We present a new method for object tracking; we use an efficient local search scheme based on the Kalman filter and the probability product kernel (KFPPK to find the image region with a histogram most similar to the histogram of the tracked target. Experimental results verify the effectiveness of this proposed system.

  12. Speckle reduction of OCT images using an adaptive cluster-based filtering

    Science.gov (United States)

    Adabi, Saba; Rashedi, Elaheh; Conforto, Silvia; Mehregan, Darius; Xu, Qiuyun; Nasiriavanaki, Mohammadreza

    2017-02-01

    Optical coherence tomography (OCT) has become a favorable device in the dermatology discipline due to its moderate resolution and penetration depth. OCT images however contain grainy pattern, called speckle, due to the broadband source that has been used in the configuration of OCT. So far, a variety of filtering techniques is introduced to reduce speckle in OCT images. Most of these methods are generic and can be applied to OCT images of different tissues. In this paper, we present a method for speckle reduction of OCT skin images. Considering the architectural structure of skin layers, it seems that a skin image can benefit from being segmented in to differentiable clusters, and being filtered separately in each cluster by using a clustering method and filtering methods such as Wiener. The proposed algorithm was tested on an optical solid phantom with predetermined optical properties. The algorithm was also tested on healthy skin images. The results show that the cluster-based filtering method can reduce the speckle and increase the signal-to-noise ratio and contrast while preserving the edges in the image.

  13. Ubiquitination of Notch1 is regulated by MAML1-mediated p300 acetylation of Notch1

    Energy Technology Data Exchange (ETDEWEB)

    Popko-Scibor, Anita E.; Lindberg, Mikael J.; Hansson, Magnus L.; Holmlund, Teresa [Division of Molecular Toxicology, Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm (Sweden); Wallberg, Annika E., E-mail: Annika.Wallberg@ki.se [Division of Molecular Toxicology, Institute of Environmental Medicine, Karolinska Institutet, 171 77 Stockholm (Sweden)

    2011-12-16

    Highlights: Black-Right-Pointing-Pointer p300 acetylates conserved lysines within Notch1 C-terminal nuclear localization signal. Black-Right-Pointing-Pointer MAML1 and CSL, components of Notch transcription complex, increase Notch acetylation. Black-Right-Pointing-Pointer MAML1-dependent acetylation of Notch1 by p300 decreases the ubiquitination of Notch1. Black-Right-Pointing-Pointer CDK8 inhibits Notch acetylation and Notch transcription enhanced by p300. -- Abstract: Earlier studies demonstrated the involvement of the p300 histone acetyltransferase in Notch signaling but the precise mechanisms by which p300 might modulate Notch function remains to be investigated. In this study, we show that p300 acetylates Notch1 ICD in cell culture assay and in vitro, and conserved lysines located within the Notch C-terminal nuclear localization signal are essential for Notch acetylation. MAML1 and CSL, which are components of the Notch transcription complex, enhance Notch acetylation and we suggest that MAML1 increases Notch acetylation by potentiating p300 autoacetylation. Furthermore, MAML1-dependent acetylation of Notch1 ICD by p300 decreases the ubiquitination of Notch1 ICD in cellular assays. CDK8 has been shown to target Notch1 for ubiquitination and proteosomal degradation. We show that CDK8 inhibits Notch acetylation and Notch transcription enhanced by p300. Therefore, we speculate that acetylation of Notch1 might be a mechanism to regulate Notch activity by interfering with ubiquitin-dependent pathways.

  14. An Adaptive Systematic Lossy Error Protection Scheme for Broadcast Applications Based on Frequency Filtering and Unequal Picture Protection

    Directory of Open Access Journals (Sweden)

    Marie Ramon

    2009-01-01

    Full Text Available Systematic lossy error protection (SLEP is a robust error resilient mechanism based on principles of Wyner-Ziv (WZ coding for video transmission over error-prone networks. In an SLEP scheme, the video bitstream is separated into two parts: a systematic part consisting of a video sequence transmitted without channel coding, and additional information consisting of a WZ supplementary stream. This paper presents an adaptive SLEP scheme in which the WZ stream is obtained by frequency filtering in the transform domain. Additionally, error resilience varies adaptively depending on the characteristics of compressed video. We show that the proposed SLEP architecture achieves graceful degradation of reconstructed video quality in the presence of increasing transmission errors. Moreover, it provides good performances in terms of error protection as well as reconstructed video quality if compared to solutions based on coarser quantization, while offering an interesting embedded scheme to apply digital video format conversion.

  15. A Small UWB Antenna with Dual Band-Notched Characteristics

    Directory of Open Access Journals (Sweden)

    J. Xu

    2012-01-01

    Full Text Available A small novel ultrawideband (UWB antenna with dual band-notched functions is proposed. The dual band rejection is achieved by etching two C-shaped slots on the radiation patch with limited area. A single band-notched antenna is firstly presented, and then an optimized dual band-notched antenna is presented and analyzed. The measured VSWR shows that the proposed antenna could operate from 3.05 to 10.7 GHz with VSWR less than 2, except two stopbands at 3.38 to 3.82 GHz and 5.3 to 5.8 GHz for filtering the WiMAX and WLAN signals. Radiation patterns are simulated by HFSS and verified by CST, and quasiomnidirectional radiation patterns in the H-plane could be observed. Moreover, the proposed antenna has a very compact size and could be easily integrated into portable UWB devices.

  16. Band-notched ultrawide band antenna loaded with ferrite slab

    Science.gov (United States)

    Wang, Hao; Zong, Weihua; Sun, Nian X.; Lin, Hwaider; Li, Shandong

    2017-05-01

    In this paper, a novel technique to design a band-notched UWB antenna by using Yttrium Iron Garnet (YIG) ferrite is proposed. A printed slot UWB antenna with size of 21mm×26 mm×0.8 mm is adopted as a basic antenna. A piece of ferrite slab with size of 5 mm×10 mm×2 mm is attached on the feeding layer of the antenna to achieve band-notched characteristics. The measured -10 dB bandwidth of the antenna without ferrite slab is 2.91-10.98 GHz. With loading of ferrite slab, the bandwidth turns to 2.73-5.12 and 5.87-10.78 GHz. A band notch of 5.12- 5.87 GHz is achieved to filter WLAN 5 GHz (5.15-5.825 GHz) band. The proposed technique has virtue of easy fabrication and keeping antenna miniaturization.

  17. Adaptive Kalman filtering based internal temperature estimation with an equivalent electrical network thermal model for hard-cased batteries

    Science.gov (United States)

    Dai, Haifeng; Zhu, Letao; Zhu, Jiangong; Wei, Xuezhe; Sun, Zechang

    2015-10-01

    The accurate monitoring of battery cell temperature is indispensible to the design of battery thermal management system. To obtain the internal temperature of a battery cell online, an adaptive temperature estimation method based on Kalman filtering and an equivalent time-variant electrical network thermal (EENT) model is proposed. The EENT model uses electrical components to simulate the battery thermodynamics, and the model parameters are obtained with a least square algorithm. With a discrete state-space description of the EENT model, a Kalman filtering (KF) based internal temperature estimator is developed. Moreover, considering the possible time-varying external heat exchange coefficient, a joint Kalman filtering (JKF) based estimator is designed to simultaneously estimate the internal temperature and the external thermal resistance. Several experiments using the hard-cased LiFePO4 cells with embedded temperature sensors have been conducted to validate the proposed method. Validation results show that, the EENT model expresses the battery thermodynamics well, the KF based temperature estimator tracks the real central temperature accurately even with a poor initialization, and the JKF based estimator can simultaneously estimate both central temperature and external thermal resistance precisely. The maximum estimation errors of the KF- and JKF-based estimators are less than 1.8 °C and 1 °C respectively.

  18. Active Optical Lattice Filters

    Directory of Open Access Journals (Sweden)

    Gary Evans

    2005-06-01

    Full Text Available Optical lattice filter structures including gains are introduced and analyzed. The photonic realization of the active, adaptive lattice filter is described. The algorithms which map between gains space and filter coefficients space are presented and studied. The sensitivities of filter parameters with respect to gains are derived and calculated. An example which is relevant to adaptive signal processing is also provided.

  19. Adaptive unscented Kalman filter based state of energy and power capability estimation approach for lithium-ion battery

    Science.gov (United States)

    Zhang, Weige; Shi, Wei; Ma, Zeyu

    2015-09-01

    Accurate estimations of battery energy and available power capability are of great of importance for realizing an efficient and reliable operation of electric vehicles. To improve the estimation accuracy and reliability for battery state of energy and power capability, a novel model-based joint estimation approach has been proposed against uncertain external operating conditions and internal degradation status of battery cells. Firstly, it proposes a three-dimensional response surface open circuit voltage model to calibrate the estimation inaccuracies of battery state of energy. Secondly, the adaptive unscented Kalman filter (AUKF) is employed to develop a novel model-based joint state estimator for battery state of energy and power capability. The AUKF algorithm utilizes the well-known features of the Kalman filter but employs the method of unscented transform (UT) and adaptive error covariance matching technology to improve the state estimation accuracy. Thirdly, the proposed joint estimator has been verified by a LiFePO4 lithium-ion battery cell under different operating temperatures and aging levels. The result indicates that the estimation errors of battery voltage and state-of-energy are less than 2% even if given a large erroneous initial value, which makes the state of available power capability predict more accurate and reliable for the electric vehicles application.

  20. Integrated WiFi/PDR/Smartphone Using an Adaptive System Noise Extended Kalman Filter Algorithm for Indoor Localization

    Directory of Open Access Journals (Sweden)

    Xin Li

    2016-02-01

    Full Text Available Wireless signal strength is susceptible to the phenomena of interference, jumping, and instability, which often appear in the positioning results based on Wi-Fi field strength fingerprint database technology for indoor positioning. Therefore, a Wi-Fi and PDR (pedestrian dead reckoning real-time fusion scheme is proposed in this paper to perform fusing calculation by adaptively determining the dynamic noise of a filtering system according to pedestrian movement (straight or turning, which can effectively restrain the jumping or accumulation phenomena of wireless positioning and the PDR error accumulation problem. Wi-Fi fingerprint matching typically requires a quite high computational burden: To reduce the computational complexity of this step, the affinity propagation clustering algorithm is adopted to cluster the fingerprint database and integrate the information of the position domain and signal domain of respective points. An experiment performed in a fourth-floor corridor at the School of Environment and Spatial Informatics, China University of Mining and Technology, shows that the traverse points of the clustered positioning system decrease by 65%–80%, which greatly improves the time efficiency. In terms of positioning accuracy, the average error is 4.09 m through the Wi-Fi positioning method. However, the positioning error can be reduced to 2.32 m after integration of the PDR algorithm with the adaptive noise extended Kalman filter (EKF.

  1. Online Reduction of Artifacts in EEG of Simultaneous EEG-fMRI Using Reference Layer Adaptive Filtering (RLAF).

    Science.gov (United States)

    Steyrl, David; Krausz, Gunther; Koschutnig, Karl; Edlinger, Günter; Müller-Putz, Gernot R

    2017-11-09

    Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) allow us to study the active human brain from two perspectives concurrently. Signal processing based artifact reduction techniques are mandatory for this, however, to obtain reasonable EEG quality in simultaneous EEG-fMRI. Current artifact reduction techniques like average artifact subtraction (AAS), typically become less effective when artifact reduction has to be performed on-the-fly. We thus present and evaluate a new technique to improve EEG quality online. This technique adds up with online AAS and combines a prototype EEG-cap for reference recordings of artifacts, with online adaptive filtering and is named reference layer adaptive filtering (RLAF). We found online AAS + RLAF to be highly effective in improving EEG quality. Online AAS + RLAF outperformed online AAS and did so in particular online in terms of the chosen performance metrics, these being specifically alpha rhythm amplitude ratio between closed and opened eyes (3-45% improvement), signal-to-noise-ratio of visual evoked potentials (VEP) (25-63% improvement), and VEPs variability (16-44% improvement). Further, we found that EEG quality after online AAS + RLAF is occasionally even comparable with the offline variant of AAS at a 3T MRI scanner. In conclusion RLAF is a very effective add-on tool to enable high quality EEG in simultaneous EEG-fMRI experiments, even when online artifact reduction is necessary.

  2. A FPGA-based Fast Converging Digital Adaptive Filter for Real-time RFI Mitigation on Ground Based Radio Telescopes

    Science.gov (United States)

    Finger, R.; Curotto, F.; Fuentes, R.; Duan, R.; Bronfman, L.; Li, D.

    2018-02-01

    Radio Frequency Interference (RFI) is a growing concern in the radio astronomy community. Single-dish telescopes are particularly susceptible to RFI. Several methods have been developed to cope with RF-polluted environments, based on flagging, excision, and real-time blanking, among others. All these methods produce some degree of data loss or require assumptions to be made on the astronomical signal. We report the development of a real-time, digital adaptive filter implemented on a Field Programmable Gate Array (FPGA) capable of processing 4096 spectral channels in a 1 GHz of instantaneous bandwidth. The filter is able to cancel a broad range of interference signals and quickly adapt to changes on the RFI source, minimizing the data loss without any assumption on the astronomical or interfering signal properties. The speed of convergence (for a decrease to a 1%) was measured to be 208.1 μs for a broadband noise-like RFI signal and 125.5 μs for a multiple-carrier RFI signal recorded at the FAST radio telescope.

  3. Adaptive removal of gradients-induced artefacts on ECG in MRI: a performance analysis of RLS filtering.

    Science.gov (United States)

    Sansone, Mario; Mirarchi, Luciano; Bracale, Marcello

    2010-05-01

    One of the main vital signs used in patient monitoring during Magnetic Resonance Imaging (MRI) is Electro-Cardio-Gram (ECG). Unfortunately, magnetic fields gradients induce artefacts which severely affect ECG quality. Adaptive Noise Cancelling (ANC) is one of the preferred techniques for artefact removal. ANC involves the adaptive estimation of the impulse response of the system constituted by the MRI equipment, the patient and the ECG recording device. Least Mean Square (LMS) adaptive filtering has been traditionally employed because of its simplicity: anyway, it requires the choice of a step-size parameter, whose proper value for the specific application must be estimated case by case: an improper choice could yield slow convergence and unsatisfactory behaviour. Recursive Least Square (RLS) algorithm has, potentially, faster convergence while not requiring any parameter. As far as the authors' knowledge, there is no systematic analysis of performances of RLS in this scenario. In this study we evaluated the performance of RLS for adaptive removal of artefacts induced by magnetic field gradients on ECG in MRI, in terms of efficacy of suppression. Tests have been made on real signals, acquired via an expressly developed system. A comparison with LMS was made on the basis of opportune performance indices. Results indicate that RLS is superior to LMS in several respects.

  4. Filter goggles imitating dark adaptation for measurement of visual readaptation after flash exposure.

    Science.gov (United States)

    Wang, L; Zand, M R; Söderberg, P G

    1994-08-01

    The effect of red pass goggles (cut off wavelength = 650 nm) imitating dark adaptation on measurement of visual readaptation after flash exposure was investigated in humans. The results showed that there is no statistically significant difference between visual readaptation time measured with ordinary dark adaptation and that with goggles for adaptation. No statistically significant difference was found between females and males. It is suggested that red pass goggles can be practicably used to simulate dark adaptation in measuring visual readaptation time. Visual readaptation time was measured as the interval between the triggering of a green flash and the reappearance of optokinetic nystagmus. Optokinetic nystagmus was induced by a moving vertical grating and recorded by DC EOG.

  5. Method of detecting abnormal signals by wavelet and adaptive digital filter; Wavelet to tekio digital filter ni yoru ijo shingo no kenshutsuho

    Energy Technology Data Exchange (ETDEWEB)

    Sasaki, T. [Idemitsu Engineering Co. Ltd., Tokyo (Japan); Hanakuma, Y.; Nakayama, K. [Idemitsu Petrochemical Co. Ltd., Tokyo (Japan); Nakanishi, E. [Kobe University, Kobe (Japan)

    1994-09-15

    With an objective to improve incompleteness in abnormality detection in the conventional standard function monitoring using a discrete type control system, an abnormal signal detection method was developed that uses a wavelet that processes on-line signals easily and an adaptive digital filter (ADF). Multiplying the signal `f(t)` with a wavelet function `h{sub o}(t)` and integrating the result derives the wavelet conversion value `h(a, b)`. Since the weight imposed on the data can be changed, the `h(a, b)` responds sensitively to the change in `f(t)`. A Gbor function that facilitates on-line processing was used for `h{sub o}t`. The ADF detects errors between the target value and the output value by using the algorithm of Feintuch, and can estimate the change in the signal and the time when the abnormal signal has mixed in. The trend indication facilitates the monitoring, and makes the on-line detection possible. The effectiveness of the method was verified when it was applied to a simulation and detection of abnormality in catalyst flow rate in a polyethylene manufacturing device. 2 refs., 7 figs.

  6. Adaptively Blocked Particle Filtering with Spatial Smoothing in Large Scale Dynamic Random Fields

    Science.gov (United States)

    2014-07-01

    References [1] B.D.O. Anderson and J.B. Moore. Optimal Filtering. Prentice Hall, Englewood Cliffs, N.J., 1979. [2] A. Beskos, D. Crisan , and A. Jasra. On the... Crisan , A. Jasra, and N. Whiteley. Error bounds and normalising constants for sequential Monte Carlo samplers in high dimensions. Advances in Applied...Statistics, 2008. [5] O. Cappé, E. Moulines, and T. Rydén. Inference in Hidden MarkovModels. Springer, New York, N.Y., 2005. [6] D. Crisan and A. Doucet

  7. A tunable electrochromic fabry-perot filter for adaptive optics applications.

    Energy Technology Data Exchange (ETDEWEB)

    Blaich, Jonathan David; Kammler, Daniel R.; Ambrosini, Andrea; Sweatt, William C.; Verley, Jason C.; Heller, Edwin J.; Yelton, William Graham

    2006-10-01

    The potential for electrochromic (EC) materials to be incorporated into a Fabry-Perot (FP) filter to allow modest amounts of tuning was evaluated by both experimental methods and modeling. A combination of chemical vapor deposition (CVD), physical vapor deposition (PVD), and electrochemical methods was used to produce an ECFP film stack consisting of an EC WO{sub 3}/Ta{sub 2}O{sub 5}/NiO{sub x}H{sub y} film stack (with indium-tin-oxide electrodes) sandwiched between two Si{sub 3}N{sub 4}/SiO{sub 2} dielectric reflector stacks. A process to produce a NiO{sub x}H{sub y} charge storage layer that freed the EC stack from dependence on atmospheric humidity and allowed construction of this complex EC-FP stack was developed. The refractive index (n) and extinction coefficient (k) for each layer in the EC-FP film stack was measured between 300 and 1700 nm. A prototype EC-FP filter was produced that had a transmission at 500 nm of 36%, and a FWHM of 10 nm. A general modeling approach that takes into account the desired pass band location, pass band width, required transmission and EC optical constants in order to estimate the maximum tuning from an EC-FP filter was developed. Modeling shows that minor thickness changes in the prototype stack developed in this project should yield a filter with a transmission at 600 nm of 33% and a FWHM of 9.6 nm, which could be tuned to 598 nm with a FWHM of 12.1 nm and a transmission of 16%. Additional modeling shows that if the EC WO{sub 3} absorption centers were optimized, then a shift from 600 nm to 598 nm could be made with a FWHM of 11.3 nm and a transmission of 20%. If (at 600 nm) the FWHM is decreased to 1 nm and transmission maintained at a reasonable level (e.g. 30%), only fractions of a nm of tuning would be possible with the film stack considered in this study. These tradeoffs may improve at other wavelengths or with EC materials different than those considered here. Finally, based on our limited investigation and material set

  8. Binaural noise reduction via cue-preserving MMSE filter and adaptive-blocking-based noise PSD estimation

    Science.gov (United States)

    Azarpour, Masoumeh; Enzner, Gerald

    2017-12-01

    Binaural noise reduction, with applications for instance in hearing aids, has been a very significant challenge. This task relates to the optimal utilization of the available microphone signals for the estimation of the ambient noise characteristics and for the optimal filtering algorithm to separate the desired speech from the noise. The additional requirements of low computational complexity and low latency further complicate the design. A particular challenge results from the desired reconstruction of binaural speech input with spatial cue preservation. The latter essentially diminishes the utility of multiple-input/single-output filter-and-sum techniques such as beamforming. In this paper, we propose a comprehensive and effective signal processing configuration with which most of the aforementioned criteria can be met suitably. This relates especially to the requirement of efficient online adaptive processing for noise estimation and optimal filtering while preserving the binaural cues. Regarding noise estimation, we consider three different architectures: interaural (ITF), cross-relation (CR), and principal-component (PCA) target blocking. An objective comparison with two other noise PSD estimation algorithms demonstrates the superiority of the blocking-based noise estimators, especially the CR-based and ITF-based blocking architectures. Moreover, we present a new noise reduction filter based on minimum mean-square error (MMSE), which belongs to the class of common gain filters, hence being rigorous in terms of spatial cue preservation but also efficient and competitive for the acoustic noise reduction task. A formal real-time subjective listening test procedure is also developed in this paper. The proposed listening test enables a real-time assessment of the proposed computationally efficient noise reduction algorithms in a realistic acoustic environment, e.g., considering time-varying room impulse responses and the Lombard effect. The listening test outcome

  9. An Adaptive Filtering-based Adjustment Method for Reliability Parameters of Vehicle Systems During Their Lifecycle

    Directory of Open Access Journals (Sweden)

    O. M. Lurie

    2017-01-01

    Full Text Available The paper considers a problem of difficult accessibility and low quality of data on the reliability parameters of the vehicle system components and the difficulties arising from this problem to estimate the reliability parameters of the systems themselves as statutorily required and in terms of international standards (e.g. ISO 26262. As a problem solution, the paper proposes a method for adjustment of the system reliability estimates based on the field observation of system failures. The method based on a Kalman filter uses non-parametric definition of the failure probability distribution (quantile «folding» of the distribution with subsequent «unfolding» via Monte Carlo.A mathematical model shows how to use this method.  For clarity, the estimates of reliability parameters are given at the time of rollout (100 % of systems are in working order and upon the failure of 25%, 50%, 75% and 100% of produced systems, respectively. A КК plot shows that the reliability estimates gradually become close to the field reliability data.The method allows, by varying filter parameters, a more conservative estimate of the reliability parameters or an estimate, which is more in accord with the field data. Thus, the results can be used at all stages of the system lifecycle, namely when developing, manufacturing and upon completing production for the aftermarket services.

  10. Detection of User Independent Single Trial ERPs in Brain Computer Interfaces: An Adaptive Spatial Filtering Approach

    DEFF Research Database (Denmark)

    Leza, Cristina; Puthusserypady, Sadasivan

    2017-01-01

    Brain Computer Interfaces (BCIs) use brain signals to communicate with the external world. The main challenges to address are speed, accuracy and adaptability. Here, a novel algorithm for P300 based BCI spelling system is presented, specifically suited for single-trial detection of Event...

  11. A Study on Maneuvering Obstacle Motion State Estimation for Intelligent Vehicle Using Adaptive Kalman Filter Based on Current Statistical Model

    Directory of Open Access Journals (Sweden)

    Bao Han

    2015-01-01

    Full Text Available The obstacle motion state estimation is an essential task in intelligent vehicle. The ASCL group has developed such a system that uses a radar and GPS/INS. When running on the road, the acceleration of the vehicle is always changing, so it is hard for constant velocity (CV model and constant acceleration (CA model to describe the motion state of the vehicle. This paper introduced Current Statistical (CS model from military field, which uses the modified Rayleigh distribution to describe acceleration. The adaptive Kalman filter based on CS model was used to estimate the motion state of the target. We conducted simulation experiments and real vehicle tests, and the results showed that the estimation of position, velocity, and acceleration can be precise.

  12. The energy-efficient implementation of an adaptive-filtering-based QRS complex detection method for wearable devices

    Science.gov (United States)

    Tian, Shudong; Han, Jun; Yang, Jianwei; Zeng, Xiaoyang

    2017-10-01

    Electrocardiogram (ECG) can be used as a valid way for diagnosing heart disease. To fulfill ECG processing in wearable devices by reducing computation complexity and hardware cost, two kinds of adaptive filters are designed to perform QRS complex detection and motion artifacts removal, respectively. The proposed design achieves a sensitivity of 99.49% and a positive predictivity of 99.72%, tested under the MIT-BIH ECG database. The proposed design is synthesized under the SMIC 65-nm CMOS technology and verified by post-synthesis simulation. Experimental results show that the power consumption and area cost of this design are of 160 μW and 1.09 × 10 5 μm2, respectively. Project supported by the National Natural Science Foundation of China (Nos. 61574040, 61234002, 61525401).

  13. An optimized DSP implementation of adaptive filtering and ICA for motion artifact reduction in ambulatory ECG monitoring.

    Science.gov (United States)

    Berset, Torfinn; Geng, Di; Romero, Iñaki

    2012-01-01

    Noise from motion artifacts is currently one of the main challenges in the field of ambulatory ECG recording. To address this problem, we propose the use of two different approaches. First, an adaptive filter with electrode-skin impedance as a reference signal is described. Secondly, a multi-channel ECG algorithm based on Independent Component Analysis is introduced. Both algorithms have been designed and further optimized for real-time work embedded in a dedicated Digital Signal Processor. We show that both algorithms improve the performance of a beat detection algorithm when applied in high noise conditions. In addition, an efficient way of choosing this methods is suggested with the aim of reduce the overall total system power consumption.

  14. Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

    Science.gov (United States)

    Villa-Parra, Ana Cecilia; Bastos-Filho, Teodiano; López-Delis, Alberto; Frizera-Neto, Anselmo; Krishnan, Sridhar

    2017-01-01

    This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p<0.01) improved for most of the subjects (ACC≥74.79%), when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry. PMID:29186848

  15. Bridge Performance Assessment Based on an Adaptive Neuro-Fuzzy Inference System with Wavelet Filter for the GPS Measurements

    Directory of Open Access Journals (Sweden)

    Mosbeh R. Kaloop

    2015-10-01

    Full Text Available This study describes the performance assessment of the Huangpu Bridge in Guangzhou, China based on long-term monitoring in real-time by the kinematic global positioning system (RTK-GPS technique. Wavelet transformde-noising is applied to filter the GPS measurements, while the adaptive neuro-fuzzy inference system (ANFIS time series output-only model is used to predict the deformations of GPS-bridge monitoring points. In addition, GPS and accelerometer monitoring systems are used to evaluate the bridge oscillation performance. The conclusions drawn from investigating the numerical results show that: (1the wavelet de-noising of the GPS measurements of the different recording points on the bridge is a suitable tool to efficiently eliminate the signal noise and extract the different deformation components such as: semi-static and dynamic displacements; (2 the ANFIS method with two multi-input single output model is revealed to powerfully predict GPS movement measurements and assess the bridge deformations; and (3 The installed structural health monitoring system and the applied ANFIS movement prediction performance model are solely sufficient to assure bridge safety based on the analyses of the different filtered movement components.

  16. An Artificial Measurements-Based Adaptive Filter for Energy-Efficient Target Tracking via Underwater Wireless Sensor Networks.

    Science.gov (United States)

    Chen, Huayan; Zhang, Senlin; Liu, Meiqin; Zhang, Qunfei

    2017-04-27

    We study the problem of energy-efficient target tracking in underwater wireless sensor networks (UWSNs). Since sensors of UWSNs are battery-powered, it is impracticable to replace the batteries when exhausted. This means that the battery life affects the lifetime of the whole network. In order to extend the network lifetime, it is worth reducing the energy consumption on the premise of sufficient tracking accuracy. This paper proposes an energy-efficient filter that implements the tradeoff between communication cost and tracking accuracy. Under the distributed fusion framework, local sensors should not send their weak information to the fusion center if their measurement residuals are smaller than the pre-given threshold. In order to guarantee the target tracking accuracy, artificial measurements are generated to compensate for those unsent real measurements. Then, an adaptive scheme is derived to take full advantages of the artificial measurements-based filter in terms of energy-efficiency. Furthermore, a computationally efficient optimal sensor selection scheme is proposed to improve tracking accuracy on the premise of employing the same number of sensors. Simulation demonstrates that our scheme has superior advantages in the tradeoff between communication cost and tracking accuracy. It saves much energy while loosing little tracking accuracy or improves tracking performance with less additional energy cost.

  17. An Artificial Measurements-Based Adaptive Filter for Energy-Efficient Target Tracking via Underwater Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Huayan Chen

    2017-04-01

    Full Text Available We study the problem of energy-efficient target tracking in underwater wireless sensor networks (UWSNs. Since sensors of UWSNs are battery-powered, it is impracticable to replace the batteries when exhausted. This means that the battery life affects the lifetime of the whole network. In order to extend the network lifetime, it is worth reducing the energy consumption on the premise of sufficient tracking accuracy. This paper proposes an energy-efficient filter that implements the tradeoff between communication cost and tracking accuracy. Under the distributed fusion framework, local sensors should not send their weak information to the fusion center if their measurement residuals are smaller than the pre-given threshold. In order to guarantee the target tracking accuracy, artificial measurements are generated to compensate for those unsent real measurements. Then, an adaptive scheme is derived to take full advantages of the artificial measurements-based filter in terms of energy-efficiency. Furthermore, a computationally efficient optimal sensor selection scheme is proposed to improve tracking accuracy on the premise of employing the same number of sensors. Simulation demonstrates that our scheme has superior advantages in the tradeoff between communication cost and tracking accuracy. It saves much energy while loosing little tracking accuracy or improves tracking performance with less additional energy cost.

  18. Adaptive prognosis of lithium-ion batteries based on the combination of particle filters and radial basis function neural networks

    Science.gov (United States)

    Sbarufatti, Claudio; Corbetta, Matteo; Giglio, Marco; Cadini, Francesco

    2017-03-01

    Lithium-Ion rechargeable batteries are widespread power sources with applications to consumer electronics, electrical vehicles, unmanned aerial and spatial vehicles, etc. The failure to supply the required power levels may lead to severe safety and economical consequences. Thus, in view of the implementation of adequate maintenance strategies, the development of diagnostic and prognostic tools for monitoring the state of health of the batteries and predicting their remaining useful life is becoming a crucial task. Here, we propose a method for predicting the end of discharge of Li-Ion batteries, which stems from the combination of particle filters with radial basis function neural networks. The major innovation lies in the fact that the radial basis function model is adaptively trained on-line, i.e., its parameters are identified in real time by the particle filter as new observations of the battery terminal voltage become available. By doing so, the prognostic algorithm achieves the flexibility needed to provide sound end-of-discharge time predictions as the charge-discharge cycles progress, even in presence of anomalous behaviors due to failures or unforeseen operating conditions. The method is demonstrated with reference to actual Li-Ion battery discharge data contained in the prognostics data repository of the NASA Ames Research Center database.

  19. Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

    Directory of Open Access Journals (Sweden)

    Denis Delisle-Rodriguez

    2017-11-01

    Full Text Available This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs based on Canonical Correlation Analysis (CCA to recognize 40 targets of steady-state visual evoked potential (SSVEP, providing an accuracy (ACC of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly ( p < 0.01 improved for most of the subjects ( A C C ≥ 74.79 % , when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry.

  20. PKCζ regulates Notch receptor routing and activity in a Notch signaling-dependent manner.

    Science.gov (United States)

    Sjöqvist, Marika; Antfolk, Daniel; Ferraris, Saima; Rraklli, Vilma; Haga, Cecilia; Antila, Christian; Mutvei, Anders; Imanishi, Susumu Y; Holmberg, Johan; Jin, Shaobo; Eriksson, John E; Lendahl, Urban; Sahlgren, Cecilia

    2014-04-01

    Activation of Notch signaling requires intracellular routing of the receptor, but the mechanisms controlling the distinct steps in the routing process is poorly understood. We identify PKCζ as a key regulator of Notch receptor intracellular routing. When PKCζ was inhibited in the developing chick central nervous system and in cultured myoblasts, Notch-stimulated cells were allowed to undergo differentiation. PKCζ phosphorylates membrane-tethered forms of Notch and regulates two distinct routing steps, depending on the Notch activation state. When Notch is activated, PKCζ promotes re-localization of Notch from late endosomes to the nucleus and enhances production of the Notch intracellular domain, which leads to increased Notch activity. In the non-activated state, PKCζ instead facilitates Notch receptor internalization, accompanied with increased ubiquitylation and interaction with the endosomal sorting protein Hrs. Collectively, these data identify PKCζ as a key regulator of Notch trafficking and demonstrate that distinct steps in intracellular routing are differentially modulated depending on Notch signaling status.

  1. Endosomal sorting of Notch receptors through COMMD9-dependent pathways modulates Notch signaling

    NARCIS (Netherlands)

    Li, H.; Koo, Y.; Mao, X.; Sifuentes-Dominguez, L.; Morris, L.L.; Jia, D.; Miyata, N; Faulkner, R.A.; Deursen, J.M.A. van; Vooijs, M.; Billadeau, D.D.; Sluis, B. van de; Cleaver, O.; Burstein, E.

    2015-01-01

    Notch family members are transmembrane receptors that mediate essential developmental programs. Upon ligand binding, a proteolytic event releases the intracellular domain of Notch, which translocates to the nucleus to regulate gene transcription. In addition, Notch trafficking across the

  2. Notch Signaling and Brain Tumors

    DEFF Research Database (Denmark)

    Stockhausen, Marie; Kristoffersen, Karina; Poulsen, Hans Skovgaard

    2011-01-01

    Human brain tumors are a heterogenous group of neoplasms occurring inside the cranium and the central spinal cord. In adults and children, astrocytic glioma and medulloblastoma are the most common subtypes of primary brain tumors. These tumor types are thought to arise from cells in which Notch...... and medulloblastoma. In this chapter we will cover the present findings of Notch signaling in human glioma and medulloblastoma and try to create an overall picture of its relevance in the pathogenesis of these tumors....

  3. Compression of seismic data: filter banks and extended transforms, synthesis and adaptation; Compression de donnees sismiques: bancs de filtres et transformees etendues, synthese et adaptation

    Energy Technology Data Exchange (ETDEWEB)

    Duval, L.

    2000-11-01

    Wavelet and wavelet packet transforms are the most commonly used algorithms for seismic data compression. Wavelet coefficients are generally quantized and encoded by classical entropy coding techniques. We first propose in this work a compression algorithm based on the wavelet transform. The wavelet transform is used together with a zero-tree type coding, with first use in seismic applications. Classical wavelet transforms nevertheless yield a quite rigid approach, since it is often desirable to adapt the transform stage to the properties of each type of signal. We thus propose a second algorithm using, instead of wavelets, a set of so called 'extended transforms'. These transforms, originating from the filter bank theory, are parameterized. Classical examples are Malvar's Lapped Orthogonal Transforms (LOT) or de Queiroz et al. Generalized Lapped Orthogonal Transforms (GenLOT). We propose several optimization criteria to build 'extended transforms' which are adapted the properties of seismic signals. We further show that these transforms can be used with the same zero-tree type coding technique as used with wavelets. Both proposed algorithms provide exact compression rate choice, block-wise compression (in the case of extended transforms) and partial decompression for quality control or visualization. Performances are tested on a set of actual seismic data. They are evaluated for several quality measures. We also compare them to other seismic compression algorithms. (author)

  4. Non-Invasive Fetal Monitoring: A Maternal Surface ECG Electrode Placement-Based Novel Approach for Optimization of Adaptive Filter Control Parameters Using the LMS and RLS Algorithms.

    Science.gov (United States)

    Martinek, Radek; Kahankova, Radana; Nazeran, Homer; Konecny, Jaromir; Jezewski, Janusz; Janku, Petr; Bilik, Petr; Zidek, Jan; Nedoma, Jan; Fajkus, Marcel

    2017-05-19

    This paper is focused on the design, implementation and verification of a novel method for the optimization of the control parameters (such as step size μ and filter order N) of LMS and RLS adaptive filters used for noninvasive fetal monitoring. The optimization algorithm is driven by considering the ECG electrode positions on the maternal body surface in improving the performance of these adaptive filters. The main criterion for optimal parameter selection was the Signal-to-Noise Ratio (SNR). We conducted experiments using signals supplied by the latest version of our LabVIEW-Based Multi-Channel Non-Invasive Abdominal Maternal-Fetal Electrocardiogram Signal Generator, which provides the flexibility and capability of modeling the principal distribution of maternal/fetal ECGs in the human body. Our novel algorithm enabled us to find the optimal settings of the adaptive filters based on maternal surface ECG electrode placements. The experimental results further confirmed the theoretical assumption that the optimal settings of these adaptive filters are dependent on the ECG electrode positions on the maternal body, and therefore, we were able to achieve far better results than without the use of optimization. These improvements in turn could lead to a more accurate detection of fetal hypoxia. Consequently, our approach could offer the potential to be used in clinical practice to establish recommendations for standard electrode placement and find the optimal adaptive filter settings for extracting high quality fetal ECG signals for further processing. Ultimately, diagnostic-grade fetal ECG signals would ensure the reliable detection of fetal hypoxia.

  5. Adaptive Tracking Filter Design and Evaluation for Gun Fire Control Systems

    Science.gov (United States)

    1974-01-23

    Nominal Case. ( ia,l < 50 ft/sec3) < I < ■ c (c* Hif^ily Evasive Cose (!a,| < 150 ft/sec3) Figure 2.3-2 Target Norma * Acceleration... IEEE Trans- actions on Automatic Control, Vol. AC-16, No. 6, December 1971. 4. Magill, D.T., "Optimal Adaptive Estimation of Sampled Stochastic...August 1972. 7. Hampton, R. L.T. and Cooke, J.R., "Unsupervised Tracking of Maneuvering Vehicles," IEEE Transactions on Aerospacgand Electronic

  6. Adaptive filtering of ballistocardiogram artifact from EEG signals using the dilated discrete Hermite transform.

    Science.gov (United States)

    Mahadevan, Anandi; Mugler, Dale H; Acharya, Soumyadipta

    2008-01-01

    Electroencephalogram (EEG) signals, when recorded within the strong magnetic field of an MRI scanner are subject to various artifacts, of which the ballistocardiogram (BCG) is one of the prominent ones affecting the quality of the EEG. The BCG artifact varies slightly in shape and amplitude for every cardiac cycle making it difficult to identify and remove. This paper proposes a novel method for the identification and elimination of this artifact using the shape basis functions of the new dilated discrete Hermite transform. In this study, EEG data within and outside the scanner was recorded. On removal of the BCG artifact for the EEG data recorded within the scanner, a significant reduction in amplitude at the frequencies associated with the BCG artifact was observed. In order to quantitatively assess the efficacy of this method, BCG artifact templates were added to segments of EEG signals recorded outside the scanner. These signals, when filtered using the proposed method, had no significant difference (p0.05) from the original signals, indicating that the technique satisfactorily eliminates the BCG artifact and does not introduce any distortions in the original signal. The method is computationally efficient for real-time implementation.

  7. Notch 1 impairs osteoblastic cell differentiation.

    Science.gov (United States)

    Sciaudone, Maria; Gazzerro, Elisabetta; Priest, Leah; Delany, Anne M; Canalis, Ernesto

    2003-12-01

    Notch receptors are single pass transmembrane receptors activated by membrane-bound ligands with a role in cell proliferation and differentiation. As Notch 1 and 2 mRNAs are expressed by osteoblasts and induced by cortisol, we postulated that Notch could regulate osteoblastogenesis. We investigated the effects of retroviral vectors directing the constitutive expression of the Notch 1 intracellular domain (NotchIC) in murine ST-2 stromal and in MC3T3 cells. NotchIC overexpression was documented by increased Notch 1 transcripts and activity of the Notch-dependent Hairy Enhancer of Split promoter. In the presence of bone morphogenetic protein-2 (BMP-2), ST-2 cells differentiated toward osteoblasts forming mineralized nodules, and Notch 1 opposed this effect and decreased the expression of osteocalcin, type I collagen, and alkaline phosphatase transcripts and Delta2Delta FosB protein. Further, NotchIC decreased Wnt/beta-catenin signaling. As cells differentiated in the presence of BMP-2, they underwent apoptosis, and Notch opposed this event. In the presence of cortisol, NotchIC induced the formation of mature adipocytes and enhanced the effect of cortisol on adipsin, peroxisome proliferator-activated receptor-gamma2 and CCAAT enhancer binding protein alpha and delta mRNA levels. NotchIC also opposed MC3T3 cell differentiation and the expression of a mature osteoblastic phenotype. In conclusion, NotchIC impairs osteoblast differentiation and enhances adipogenesis in stromal cell cultures.

  8. Local ensemble transform Kalman filter, a fast non-stationary control law for adaptive optics on ELTs: theoretical aspects and first simulation results.

    Science.gov (United States)

    Gray, Morgan; Petit, Cyril; Rodionov, Sergey; Bocquet, Marc; Bertino, Laurent; Ferrari, Marc; Fusco, Thierry

    2014-08-25

    We propose a new algorithm for an adaptive optics system control law, based on the Linear Quadratic Gaussian approach and a Kalman Filter adaptation with localizations. It allows to handle non-stationary behaviors, to obtain performance close to the optimality defined with the residual phase variance minimization criterion, and to reduce the computational burden with an intrinsically parallel implementation on the Extremely Large Telescopes (ELTs).

  9. An Adaptive Particle Filtering Approach to Tracking Modes in a Varying Shallow Ocean Environment

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J V

    2011-03-22

    The shallow ocean environment is ever changing mostly due to temperature variations in its upper layers (< 100m) directly affecting sound propagation throughout. The need to develop processors that are capable of tracking these changes implies a stochastic as well as an 'adaptive' design. The stochastic requirement follows directly from the multitude of variations created by uncertain parameters and noise. Some work has been accomplished in this area, but the stochastic nature was constrained to Gaussian uncertainties. It has been clear for a long time that this constraint was not particularly realistic leading a Bayesian approach that enables the representation of any uncertainty distribution. Sequential Bayesian techniques enable a class of processors capable of performing in an uncertain, nonstationary (varying statistics), non-Gaussian, variable shallow ocean. In this paper adaptive processors providing enhanced signals for acoustic hydrophonemeasurements on a vertical array as well as enhanced modal function estimates are developed. Synthetic data is provided to demonstrate that this approach is viable.

  10. Adaptive filtering to reduce global interference in non-invasive NIRS measures of brain activation: how well and when does it work?

    Science.gov (United States)

    Zhang, Quan; Strangman, Gary E; Ganis, Giorgio

    2009-04-15

    In previous work we introduced a novel method for reducing global interference, based on adaptive filtering, to improve the contrast to noise ratio (CNR) of evoked hemodynamic responses measured non-invasively with near infrared spectroscopy (NIRS). Here, we address the issue of how to generally apply the proposed adaptive filtering method. A total of 156 evoked visual response measurements, collected from 15 individuals, were analyzed. The similarity (correlation) between measurements with far and near source-detector separations collected during the rest period before visual stimulation was used as indicator of global interference dominance. A detailed analysis of CNR improvement in oxy-hemoglobin (O(2)Hb) and deoxy-hemoglobin (HHb), as a function of the rest period correlation coefficient, is presented. Results show that for O(2)Hb measurements, 66% exhibited substantial global interference. For this dataset, dominated by global interference, 71% of the measurements revealed CNR improvements after adaptive filtering, with a mean CNR improvement of 60%. No CNR improvement was observed for HHb. This study corroborates our previous finding that adaptive filtering provides an effective method to increase CNR when there is strong global interference, and also provides a practical way for determining when and where to apply this technique.

  11. FPGA/NIOS Implementation of an Adaptive FIR Filter Using Linear Prediction to Reduce Narrow-Band RFI for Radio Detection of Cosmic Rays

    NARCIS (Netherlands)

    Szadkowski, Zbigniew; Fraenkel, E. D.; van den Berg, Ad M.

    2013-01-01

    We present the FPGA/NIOS implementation of an adaptive finite impulse response (FIR) filter based on linear prediction to suppress radio frequency interference (RFI). This technique will be used for experiments that observe coherent radio emission from extensive air showers induced by

  12. NOTCH1 and NOTCH2 regulate epithelial cell proliferation in mouse and human gastric corpus.

    Science.gov (United States)

    Demitrack, Elise S; Gifford, Gail B; Keeley, Theresa M; Horita, Nobukatsu; Todisco, Andrea; Turgeon, D Kim; Siebel, Christian W; Samuelson, Linda C

    2017-02-01

    The Notch signaling pathway is known to regulate stem cells and epithelial cell homeostasis in gastrointestinal tissues; however, Notch function in the corpus region of the stomach is poorly understood. In this study we examined the consequences of Notch inhibition and activation on cellular proliferation and differentiation and defined the specific Notch receptors functioning in the mouse and human corpus. Notch pathway activity was observed in the mouse corpus epithelium, and gene expression analysis revealed NOTCH1 and NOTCH2 to be the predominant Notch receptors in both mouse and human. Global Notch inhibition for 5 days reduced progenitor cell proliferation in the mouse corpus, as well as in organoids derived from mouse and human corpus tissue. Proliferation effects were mediated through both NOTCH1 and NOTCH2 receptors, as demonstrated by targeting each receptor alone or in combination with Notch receptor inhibitory antibodies. Analysis of differentiation by marker expression showed no change to the major cell lineages; however, there was a modest increase in the number of transitional cells coexpressing markers of mucous neck and chief cells. In contrast to reduced proliferation after pathway inhibition, Notch activation in the adult stomach resulted in increased proliferation coupled with reduced differentiation. These findings suggest that NOTCH1 and NOTCH2 signaling promotes progenitor cell proliferation in the mouse and human gastric corpus, which is consistent with previously defined roles for Notch in promoting stem and progenitor cell proliferation in the intestine and antral stomach. Here we demonstrate that the Notch signaling pathway is essential for proliferation of stem cells in the mouse and human gastric corpus. We identify NOTCH1 and NOTCH2 as the predominant Notch receptors expressed in both mouse and human corpus and show that both receptors are required for corpus stem cell proliferation. We show that chronic Notch activation in corpus stem

  13. A Fixed-Lag Kalman Smoother to Filter Power Line Interference in Electrocardiogram Recordings.

    Science.gov (United States)

    Warmerdam, G J J; Vullings, R; Schmitt, L; Van Laar, J O E H; Bergmans, J W M

    2017-08-01

    Filtering power line interference (PLI) from electrocardiogram (ECG) recordings can lead to significant distortions of the ECG and mask clinically relevant features in ECG waveform morphology. The objective of this study is to filter PLI from ECG recordings with minimal distortion of the ECG waveform. In this paper, we propose a fixed-lag Kalman smoother with adaptive noise estimation. The performance of this Kalman smoother in filtering PLI is compared to that of a fixed-bandwidth notch filter and several adaptive PLI filters that have been proposed in the literature. To evaluate the performance, we corrupted clean neonatal ECG recordings with various simulated PLI. Furthermore, examples are shown of filtering real PLI from an adult and a fetal ECG recording. The fixed-lag Kalman smoother outperforms other PLI filters in terms of step response settling time (improvements that range from 0.1 to 1 s) and signal-to-noise ratio (improvements that range from 17 to 23 dB). Our fixed-lag Kalman smoother can be used for semi real-time applications with a limited delay of 0.4 s. The fixed-lag Kalman smoother presented in this study outperforms other methods for filtering PLI and leads to minimal distortion of the ECG waveform.

  14. High-dynamic range compressive spectral imaging by grayscale coded aperture adaptive filtering

    Directory of Open Access Journals (Sweden)

    Nelson Eduardo Diaz

    2015-12-01

    Full Text Available The coded aperture snapshot spectral imaging system (CASSI is an imaging architecture which senses the three dimensional informa-tion of a scene with two dimensional (2D focal plane array (FPA coded projection measurements. A reconstruction algorithm takes advantage of the compressive measurements sparsity to recover the underlying 3D data cube. Traditionally, CASSI uses block-un-block coded apertures (BCA to spatially modulate the light. In CASSI the quality of the reconstructed images depends on the design of these coded apertures and the FPA dynamic range. This work presents a new CASSI architecture based on grayscaled coded apertu-res (GCA which reduce the FPA saturation and increase the dynamic range of the reconstructed images. The set of GCA is calculated in a real-time adaptive manner exploiting the information from the FPA compressive measurements. Extensive simulations show the attained improvement in the quality of the reconstructed images when GCA are employed.  In addition, a comparison between traditional coded apertures and GCA is realized with respect to noise tolerance.

  15. Non-Maximally Decimated Filter Banks Enable Adaptive Frequency Hopping for Unmanned Aircraft Vehicles

    Science.gov (United States)

    Venosa, Elettra; Vermeire, Bert; Alakija, Cameron; Harris, Fred; Strobel, David; Sheehe, Charles J.; Krunz, Marwan

    2017-01-01

    In the last few years, radio technologies for unmanned aircraft vehicle (UAV) have advanced very rapidly. The increasing need to fly unmanned aircraft systems (UAS) in the national airspace system (NAS) to perform missions of vital importance to national security, defense, and science has pushed ahead the design and implementation of new radio platforms. However, a lot still has to be done to improve those radios in terms of performance and capabilities. In addition, an important aspect to account for is hardware cost and the feasibility to implement these radios using commercial off-the-shelf (COTS) components. UAV radios come with numerous technical challenges and their development involves contributions at different levels of the design. Cognitive algorithms need to be developed in order to perform agile communications using appropriate frequency allocation while maintaining safe and efficient operations in the NAS and, digital reconfigurable architectures have to be designed in order to ensure a prompt response to environmental changes. Command and control (C2) communications have to be preserved during "standard" operations while crew operations have to be minimized. It is clear that UAV radios have to be software-defined systems, where size, weight and power consumption (SWaP) are critical parameters. This paper provides preliminary results of the efforts performed to design a fully digital radio architecture as part of a NASA Phase I STTR. In this paper, we will explain the basic idea and technical principles behind our dynamic/adaptive frequency hopping radio for UAVs. We will present our Simulink model of the dynamic FH radio transmitter design for UAV communications and show simulation results and FPGA system analysis.

  16. The developmental biology of genetic Notch disorders.

    Science.gov (United States)

    Mašek, Jan; Andersson, Emma R

    2017-05-15

    Notch signaling regulates a vast array of crucial developmental processes. It is therefore not surprising that mutations in genes encoding Notch receptors or ligands lead to a variety of congenital disorders in humans. For example, loss of function of Notch results in Adams-Oliver syndrome, Alagille syndrome, spondylocostal dysostosis and congenital heart disorders, while Notch gain of function results in Hajdu-Cheney syndrome, serpentine fibula polycystic kidney syndrome, infantile myofibromatosis and lateral meningocele syndrome. Furthermore, structure-abrogating mutations in NOTCH3 result in CADASIL. Here, we discuss these human congenital disorders in the context of known roles for Notch signaling during development. Drawing on recent analyses by the exome aggregation consortium (EXAC) and on recent studies of Notch signaling in model organisms, we further highlight additional Notch receptors or ligands that are likely to be involved in human genetic diseases. © 2017. Published by The Company of Biologists Ltd.

  17. Notch Signaling and Brain Tumors

    DEFF Research Database (Denmark)

    Stockhausen, Marie; Kristoffersen, Karina; Poulsen, Hans Skovgaard

    2011-01-01

    Human brain tumors are a heterogenous group of neoplasms occurring inside the cranium and the central spinal cord. In adults and children, astrocytic glioma and medulloblastoma are the most common subtypes of primary brain tumors. These tumor types are thought to arise from cells in which Notch...... signaling plays a fundamental role during development. Recent findings have shown that Notch signaling is dysregulated, and contributes to the malignant potential of these tumors. Growing evidence point towards an important role for cancer stem cells in the initiation and maintenance of glioma...... and medulloblastoma. In this chapter we will cover the present findings of Notch signaling in human glioma and medulloblastoma and try to create an overall picture of its relevance in the pathogenesis of these tumors....

  18. Assembly Processes under Severe Abiotic Filtering: Adaptation Mechanisms of Weed Vegetation to the Gradient of Soil Constraints

    Science.gov (United States)

    Nikolic, Nina; Böcker, Reinhard; Kostic-Kravljanac, Ljiljana; Nikolic, Miroslav

    2014-01-01

    Questions Effects of soil on vegetation patterns are commonly obscured by other environmental factors; clear and general relationships are difficult to find. How would community assembly processes be affected by a substantial change in soil characteristics when all other relevant factors are held constant? In particular, can we identify some functional adaptations which would underpin such soil-induced vegetation response? Location Eastern Serbia: fields partially damaged by long-term and large-scale fluvial deposition of sulphidic waste from a Cu mine; subcontinental/submediterranean climate. Methods We analysed the multivariate response of cereal weed assemblages (including biomass and foliar analyses) to a strong man-made soil gradient (from highly calcareous to highly acidic, nutrient-poor soils) over short distances (field scale). Results The soil gradient favoured a substitution of calcicoles by calcifuges, and an increase in abundance of pseudometallophytes, with preferences for Atlantic climate, broad geographical distribution, hemicryptophytic life form, adapted to low-nutrient and acidic soils, with lower concentrations of Ca, and very narrow range of Cu concentrations in leaves. The trends of abundance of the different ecological groups of indicator species along the soil gradient were systematically reflected in the maintenance of leaf P concentrations, and strong homeostasis in biomass N:P ratio. Conclusion Using annual weed vegetation at the field scale as a fairly simple model, we demonstrated links between gradients in soil properties (pH, nutrient availability) and floristic composition that are normally encountered over large geographic distances. We showed that leaf nutrient status, in particular the maintenance of leaf P concentrations and strong homeostasis of biomass N:P ratio, underpinned a clear functional response of vegetation to mineral stress. These findings can help to understand assembly processes leading to unusual, novel combinations

  19. Assembly processes under severe abiotic filtering: adaptation mechanisms of weed vegetation to the gradient of soil constraints.

    Directory of Open Access Journals (Sweden)

    Nina Nikolic

    Full Text Available Effects of soil on vegetation patterns are commonly obscured by other environmental factors; clear and general relationships are difficult to find. How would community assembly processes be affected by a substantial change in soil characteristics when all other relevant factors are held constant? In particular, can we identify some functional adaptations which would underpin such soil-induced vegetation response?Eastern Serbia: fields partially damaged by long-term and large-scale fluvial deposition of sulphidic waste from a Cu mine; subcontinental/submediterranean climate.We analysed the multivariate response of cereal weed assemblages (including biomass and foliar analyses to a strong man-made soil gradient (from highly calcareous to highly acidic, nutrient-poor soils over short distances (field scale.The soil gradient favoured a substitution of calcicoles by calcifuges, and an increase in abundance of pseudometallophytes, with preferences for Atlantic climate, broad geographical distribution, hemicryptophytic life form, adapted to low-nutrient and acidic soils, with lower concentrations of Ca, and very narrow range of Cu concentrations in leaves. The trends of abundance of the different ecological groups of indicator species along the soil gradient were systematically reflected in the maintenance of leaf P concentrations, and strong homeostasis in biomass N:P ratio.Using annual weed vegetation at the field scale as a fairly simple model, we demonstrated links between gradients in soil properties (pH, nutrient availability and floristic composition that are normally encountered over large geographic distances. We showed that leaf nutrient status, in particular the maintenance of leaf P concentrations and strong homeostasis of biomass N:P ratio, underpinned a clear functional response of vegetation to mineral stress. These findings can help to understand assembly processes leading to unusual, novel combinations of species which are typically

  20. Current Conveyor Based Multifunction Filter

    OpenAIRE

    Manish Kumar; Srivastava, M. C.; Umesh Kumar

    2010-01-01

    The paper presents a current conveyor based multifunction filter. The proposed circuit can be realized as low pass, high pass, band pass and elliptical notch filter. The circuit employs two balanced output current conveyors, four resistors and two grounded capacitors, ideal for integration. It has only one output terminal and the number of input terminals may be used. Further, there is no requirement for component matching in the circuit. The parameter resonance frequency (\\omega_0) and bandw...

  1. Frequency selectivity in macaque monkeys measured using a notched-noise method.

    Science.gov (United States)

    Burton, Jane A; Dylla, Margit E; Ramachandran, Ramnarayan

    2017-11-28

    The auditory system is thought to process complex sounds through overlapping bandpass filters. Frequency selectivity as estimated by auditory filters has been well quantified in humans and other mammalian species using behavioral and physiological methodologies, but little work has been done to examine frequency selectivity in nonhuman primates. In particular, knowledge of macaque frequency selectivity would help address the recent controversy over the sharpness of cochlear tuning in humans relative to other animal species. The purpose of our study was to investigate the frequency selectivity of macaque monkeys using a notched-noise paradigm. Four macaques were trained to detect tones in noises that were spectrally notched symmetrically and asymmetrically around the tone frequency. Masked tone thresholds decreased with increasing notch width. Auditory filter shapes were estimated using a rounded exponential function. Macaque auditory filters were symmetric at low noise levels and broader and more asymmetric at higher noise levels with broader low-frequency and steeper high-frequency tails. Macaque filter bandwidths (BW3dB) increased with increasing center frequency, similar to humans and other species. Estimates of equivalent rectangular bandwidth (ERB) and filter quality factor (QERB) suggest macaque filters are broader than human filters. These data shed further light on frequency selectivity across species and serve as a baseline for studies of neuronal frequency selectivity and frequency selectivity in subjects with hearing loss. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. A Simplified Baseband Prefilter Model with Adaptive Kalman Filter for Ultra-Tight COMPASS/INS Integration

    Directory of Open Access Journals (Sweden)

    Bing Luo

    2012-07-01

    Full Text Available COMPASS is an indigenously developed Chinese global navigation satellite system and will share many features in common with GPS (Global Positioning System. Since the ultra-tight GPS/INS (Inertial Navigation System integration shows its advantage over independent GPS receivers in many scenarios, the federated ultra-tight COMPASS/INS integration has been investigated in this paper, particularly, by proposing a simplified prefilter model. Compared with a traditional prefilter model, the state space of this simplified system contains only carrier phase, carrier frequency and carrier frequency rate tracking errors. A two-quadrant arctangent discriminator output is used as a measurement. Since the code tracking error related parameters were excluded from the state space of traditional prefilter models, the code/carrier divergence would destroy the carrier tracking process, and therefore an adaptive Kalman filter algorithm tuning process noise covariance matrix based on state correction sequence was incorporated to compensate for the divergence. The federated ultra-tight COMPASS/INS integration was implemented with a hardware COMPASS intermediate frequency (IF, and INS’s accelerometers and gyroscopes signal sampling system. Field and simulation test results showed almost similar tracking and navigation performances for both the traditional prefilter model and the proposed system; however, the latter largely decreased the computational load.

  3. Assessment of Filtered Back Projection, Adaptive Statistical, and Model-Based Iterative Reconstruction for Reduced Dose Abdominal Computed Tomography.

    Science.gov (United States)

    Padole, Atul; Singh, Sarabjeet; Lira, Diego; Blake, Michael A; Pourjabbar, Sarvenaz; Khawaja, Ranish Deedar Ali; Choy, Garry; Saini, Sanjay; Do, Synho; Kalra, Mannudeep K

    2015-01-01

    To compare standard of care and reduced dose (RD) abdominal computed tomography (CT) images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), model-based iterative reconstruction (MBIR) techniques. In an Institutional Review Board-approved, prospective clinical study, 28 patients (mean age 59 ± 13 years ), undergoing clinically indicated routine abdominal CT on a 64-channel multi-detector CT scanner, gave written informed consent for acquisition of an additional RD (reconstructed with FBP, ASIR, and MBIR and compared with FBP images of standard dose abdomen CT. Two radiologists performed randomized, independent, and blinded comparison for lesion detection, lesion margin, visibility of normal structures, and diagnostic confidence. Mean CT dose index volume was 10 ± 3.4 mGy and 1.3 ± 0.3 mGy for standard and RD CT, respectively. There were 73 "true positive" lesions detected on standard of care CT. Nine lesions (iterative reconstruction techniques used for reconstruction of RD data sets. The visibility of lesion margin was suboptimal in (23/28) patients with RD FBP, (15/28) patients with RD ASIR, and (14/28) patients with RD MBIR compared to standard of care FBP images (P iterative reconstruction techniques. Clinically significant lesions (reconstruction techniques (FBP, ASIR, and MBIR).

  4. Stochastic modelling of aquifer level temporal fluctuations using the Kalman filter adaptation algorithm and an autoregressive exogenous variable model

    Science.gov (United States)

    Varouchakis, Emmanouil

    2017-04-01

    Reliable temporal modelling of groundwater level is significant for efficient water resources management in hydrological basins and for the prevention of possible desertification effects. In this work we propose a stochastic data driven approach of temporal monitoring and prediction that can incorporate auxiliary information. More specifically, we model the temporal (mean annual and biannual) variation of groundwater level by means of a discrete time autoregressive exogenous variable model (ARX model). The ARX model parameters and its predictions are estimated by means of the Kalman filter adaptation algorithm (KFAA). KFAA is suitable for sparsely monitored basins that do not allow for an independent estimation of the ARX model parameters. Three new modified versions of the original form of the ARX model are proposed and investigated: the first considers a larger time scale, the second a larger time delay in terms of the groundwater level input and the third considers the groundwater level difference between the last two hydrological years, which is incorporated in the model as a third input variable. We apply KFAA to time series of groundwater level values from Mires basin in the island of Crete. In addition to precipitation measurements, we use pumping data as exogenous variables. We calibrate the ARX model based on the groundwater level for the years 1981 to 2006 and use it to successfully predict the mean annual and biannual groundwater level for recent years (2007-2010).

  5. Notch Signaling and Brain Tumors

    DEFF Research Database (Denmark)

    Stockhausen, Marie; Kristoffersen, Karina; Poulsen, Hans Skovgaard

    2011-01-01

    Human brain tumors are a heterogenous group of neoplasms occurring inside the cranium and the central spinal cord. In adults and children, astrocytic glioma and medulloblastoma are the most common subtypes of primary brain tumors. These tumor types are thought to arise from cells in which Notch s...

  6. Femoral lntercondylar Notch (ICN) v

    African Journals Online (AJOL)

    Department of Anatomy' and Department of Human Physiology/2. University of Port Harcourt, P.M.B. 5323, Port Harcourt, Nigeria. Department of A natomy'. Nnamdi Azikiwe University, Awka, Anambra State. Summary. We have investigated and measured the Femoral lntercondylar Notch (ICN) width in Nigerians and found ...

  7. A pseudo-matched filter for chaos

    OpenAIRE

    Cohen, Seth D.; Gauthier, Daniel J.

    2012-01-01

    A matched filter maximizes the signal-to-noise ratio of a signal. In the recent work of Corron et al. [Chaos 20, 023123 (2010)], a matched filter is derived for the chaotic waveforms produced by a piecewise-linear system. Motivated by these results, we describe a pseudo-matched filter, which removes noise from the same chaotic signal. It consists of a notch filter followed by a first-order, low-pass filter. We compare quantitatively the matched filter's performance to that of our pseudo-match...

  8. NOTCH pathway inactivation promotes bladder cancer progression

    Science.gov (United States)

    Maraver, Antonio; Fernandez-Marcos, Pablo J.; Cash, Timothy P.; Mendez-Pertuz, Marinela; Dueñas, Marta; Maietta, Paolo; Martinelli, Paola; Muñoz-Martin, Maribel; Martínez-Fernández, Mónica; Cañamero, Marta; Roncador, Giovanna; Martinez-Torrecuadrada, Jorge L.; Grivas, Dimitrios; de la Pompa, Jose Luis; Valencia, Alfonso; Paramio, Jesús M.; Real, Francisco X.; Serrano, Manuel

    2015-01-01

    NOTCH signaling suppresses tumor growth and proliferation in several types of stratified epithelia. Here, we show that missense mutations in NOTCH1 and NOTCH2 found in human bladder cancers result in loss of function. In murine models, genetic ablation of the NOTCH pathway accelerated bladder tumorigenesis and promoted the formation of squamous cell carcinomas, with areas of mesenchymal features. Using bladder cancer cells, we determined that the NOTCH pathway stabilizes the epithelial phenotype through its effector HES1 and, consequently, loss of NOTCH activity favors the process of epithelial-mesenchymal transition. Evaluation of human bladder cancer samples revealed that tumors with low levels of HES1 present mesenchymal features and are more aggressive. Together, our results indicate that NOTCH serves as a tumor suppressor in the bladder and that loss of this pathway promotes mesenchymal and invasive features. PMID:25574842

  9. Adaptive Hybrid Fuzzy-Proportional Plus Crisp-Integral Current Control Algorithm for Shunt Active Power Filter Operation

    Directory of Open Access Journals (Sweden)

    Nor Farahaida Abdul Rahman

    2016-09-01

    Full Text Available An adaptive hybrid fuzzy-proportional plus crisp-integral current control algorithm (CCA for regulating supply current and enhancing the operation of a shunt active power filter (SAPF is presented. It introduces a unique integration of fuzzy-proportional (Fuzzy-P and crisp-integral (Crisp-I current controllers. The Fuzzy-P current controller is developed to perform gain tuning procedure and proportional control action. This controller inherits the simplest configuration; it is constructed using a single-input single-output fuzzy rule configuration. Thus, an execution of few fuzzy rules is sufficient for the controller’s operation. Furthermore, the fuzzy rule is developed using the relationship of currents only. Hence, it simplifies the controller development. Meanwhile, the Crisp-I current controller is developed to perform integral control action using a controllable gain value; to improve the steady-state control mechanism. The gain value is modified and controlled using the Fuzzy-P current controller’s output variable. Therefore, the gain value will continuously be adjusted at every sample period (or throughout the SAPF operation. The effectiveness of the proposed CCA in regulating supply current is validated in both simulation and experimental work. All results have proven that the SAPF using the proposed CCA is capable to regulate supply current during steady-state and dynamic-state operations. At the same time, the SAPF is able to enhance its operation in compensating harmonic currents and reactive power. Furthermore, the implementation of the proposed CCA has resulted more stable dc-link voltage waveform.

  10. On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

    Directory of Open Access Journals (Sweden)

    Mark Frogley

    2013-01-01

    Full Text Available To reduce the maintenance cost, avoid catastrophic failure, and improve the wind transmission system reliability, online condition monitoring system is critical important. In the real applications, many rotating mechanical faults, such as bearing surface defect, gear tooth crack, chipped gear tooth and so on generate impulsive signals. When there are these types of faults developing inside rotating machinery, each time the rotating components pass over the damage point, an impact force could be generated. The impact force will cause a ringing of the support structure at the structural natural frequency. By effectively detecting those periodic impulse signals, one group of rotating machine faults could be detected and diagnosed. However, in real wind turbine operations, impulsive fault signals are usually relatively weak to the background noise and vibration signals generated from other healthy components, such as shaft, blades, gears and so on. Moreover, wind turbine transmission systems work under dynamic operating conditions. This will further increase the difficulties in fault detection and diagnostics. Therefore, developing advanced signal processing methods to enhance the impulsive signals is in great needs.In this paper, an adaptive filtering technique will be applied for enhancing the fault impulse signals-to-noise ratio in wind turbine gear transmission systems. Multiple statistical features designed to quantify the impulsive signals of the processed signal are extracted for bearing fault detection. The multiple dimensional features are then transformed into one dimensional feature. A minimum error rate classifier will be designed based on the compressed feature to identify the gear transmission system with defect. Real wind turbine vibration signals will be used to demonstrate the effectiveness of the presented methodology.

  11. Comparison of image quality between filtered back-projection and the adaptive statistical and novel model-based iterative reconstruction techniques in abdominal CT for renal calculi

    OpenAIRE

    Vardhanabhuti, Varut; Ilyas, Sumaira; Gutteridge, Catherine; Freeman, Simon J.; Roobottom, Carl A

    2013-01-01

    Objectives To compare image quality on computed tomographic (CT) images acquired with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) techniques in CT kidney/ureter/bladder (KUB) examination. Methods Eighteen patients underwent standard protocol CT KUB at our institution. The same raw data were reconstructed using FBP, ASIR and MBIR. Objective [mean image noise, contrast-to-noise ratio (CNR) for kidney and me...

  12. Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar. Thesis Technical Report No. 20

    Science.gov (United States)

    Lai, Jonathan Y.

    1994-01-01

    This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

  13. Adaptive HIFU noise cancellation for simultaneous therapy and imaging using an integrated HIFU/imaging transducer

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Jong Seob; Cannata, Jonathan Matthew; Shung, K Kirk [Department of Biomedical Engineering, NIH Resource Center for Medical Ultrasonic Transducer Technology, University of Southern California, Los Angeles, CA (United States)], E-mail: jongsjeo@usc.edu

    2010-04-07

    It was previously demonstrated that it is feasible to simultaneously perform ultrasound therapy and imaging of a coagulated lesion during treatment with an integrated transducer that is capable of high intensity focused ultrasound (HIFU) and B-mode ultrasound imaging. It was found that coded excitation and fixed notch filtering upon reception could significantly reduce interference caused by the therapeutic transducer. During HIFU sonication, the imaging signal generated with coded excitation and fixed notch filtering had a range side-lobe level of less than -40 dB, while traditional short-pulse excitation and fixed notch filtering produced a range side-lobe level of -20 dB. The shortcoming is, however, that relatively complicated electronics may be needed to utilize coded excitation in an array imaging system. It is for this reason that in this paper an adaptive noise canceling technique is proposed to improve image quality by minimizing not only the therapeutic interference, but also the remnant side-lobe 'ripples' when using the traditional short-pulse excitation. The performance of this technique was verified through simulation and experiments using a prototype integrated HIFU/imaging transducer. Although it is known that the remnant ripples are related to the notch attenuation value of the fixed notch filter, in reality, it is difficult to find the optimal notch attenuation value due to the change in targets or the media resulted from motion or different acoustic properties even during one sonication pulse. In contrast, the proposed adaptive noise canceling technique is capable of optimally minimizing both the therapeutic interference and residual ripples without such constraints. The prototype integrated HIFU/imaging transducer is composed of three rectangular elements. The 6 MHz center element is used for imaging and the outer two identical 4 MHz elements work together to transmit the HIFU beam. Two HIFU elements of 14.4 mm x 20.0 mm dimensions

  14. An auxiliary adaptive Gaussian mixture filter applied to flowrate allocation using real data from a multiphase producer

    Science.gov (United States)

    Lorentzen, Rolf J.; Stordal, Andreas S.; Hewitt, Neal

    2017-05-01

    Flowrate allocation in production wells is a complicated task, especially for multiphase flow combined with several reservoir zones and/or branches. The result depends heavily on the available production data, and the accuracy of these. In the application we show here, downhole pressure and temperature data are available, in addition to the total flowrates at the wellhead. The developed methodology inverts these observations to the fluid flowrates (oil, water and gas) that enters two production branches in a real full-scale producer. A major challenge is accurate estimation of flowrates during rapid variations in the well, e.g. due to choke adjustments. The Auxiliary Sequential Importance Resampling (ASIR) filter was developed to handle such challenges, by introducing an auxiliary step, where the particle weights are recomputed (second weighting step) based on how well the particles reproduce the observations. However, the ASIR filter suffers from large computational time when the number of unknown parameters increase. The Gaussian Mixture (GM) filter combines a linear update, with the particle filters ability to capture non-Gaussian behavior. This makes it possible to achieve good performance with fewer model evaluations. In this work we present a new filter which combines the ASIR filter and the Gaussian Mixture filter (denoted ASGM), and demonstrate improved estimation (compared to ASIR and GM filters) in cases with rapid parameter variations, while maintaining reasonable computational cost.

  15. Biaxial Fatigue Cracking from Notch

    Science.gov (United States)

    2013-03-04

    of the central notch. BIAXIAL FATIGUE TEST The biaxial fatigue test was conducted in a MTS 793.10 Multiaxial Purpose Test-Ware with two pairs...of servo -hydraulic actuators and two pairs of load cells, arranged perpendicular to each other on a horizontal plane in a rigid frame, Figure A-1...TR-2009/12, of 19 Feb 2009. NAWCADPAX/TR-2013/32 15 APPENDIX A FIGURES 1. MTS Machine and Cruciform Specimen 2. Effect of Biaxiality

  16. Loss of Notch3 Signaling in Vascular Smooth Muscle Cells Promotes Severe Heart Failure Upon Hypertension.

    Science.gov (United States)

    Ragot, Hélène; Monfort, Astrid; Baudet, Mathilde; Azibani, Fériel; Fazal, Loubina; Merval, Régine; Polidano, Evelyne; Cohen-Solal, Alain; Delcayre, Claude; Vodovar, Nicolas; Chatziantoniou, Christos; Samuel, Jane-Lise

    2016-08-01

    Hypertension, which is a risk factor of heart failure, provokes adaptive changes at the vasculature and cardiac levels. Notch3 signaling plays an important role in resistance arteries by controlling the maturation of vascular smooth muscle cells. Notch3 deletion is protective in pulmonary hypertension while deleterious in arterial hypertension. Although this latter phenotype was attributed to renal and cardiac alterations, the underlying mechanisms remained unknown. To investigate the role of Notch3 signaling in the cardiac adaptation to hypertension, we used mice with either constitutive Notch3 or smooth muscle cell-specific conditional RBPJκ knockout. At baseline, both genotypes exhibited a cardiac arteriolar rarefaction associated with oxidative stress. In response to angiotensin II-induced hypertension, the heart of Notch3 knockout and SM-RBPJκ knockout mice did not adapt to pressure overload and developed heart failure, which could lead to an early and fatal acute decompensation of heart failure. This cardiac maladaptation was characterized by an absence of media hypertrophy of the media arteries, the transition of smooth muscle cells toward a synthetic phenotype, and an alteration of angiogenic pathways. A subset of mice exhibited an early fatal acute decompensated heart failure, in which the same alterations were observed, although in a more rapid timeframe. Altogether, these observations indicate that Notch3 plays a major role in coronary adaptation to pressure overload. These data also show that the hypertrophy of coronary arterial media on pressure overload is mandatory to initially maintain a normal cardiac function and is regulated by the Notch3/RBPJκ pathway. © 2016 American Heart Association, Inc.

  17. An optical catalog of galaxy clusters obtained from an adaptive matched filter finder applied to SDSS DR9 data

    Science.gov (United States)

    Banerjee, P.; Szabo, T.; Pierpaoli, E.; Franco, G.; Ortiz, M.; Oramas, A.; Tornello, B.

    2018-01-01

    We present a new galaxy cluster catalog constructed from the Sloan Digital Sky Survey Data Release 9 (SDSS DR9) using an Adaptive Matched Filter (AMF) technique. Our catalog has 46,479 galaxy clusters with richness Λ200 > 20 in the redshift range 0.045 ≤ z clusters, as well as their error analysis, are provided as part of this catalog. In addition to the main version of the catalog, we also provide an extended version with a lower richness cut, containing 79,368 clusters. This version, in addition to the clusters in the main catalog, also contains those clusters (with richness 10 cluster membership for each galaxy and implement several procedures for the identification and removal of false cluster detections. We cross-correlate the main AMF DR9 catalog with a number of cluster catalogs in different wavebands (Optical, X-ray). We compare our catalog with other SDSS-based ones such as the redMaPPer (26,350 clusters) and the Wen et al. (WHL) (132,684 clusters) in the same area of the sky and in the overlapping redshift range. We match 97% of the richest Abell clusters (Richness group 3), the same as WHL, while redMaPPer matches ∼ 90% of these clusters. Considering AMF DR9 richness bins, redMaPPer does not have one-to-one matches for 70% of our lowest richness clusters (20 clusters (not present in redMaPPer). redMaPPer consistently does not possess one-to-one matches for ∼ 20% AMF DR9 clusters with Λ200 > 40, while WHL matches ≥ 70% of these missed clusters on average. For comparisons with X-ray clusters, we match the AMF catalog with BAX, MCXC and a combined catalog from NORAS and REFLEX. We consistently obtain a greater number of one-to-one matches for X-ray clusters across higher luminosity bins (Lx > 6 × 1044 ergs/sec) than redMaPPer while WHL matches the most clusters overall. For the most luminous clusters (Lx > 8), our catalog performs equivalently to WHL. This new catalog provides a wider sample than redMaPPer while retaining many fewer objects than

  18. All-adaptive blind matched filtering for the equalization and identification of multipath channels: a practical approach

    OpenAIRE

    Coskun, A.; Kale, I.

    2012-01-01

    Blind matched filter receiver is advantageous over the state-of-the-art blind schemes due the simplicity in its implementation. To estimate the multipath communication channels, it uses neither any matrix decomposition methods nor statistics of the received data higher than the second order ones. On the other hand, the realization of the conventional blind matched filter receiver requires the noise variance to be estimated and the equalizer parameters to be calculated in state-space with rela...

  19. Adaptive Filtering Technique and Comparison of PS25015A Dry Electrodes and Two Different Ag/AgCl Wet Electrodes for Wearable ECG Applications

    Directory of Open Access Journals (Sweden)

    Nika ZOLFAGHARI

    2015-01-01

    Full Text Available The electrocardiogram (ECG is one of the most important signals acquired from the body, as it serves as the immediate source of information relating to heart performance. Hence, a lot of research has gone into various types of ECG acquisition methods and systems. With the numerous methods and systems available at hand, it is important to compare, contrast, and evaluate the existing techniques. Not only does this help distinguish between the different techniques, it also helps build on the existing methods to create successful acquisition systems that can surpass the effect of unwanted factors, such as movement and other noise artifacts. This paper builds on a previous study that compared two different ECG acquisition systems, one of which uses PS25015A dry electrodes and the other, which uses two different silver/silver chloride (Ag/AgCl wet electrodes. The adaptive filtering technique was implemented in order to test its effectiveness when applied to a wearable ECG medical device, intended to monitor the user’s ECG throughout daily activities, such as walking. According to statistical analysis, the dry electrodes may have a better SNR. However, the dry electrodes provided a lower wave amplitude, compared to the wet electrodes. Overall, the least mean squares (LMS adaptive filtering, along with bandpass filtering, helped reduce motion artifacts in ECG signals acquired during walking.

  20. Study of the Algorithm of Backtracking Decoupling and Adaptive Extended Kalman Filter Based on the Quaternion Expanded to the State Variable for Underwater Glider Navigation

    Directory of Open Access Journals (Sweden)

    Haoqian Huang

    2014-12-01

    Full Text Available High accuracy attitude and position determination is very important for underwater gliders. The cross-coupling among three attitude angles (heading angle, pitch angle and roll angle becomes more serious when pitch or roll motion occurs. This cross-coupling makes attitude angles inaccurate or even erroneous. Therefore, the high accuracy attitude and position determination becomes a difficult problem for a practical underwater glider. To solve this problem, this paper proposes backing decoupling and adaptive extended Kalman filter (EKF based on the quaternion expanded to the state variable (BD-AEKF. The backtracking decoupling can eliminate effectively the cross-coupling among the three attitudes when pitch or roll motion occurs. After decoupling, the adaptive extended Kalman filter (AEKF based on quaternion expanded to the state variable further smoothes the filtering output to improve the accuracy and stability of attitude and position determination. In order to evaluate the performance of the proposed BD-AEKF method, the pitch and roll motion are simulated and the proposed method performance is analyzed and compared with the traditional method. Simulation results demonstrate the proposed BD-AEKF performs better. Furthermore, for further verification, a new underwater navigation system is designed, and the three-axis non-magnetic turn table experiments and the vehicle experiments are done. The results show that the proposed BD-AEKF is effective in eliminating cross-coupling and reducing the errors compared with the conventional method.

  1. Study of the algorithm of backtracking decoupling and adaptive extended Kalman filter based on the quaternion expanded to the state variable for underwater glider navigation.

    Science.gov (United States)

    Huang, Haoqian; Chen, Xiyuan; Zhou, Zhikai; Xu, Yuan; Lv, Caiping

    2014-12-03

    High accuracy attitude and position determination is very important for underwater gliders. The cross-coupling among three attitude angles (heading angle, pitch angle and roll angle) becomes more serious when pitch or roll motion occurs. This cross-coupling makes attitude angles inaccurate or even erroneous. Therefore, the high accuracy attitude and position determination becomes a difficult problem for a practical underwater glider. To solve this problem, this paper proposes backing decoupling and adaptive extended Kalman filter (EKF) based on the quaternion expanded to the state variable (BD-AEKF). The backtracking decoupling can eliminate effectively the cross-coupling among the three attitudes when pitch or roll motion occurs. After decoupling, the adaptive extended Kalman filter (AEKF) based on quaternion expanded to the state variable further smoothes the filtering output to improve the accuracy and stability of attitude and position determination. In order to evaluate the performance of the proposed BD-AEKF method, the pitch and roll motion are simulated and the proposed method performance is analyzed and compared with the traditional method. Simulation results demonstrate the proposed BD-AEKF performs better. Furthermore, for further verification, a new underwater navigation system is designed, and the three-axis non-magnetic turn table experiments and the vehicle experiments are done. The results show that the proposed BD-AEKF is effective in eliminating cross-coupling and reducing the errors compared with the conventional method.

  2. Notch Signaling Enhances Nestin Expression in Gliomas

    Directory of Open Access Journals (Sweden)

    Alan H. Shih

    2006-12-01

    Full Text Available Recent findings suggest that Notch signaling is active in brain tumors and stem cells, and that stem cells or cells with progenitor characteristics contribute to brain tumor formation. These stem cells are marked by expression of several markers, including nestin, an intermediate filament protein. We have studied how the Notch signaling pathway affects nestin expression in brain tumors. We find that Notch receptors and ligands are expressed in vitro and in human samples of glioblastomas, the highest grade of malignant gliomas. In culture, Notch activity activates the nestin promoter. Activation of the Notch pathway also occurs in a glioblastoma multiforme mouse model induced by Kras, with translational regulation playing a role in Notch expression. Combined activation of Notch and Kras in wild-type nestin-expressing cells leads to their expansion within the subventricular zone and retention of proliferation and nestin expression. However, activation of Notch alone is unable to induce this cellular expansion. These data suggest that Notch may have a contributing role in the stem-like character of glioma cells.

  3. Adaptive Slope Filtering of Airborne LiDAR Data in Urban Areas for Digital Terrain Model (DTM Generation

    Directory of Open Access Journals (Sweden)

    Junichi Susaki

    2012-06-01

    Full Text Available A filtering algorithm is proposed that accurately extracts ground data from airborne light detection and ranging (LiDAR measurements and generates an estimated digital terrain model (DTM. The proposed algorithm utilizes planar surface features and connectivity with locally lowest points to improve the extraction of ground points (GPs. A slope parameter used in the proposed algorithm is updated after an initial estimation of the DTM, and thus local terrain information can be included. As a result, the proposed algorithm can extract GPs from areas where different degrees of slope variation are interspersed. Specifically, along roads and streets, GPs were extracted from urban areas, from hilly areas such as forests, and from flat area such as riverbanks. Validation using reference data showed that, compared with commercial filtering software, the proposed algorithm extracts GPs with higher accuracy. Therefore, the proposed filtering algorithm effectively generates DTMs, even for dense urban areas, from airborne LiDAR data.

  4. Notching on cancer’s door: Notch signaling in brain tumors

    Directory of Open Access Journals (Sweden)

    Marcin eTeodorczyk

    2015-01-01

    Full Text Available Notch receptors play an essential role in the regulation of central cellular processes during embryonic and postnatal development. The mammalian genome encodes for four Notch paralogs (Notch 1-4, which are activated by three Delta-like (Dll1/3/4 and two Serrate-like (Jagged1/2 ligands. Further, non-canonical Notch ligands such as EGFL7 have been identified and serve mostly as antagonists of Notch signaling. The Notch pathway prevents neuronal differentiation in the central nervous system by driving neural stem cell maintenance and commitment of neural progenitor cells into the glial lineage. Notch is therefore often implicated in the development of brain tumors, as tumor cells share various characteristics with neural stem and progenitor cells. Notch receptors are overexpressed in gliomas and their oncogenicity has been confirmed by gain- and loss-of-function studies in vitro and in vivo. To this end, special attention is paid to the impact of Notch signaling on stem-like brain tumor-propagating cells as these cells contribute to growth, survival, invasion and recurrence of brain tumors. Based on the outcome of ongoing studies in vivo, Notch-directed therapies such as γ secretase inhibitors and blocking antibodies have entered and completed various clinical trials. This review summarizes the current knowledge on Notch signaling in brain tumor formation and therapy.

  5. Fermoral Intercondylar Notch Geometry Of Nigerians | Didia ...

    African Journals Online (AJOL)

    The notch geometry had been implicated in anterior cruciate ligament (ACL) injuries and from this study we presume that the difference in incidence of ACL injuries between males and females is as a result of differences in intercondylar notch width index and the diameter of distal end of femur in both sexes. KEY WORDS: ...

  6. Very Fast Algorithms and Detection Performance of Multi-Channel and 2-D Parametric Adaptive Matched Filters for Airborne Radar

    Science.gov (United States)

    2007-06-05

    of the PAMF approach is very close to the ideal matched filter (MF) detection statistics under exactly known covari- ance (the clairvoyant case...PERFORMANCE MEASURE: dB offset to right of ideal MF clairvoyant response (shown on next slide) at Pd of 0.5 (represents roughly the performance degradation

  7. Notch filtering the nuclear environment of a spin qubit

    DEFF Research Database (Denmark)

    Malinowski, F. K.; Martins, F.; Nissen, P. D.

    2016-01-01

    Electron spins in gate-defined quantum dots provide a promising platform for quantum computation. In particular, spin-based quantum computing in gallium arsenide takes advantage of the high quality of semiconducting materials, reliability in fabricating arrays of quantum dots, and accurate qubit ...

  8. Optical bistability in a nonlinear photonic crystal waveguide notch filter

    NARCIS (Netherlands)

    Stoffer, Remco; Kivshar, Yu. S.; Leijtens, X.J.M.; Besten, J.H.

    2000-01-01

    Optical bistability occurs when the effects of nonlinear behaviour of materials cause hysteresis in the transmission and reflection of a device. A possible mechanism for this is a strong dependence of the optical intensity on the index of refraction, e.g. in a cavity near resonance. In a 2-

  9. Multi-rate cubature Kalman filter based data fusion method with residual compensation to adapt to sampling rate discrepancy in attitude measurement system

    Science.gov (United States)

    Guo, Xiaoting; Sun, Changku; Wang, Peng

    2017-08-01

    This paper investigates the multi-rate inertial and vision data fusion problem in nonlinear attitude measurement systems, where the sampling rate of the inertial sensor is much faster than that of the vision sensor. To fully exploit the high frequency inertial data and obtain favorable fusion results, a multi-rate CKF (Cubature Kalman Filter) algorithm with estimated residual compensation is proposed in order to adapt to the problem of sampling rate discrepancy. During inter-sampling of slow observation data, observation noise can be regarded as infinite. The Kalman gain is unknown and approaches zero. The residual is also unknown. Therefore, the filter estimated state cannot be compensated. To obtain compensation at these moments, state error and residual formulas are modified when compared with the observation data available moments. Self-propagation equation of the state error is established to propagate the quantity from the moments with observation to the moments without observation. Besides, a multiplicative adjustment factor is introduced as Kalman gain, which acts on the residual. Then the filter estimated state can be compensated even when there are no visual observation data. The proposed method is tested and verified in a practical setup. Compared with multi-rate CKF without residual compensation and single-rate CKF, a significant improvement is obtained on attitude measurement by using the proposed multi-rate CKF with inter-sampling residual compensation. The experiment results with superior precision and reliability show the effectiveness of the proposed method.

  10. Multi-rate cubature Kalman filter based data fusion method with residual compensation to adapt to sampling rate discrepancy in attitude measurement system.

    Science.gov (United States)

    Guo, Xiaoting; Sun, Changku; Wang, Peng

    2017-08-01

    This paper investigates the multi-rate inertial and vision data fusion problem in nonlinear attitude measurement systems, where the sampling rate of the inertial sensor is much faster than that of the vision sensor. To fully exploit the high frequency inertial data and obtain favorable fusion results, a multi-rate CKF (Cubature Kalman Filter) algorithm with estimated residual compensation is proposed in order to adapt to the problem of sampling rate discrepancy. During inter-sampling of slow observation data, observation noise can be regarded as infinite. The Kalman gain is unknown and approaches zero. The residual is also unknown. Therefore, the filter estimated state cannot be compensated. To obtain compensation at these moments, state error and residual formulas are modified when compared with the observation data available moments. Self-propagation equation of the state error is established to propagate the quantity from the moments with observation to the moments without observation. Besides, a multiplicative adjustment factor is introduced as Kalman gain, which acts on the residual. Then the filter estimated state can be compensated even when there are no visual observation data. The proposed method is tested and verified in a practical setup. Compared with multi-rate CKF without residual compensation and single-rate CKF, a significant improvement is obtained on attitude measurement by using the proposed multi-rate CKF with inter-sampling residual compensation. The experiment results with superior precision and reliability show the effectiveness of the proposed method.

  11. Characterization of Notch1 antibodies that inhibit signaling of both normal and mutated Notch1 receptors.

    Directory of Open Access Journals (Sweden)

    Miguel Aste-Amézaga

    2010-02-01

    Full Text Available Notch receptors normally play a key role in guiding a variety of cell fate decisions during development and differentiation of metazoan organisms. On the other hand, dysregulation of Notch1 signaling is associated with many different types of cancer as well as tumor angiogenesis, making Notch1 a potential therapeutic target.Here we report the in vitro activities of inhibitory Notch1 monoclonal antibodies derived from cell-based and solid-phase screening of a phage display library. Two classes of antibodies were found, one directed against the EGF-repeat region that encompasses the ligand-binding domain (LBD, and the second directed against the activation switch of the receptor, the Notch negative regulatory region (NRR. The antibodies are selective for Notch1, inhibiting Jag2-dependent signaling by Notch1 but not by Notch 2 and 3 in reporter gene assays, with EC(50 values as low as 5+/-3 nM and 0.13+/-0.09 nM for the LBD and NRR antibodies, respectively, and fail to recognize Notch4. While more potent, NRR antibodies are incomplete antagonists of Notch1 signaling. The antagonistic activity of LBD, but not NRR, antibodies is strongly dependent on the activating ligand. Both LBD and NRR antibodies bind to Notch1 on human tumor cell lines and inhibit the expression of sentinel Notch target genes, including HES1, HES5, and DTX1. NRR antibodies also strongly inhibit ligand-independent signaling in heterologous cells transiently expressing Notch1 receptors with diverse NRR "class I" point mutations, the most common type of mutation found in human T-cell acute lymphoblastic leukemia (T-ALL. In contrast, NRR antibodies failed to antagonize Notch1 receptors bearing rare "class II" or "class III" mutations, in which amino acid insertions generate a duplicated or constitutively sensitive metalloprotease cleavage site. Signaling in T-ALL cell lines bearing class I mutations is partially refractory to inhibitory antibodies as compared to cell

  12. Noninvasive Fetal Heart Rate Monitoring: Validation of Phonocardiography-Based Fiber-Optic Sensing and Adaptive Filtering Using the NLMS Algorithm

    Directory of Open Access Journals (Sweden)

    Jan Nedoma

    2017-01-01

    Full Text Available Here we present the evaluation results of our novel noninvasive phonocardiographic-based fiber-optic sensor for fetal Heart Rate (fHR detection using adaptive filtering and the NLMS Algorithm. The sensor uses two interferometric probes encapsulated inside a PolyDiMethylSiloxane (PDMS polymer. Based on real data acquired from pregnant women in a suitable research laboratory environment, once they had given their written informed consents, we created a simplified dynamic signal model of the distribution of maternal and fetal heart sounds inside the maternal body. Building upon this signal model, we verified the functionality of our novel fiber-optic sensor and its associated adaptive filtering system using the NLMS Algorithm. The main reason why we chose this technology to develop our system was that it allows monitoring the fHR without exposing the fetus to any external energies or radiation (in contrast to the ultrasound-based Cardiotocography Method. We used objective criteria such as: Signal to Noise Ratios: SNR_in, SNR_out and Percentage Root-mean-square Difference (PRD for our evaluations.

  13. Performance Enhancement of a USV INS/CNS/DVL Integration Navigation System Based on an Adaptive Information Sharing Factor Federated Filter.

    Science.gov (United States)

    Wang, Qiuying; Cui, Xufei; Li, Yibing; Ye, Fang

    2017-02-03

    To improve the ability of autonomous navigation for Unmanned Surface Vehicles (USVs), multi-sensor integrated navigation based on Inertial Navigation System (INS), Celestial Navigation System (CNS) and Doppler Velocity Log (DVL) is proposed. The CNS position and the DVL velocity are introduced as the reference information to correct the INS divergence error. The autonomy of the integrated system based on INS/CNS/DVL is much better compared with the integration based on INS/GNSS alone. However, the accuracy of DVL velocity and CNS position are decreased by the measurement noise of DVL and bad weather, respectively. Hence, the INS divergence error cannot be estimated and corrected by the reference information. To resolve the problem, the Adaptive Information Sharing Factor Federated Filter (AISFF) is introduced to fuse data. The information sharing factor of the Federated Filter is adaptively adjusted to maintaining multiple component solutions usable as back-ups, which can improve the reliability of overall system. The effectiveness of this approach is demonstrated by simulation and experiment, the results show that for the INS/CNS/DVL integrated system, when the DVL velocity accuracy is decreased and the CNS cannot work under bad weather conditions, the INS/CNS/DVL integrated system can operate stably based on the AISFF method.

  14. Performance Enhancement of a USV INS/CNS/DVL Integration Navigation System Based on an Adaptive Information Sharing Factor Federated Filter

    Directory of Open Access Journals (Sweden)

    Qiuying Wang

    2017-02-01

    Full Text Available To improve the ability of autonomous navigation for Unmanned Surface Vehicles (USVs, multi-sensor integrated navigation based on Inertial Navigation System (INS, Celestial Navigation System (CNS and Doppler Velocity Log (DVL is proposed. The CNS position and the DVL velocity are introduced as the reference information to correct the INS divergence error. The autonomy of the integrated system based on INS/CNS/DVL is much better compared with the integration based on INS/GNSS alone. However, the accuracy of DVL velocity and CNS position are decreased by the measurement noise of DVL and bad weather, respectively. Hence, the INS divergence error cannot be estimated and corrected by the reference information. To resolve the problem, the Adaptive Information Sharing Factor Federated Filter (AISFF is introduced to fuse data. The information sharing factor of the Federated Filter is adaptively adjusted to maintaining multiple component solutions usable as back-ups, which can improve the reliability of overall system. The effectiveness of this approach is demonstrated by simulation and experiment, the results show that for the INS/CNS/DVL integrated system, when the DVL velocity accuracy is decreased and the CNS cannot work under bad weather conditions, the INS/CNS/DVL integrated system can operate stably based on the AISFF method.

  15. Tunable Multifunction Filter Using Current Conveyor

    OpenAIRE

    Manish Kumar; Srivastava, M. C.; Umesh Kumar

    2010-01-01

    The paper presents a current tunable multifunction filter using current conveyor. The proposed circuit can be realized as on chip tunable low pass, high pass, band pass and elliptical notch filter. The circuit employs two current conveyors, one OTA, four resistors and two grounded capacitors, ideal for integration. It has only one output terminal and the number of input terminals may be used. Further, there is no requirement for component matching in the circuit. The resonance frequency ({\\om...

  16. Notch and the awesome power of genetics.

    Science.gov (United States)

    Greenwald, Iva

    2012-07-01

    Notch is a receptor that mediates cell-cell interactions in animal development, and aberrations in Notch signal transduction can cause cancer and other human diseases. Here, I describe the major advances in the Notch field from the identification of the first mutant in Drosophila almost a century ago through the elucidation of the unusual mechanism of signal transduction a little over a decade ago. As an essay for the GENETICS Perspectives series, it is my personal and critical commentary as well as an historical account of discovery.

  17. Relaxed Bi - Quadratic Optimization For Joint Filter Signal Design In Signal Dependent Space Time Adaptive Processing (STAP) (Preprint)

    Science.gov (United States)

    2016-11-16

    the following function P(fd, θ) = |wHo (v(fd)⊗ soa (θ, φ)|2. (59) That is, the adapted pattern for a given beamformer-signal pair wo, so is a function...public release; distribution is unlimited. 13. SUPPLEMENTARY NOTES The U.S. Government is joint author of the work and has the right to use, modify...subspace alignment and the overall adapted pattern . 48 Approved for public release; distribution is unlimited. S. M. O’ROURKE, ET AL.: AFRL SENSORS

  18. Variable Delay With Directly-Modulated R-SOA and Optical Filters for Adaptive Antenna Radio-Fiber Access

    DEFF Research Database (Denmark)

    Prince, Kamau; Presi, Marco; Chiuchiarelli, Andrea

    2009-01-01

    We present an all-optical adaptive-antenna radio over fiber transport system that uses proven, commercially-available components to effectively deliver standard-compliant optical signaling to adaptive multiantenna arrays for current and emerging radio technology implementations. The system is based...... types of signals defined in IEEE 802.16 (WiMAX) standard for wireless networks: a 90 Mbps single-carrier signal (64-QAM at 2.4 GHz) and a 78 Mbps multitone orthogonal frequency-division multiple access (OFDMA) signal. The power budget of this configuration supports a 4-element antenna array....

  19. LMS filter for noise cancellation using Simulink

    Science.gov (United States)

    Talele, K. T.; Shrivastav, Ashish; Utekar, Kunal; Deshpande, Abhishek

    2011-06-01

    In this paper we have proposed the simplified implementation of adaptive noise cancellation using LMS filter. The LMS algorithm belongs to the family of stochastic gradient algorithms. It is one of the efficient algorithms in adaptive filtering.

  20. Notch signaling in embryology and cancer

    National Research Council Canada - National Science Library

    Reichrath, J; Reichrath, Sandra

    2012-01-01

    "The goal of this volume is to comprehensively cover a highly readable overview on our present knowledge of the role of Notch signalling for embryology and cancer, with a focus on new findings in molecular biology...

  1. Adaptive spatial filtering for off-axis digital holographic microscopy based on region recognition approach with iterative thresholding

    Science.gov (United States)

    He, Xuefei; Nguyen, Chuong Vinh; Pratap, Mrinalini; Zheng, Yujie; Wang, Yi; Nisbet, David R.; Rug, Melanie; Maier, Alexander G.; Lee, Woei Ming

    2016-12-01

    Here we propose a region-recognition approach with iterative thresholding, which is adaptively tailored to extract the appropriate region or shape of spatial frequency. In order to justify the method, we tested it with different samples and imaging conditions (different objectives). We demonstrate that our method provides a useful method for rapid imaging of cellular dynamics in microfluidic and cell cultures.

  2. Filtered stochastic calculus

    OpenAIRE

    Lenczewski, Romuald

    2001-01-01

    By introducing a color filtration to the multiplicity space, we extend the quantum Ito calculus on multiple symmetric Fock space to the framework of filtered adapted biprocesses. In this new notion of adaptedness,``classical'' time filtration makes the integrands similar to adapted processes, whereas ``quantum'' color filtration produces their deviations from adaptedness. An important feature of this calculus, which we call filtered stochastic calculus, is that it provides an explicit interpo...

  3. Modified compensation algorithm of lever-arm effect and flexural deformation for polar shipborne transfer alignment based on improved adaptive Kalman filter

    Science.gov (United States)

    Wang, Tongda; Cheng, Jianhua; Guan, Dongxue; Kang, Yingyao; Zhang, Wei

    2017-09-01

    Due to the lever-arm effect and flexural deformation in the practical application of transfer alignment (TA), the TA performance is decreased. The existing polar TA algorithm only compensates a fixed lever-arm without considering the dynamic lever-arm caused by flexural deformation; traditional non-polar TA algorithms also have some limitations. Thus, the performance of existing compensation algorithms is unsatisfactory. In this paper, a modified compensation algorithm of the lever-arm effect and flexural deformation is proposed to promote the accuracy and speed of the polar TA. On the basis of a dynamic lever-arm model and a noise compensation method for flexural deformation, polar TA equations are derived in grid frames. Based on the velocity-plus-attitude matching method, the filter models of polar TA are designed. An adaptive Kalman filter (AKF) is improved to promote the robustness and accuracy of the system, and then applied to the estimation of the misalignment angles. Simulation and experiment results have demonstrated that the modified compensation algorithm based on the improved AKF for polar TA can effectively compensate the lever-arm effect and flexural deformation, and then improve the accuracy and speed of TA in the polar region.

  4. On-board adaptive model for state of charge estimation of lithium-ion batteries based on Kalman filter with proportional integral-based error adjustment

    Science.gov (United States)

    Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai

    2017-10-01

    With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.

  5. Comparing model-based adaptive LMS filters and a model-free hysteresis loop analysis method for structural health monitoring

    Science.gov (United States)

    Zhou, Cong; Chase, J. Geoffrey; Rodgers, Geoffrey W.; Xu, Chao

    2017-02-01

    The model-free hysteresis loop analysis (HLA) method for structural health monitoring (SHM) has significant advantages over the traditional model-based SHM methods that require a suitable baseline model to represent the actual system response. This paper provides a unique validation against both an experimental reinforced concrete (RC) building and a calibrated numerical model to delineate the capability of the model-free HLA method and the adaptive least mean squares (LMS) model-based method in detecting, localizing and quantifying damage that may not be visible, observable in overall structural response. Results clearly show the model-free HLA method is capable of adapting to changes in how structures transfer load or demand across structural elements over time and multiple events of different size. However, the adaptive LMS model-based method presented an image of greater spread of lesser damage over time and story when the baseline model is not well defined. Finally, the two algorithms are tested over a simpler hysteretic behaviour typical steel structure to quantify the impact of model mismatch between the baseline model used for identification and the actual response. The overall results highlight the need for model-based methods to have an appropriate model that can capture the observed response, in order to yield accurate results, even in small events where the structure remains linear.

  6. The role of Notch in the cardiovascular system: potential adverse effects of investigational Notch inhibitors

    Directory of Open Access Journals (Sweden)

    Paola eRizzo

    2015-01-01

    Full Text Available Targeting the Notch pathway is a new promising therapeutic approach for cancer patients. Inhibition of Notch is effective in the oncology setting because it causes a reduction of highly proliferative tumor cells and it inhibits survival of cancer stem cells which are considered responsible for tumor recurrence and metastasis. Additionally, since Delta- like ligand 4 (Dll4- activated Notch signalling is a major modulator of angiogenesis, anti-Dll4 agents are being investigated to reduce vascularization of the tumor. Notch plays a major role in the heart during the development and, after birth, in response to cardiac damage. Therefore, agents used to inhibit Notch in the tumors (gamma secretase inhibitors and anti-Dll4 agents could potentially affect myocardial repair. The past experience with trastuzumab and other tyrosine kinase inhibitors used for cancer therapy demonstrates that the possible cardiotoxicity of agents targeting shared pathways between cancer and heart and the vasculature should be considered. To date, Notch inhibition in cancer patients has resulted only in mild gastrointestinal toxicity. Little is known about the potential long term cardiotoxicity associated to Notch inhibition in cancer patients. In this review we will focus on mechanisms through which inhibition of Notch signalling could lead to cardiomyocytes and endothelial dysfunctions. These adverse effects could contrast with the benefits of therapeutic responses in cancer cells during times of increased cardiac stress and/or in the presence of cardiovascular risk factor

  7. Hessian-LoG filtering for enhancement and detection of photoreceptor cells in adaptive optics retinal images.

    Science.gov (United States)

    Lazareva, Anfisa; Liatsis, Panos; Rauscher, Franziska G

    2016-01-01

    Automated analysis of retinal images plays a vital role in the examination, diagnosis, and prognosis of healthy and pathological retinas. Retinal disorders and the associated visual loss can be interpreted via quantitative correlations, based on measurements of photoreceptor loss. Therefore, it is important to develop reliable tools for identification of photoreceptor cells. In this paper, an automated algorithm is proposed, based on the use of the Hessian-Laplacian of Gaussian filter, which allows enhancement and detection of photoreceptor cells. The performance of the proposed technique is evaluated on both synthetic and high-resolution retinal images, in terms of packing density. The results on the synthetic data were compared against ground truth as well as cone counts obtained by the Li and Roorda algorithm. For the synthetic datasets, our method showed an average detection accuracy of 98.8%, compared to 93.9% for the Li and Roorda approach. The packing density estimates calculated on the retinal datasets were validated against manual counts and the results obtained by a proprietary software from Imagine Eyes and the Li and Roorda algorithm. Among the tested methods, the proposed approach showed the closest agreement with manual counting.

  8. [Adaptive Wiener filter based on Gaussian mixture distribution model for denoising chest X-ray CT image].

    Science.gov (United States)

    Tabuchi, Motohiro; Yamane, Nobumoto; Morikawa, Yoshitaka

    2008-05-20

    In recent decades, X-ray CT imaging has become more important as a result of its high-resolution performance. However, it is well known that the X-ray dose is insufficient in the techniques that use low-dose imaging in health screening or thin-slice imaging in work-up. Therefore, the degradation of CT images caused by the streak artifact frequently becomes problematic. In this study, we applied a Wiener filter (WF) using the universal Gaussian mixture distribution model (UNI-GMM) as a statistical model to remove streak artifact. In designing the WF, it is necessary to estimate the statistical model and the precise co-variances of the original image. In the proposed method, we obtained a variety of chest X-ray CT images using a phantom simulating a chest organ, and we estimated the statistical information using the images for training. The results of simulation showed that it is possible to fit the UNI-GMM to the chest X-ray CT images and reduce the specific noise.

  9. Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

    Science.gov (United States)

    Torteeka, Peerapong; Gao, Peng-Qi; Shen, Ming; Guo, Xiao-Zhang; Yang, Da-Tao; Yu, Huan-Huan; Zhou, Wei-Ping; Zhao, You

    2017-02-01

    Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia-Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle-filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

  10. Adaptive Stabilization and Dynamic Performance Preservation of Cascaded DC-DC Systems by Incorporating Low Pass Filters

    Directory of Open Access Journals (Sweden)

    Ahmed Aldhaheri

    2018-02-01

    Full Text Available This paper proposes a method to stabilize and enhance the dynamic performance of a cascaded DC-DC system by adaptively reshaping the source output impedance. The method aims to reduce the ratio of the source output impedance to the load input impedance, referred to as the minor loop gain, to eliminate the interaction between the load and the source systems. This interaction can deteriorate the dynamic performance or might lead to instability. Thus, the bus current is used to improve the dynamic performance by reducing the magnitude of the source’s output impedance adaptively according to the loading condition such that the dynamic performance is consistently improved. Utilizing the bus current facilitates the compatibility between the proposed controller and most widely used DC-DC converters controlled in voltage mode, including non-minimum phase converters. In addition to the flexibility the bus current provides to embed the proposed solution with conventional control schemes. Experimental results have validated the effectiveness of the proposed controller along with time-based simulation and theoretical analysis, for minimum and non-minimum phase converters.

  11. Activated Notch signaling cascade is correlated with stem cell differentiation toward absorptive progenitors after massive small bowel resection in a rat.

    Science.gov (United States)

    Sukhotnik, Igor; Coran, Arnold G; Pollak, Yulia; Kuhnreich, Eviatar; Berkowitz, Drora; Saxena, Amulya K

    2017-09-01

    Notch signaling is thought to act to drive cell versification in the lining of the small intestine. The purpose of the present study was to evaluate the role of the Notch signaling pathway in stem cell differentiation in the late stages of intestinal adaptation after massive small bowel resection in a rat. Male Sprague-Dawley rats were randomly assigned to one of two experimental groups of eight rats each: Sham rats underwent bowel transection and reanastomosis, while SBS rats underwent 75% small bowel resection. Rats were euthanized on day 14 Illumina's Digital Gene Expression (DGE) analysis was used to determine Notch signaling gene expression profiling. Notch-related gene and protein expression was determined using real-time PCR, Western blot analysis, and immunohistochemistry. From seven investigated Notch-related (by DGE analysis) genes, six genes were upregulated in SBS vs. control animals with a relative change in gene expression level of 20% or more. A significant upregulation of Notch signaling-related genes in resected animals was accompanied by a significant increase in Notch-1 protein levels (Western blot analysis) and a significant increase in the number of Notch1 and Hes1 (target gene)-positive cells (immunohistochemistry) compared with sham animals. Evaluation of cell differentiation has shown a strong increase in total number of absorptive cells (unchanged secretory cells) compared with control rats. In conclusion, 2 wk after bowel resection in rats, stimulated Notch signaling directs the crypt cell population toward absorptive progenitors.NEW & NOTEWORTHY This study provides novel insight into the mechanisms of cell proliferation following massive small bowel resection. We show that 2 wk after bowel resection in rats, enhanced stem cell activity was associated with stimulated Notch signaling pathway. We demonstrate that activated Notch signaling cascade directs the crypt cell population toward absorptive progenitors. Copyright © 2017 the American

  12. SEL-10 is an inhibitor of notch signaling that targets notch for ubiquitin-mediated protein degradation.

    Science.gov (United States)

    Wu, G; Lyapina, S; Das, I; Li, J; Gurney, M; Pauley, A; Chui, I; Deshaies, R J; Kitajewski, J

    2001-11-01

    Notch receptors and their ligands play important roles in both normal animal development and pathogenesis. We show here that the F-box/WD40 repeat protein SEL-10 negatively regulates Notch receptor activity by targeting the intracellular domain of Notch receptors for ubiquitin-mediated protein degradation. Blocking of endogenous SEL-10 activity was done by expression of a dominant-negative form containing only the WD40 repeats. In the case of Notch1, this block leads to an increase in Notch signaling stimulated by either an activated form of the Notch1 receptor or Jagged1-induced signaling through Notch1. Expression of dominant-negative SEL-10 leads to stabilization of the intracellular domain of Notch1. The Notch4 intracellular domain bound to SEL-10, but its activity was not increased as a result of dominant-negative SEL-10 expression. SEL-10 bound Notch4 via the WD40 repeats and bound preferentially to a phosphorylated form of Notch4 in cells. We mapped the region of Notch4 essential for SEL-10 binding to the C-terminal region downstream of the ankyrin repeats. When this C-terminal fragment of Notch4 was expressed in cells, it was highly labile but could be stabilized by the expression of dominant-negative SEL-10. Ubiquitination of Notch1 and Notch4 intracellular domains in vitro was dependent on SEL-10. Although SEL-10 interacts with the intracellular domains of both Notch1 and Notch4, these proteins respond differently to interference with SEL-10 function. Thus, SEL-10 functions to promote the ubiquitination of Notch proteins; however, the fates of these proteins may differ.

  13. A pseudo-matched filter for chaos.

    Science.gov (United States)

    Cohen, Seth D; Gauthier, Daniel J

    2012-09-01

    A matched filter maximizes the signal-to-noise ratio of a signal. In the recent work of Corron et al. [Chaos 20, 023123 (2010)], a matched filter is derived for the chaotic waveforms produced by a piecewise-linear system. This system produces a readily available binary symbolic dynamics that can be used to perform correlations in the presence of large amounts of noise using the matched filter. Motivated by these results, we describe a pseudo-matched filter, which operates similarly to the original matched filter. It consists of a notch filter followed by a first-order, low-pass filter. We compare quantitatively the matched filter's performance to that of our pseudo-matched filter using correlation functions. On average, the pseudo-matched filter performs with a correlation signal-to-noise ratio that is 2.0 dB below that of the matched filter. Our pseudo-matched filter, though somewhat inferior in comparison to the matched filter, is easily realizable at high speed (>1 GHz) for potential radar applications.

  14. Prox1 regulates the notch1-mediated inhibition of neurogenesis.

    Directory of Open Access Journals (Sweden)

    Valeria Kaltezioti

    2010-12-01

    Full Text Available Activation of Notch1 signaling in neural progenitor cells (NPCs induces self-renewal and inhibits neurogenesis. Upon neuronal differentiation, NPCs overcome this inhibition, express proneural genes to induce Notch ligands, and activate Notch1 in neighboring NPCs. The molecular mechanism that coordinates Notch1 inactivation with initiation of neurogenesis remains elusive. Here, we provide evidence that Prox1, a transcription repressor and downstream target of proneural genes, counteracts Notch1 signaling via direct suppression of Notch1 gene expression. By expression studies in the developing spinal cord of chick and mouse embryo, we showed that Prox1 is limited to neuronal precursors residing between the Notch1+ NPCs and post-mitotic neurons. Physiological levels of Prox1 in this tissue are sufficient to allow binding at Notch1 promoter and they are critical for proper Notch1 transcriptional regulation in vivo. Gain-of-function studies in the chick neural tube and mouse NPCs suggest that Prox1-mediated suppression of Notch1 relieves its inhibition on neurogenesis and allows NPCs to exit the cell cycle and differentiate. Moreover, loss-of-function in the chick neural tube shows that Prox1 is necessary for suppression of Notch1 outside the ventricular zone, inhibition of active Notch signaling, down-regulation of NPC markers, and completion of neuronal differentiation program. Together these data suggest that Prox1 inhibits Notch1 gene expression to control the balance between NPC self-renewal and neuronal differentiation.

  15. Is notch sensitivity a stress analysis problem?

    Directory of Open Access Journals (Sweden)

    Jaime Tupiassú Pinho de Castro

    2013-07-01

    Full Text Available Semi–empirical notch sensitivity factors q have been widely used to properly account for notch effects in fatigue design for a long time. However, the intrinsically empirical nature of this old concept can be avoided by modeling it using sound mechanical concepts that properly consider the influence of notch tip stress gradients on the growth behavior of mechanically short cracks. Moreover, this model requires only well-established mechanical properties, as it has no need for data-fitting or similar ill-defined empirical parameters. In this way, the q value can now be calculated considering the characteristics of the notch geometry and of the loading, as well as the basic mechanical properties of the material, such as its fatigue limit and crack propagation threshold, if the problem is fatigue, or its equivalent resistances to crack initiation and to crack propagation under corrosion conditions, if the problem is environmentally assisted or stress corrosion cracking. Predictions based on this purely mechanical model have been validated by proper tests both in the fatigue and in the SCC cases, indicating that notch sensitivity can indeed be treated as a stress analysis problem.

  16. Aberrant activation of notch signaling in human breast cancer.

    Science.gov (United States)

    Stylianou, Spyros; Clarke, Rob B; Brennan, Keith

    2006-02-01

    A role for Notch signaling in human breast cancer has been suggested by both the development of adenocarcinomas in the murine mammary gland following pathway activation and the loss of Numb expression, a negative regulator of the Notch pathway, in a large proportion of breast carcinomas. However, it is not clear currently whether Notch signaling is frequently activated in breast tumors, and how it causes cellular transformation. Here, we show accumulation of the intracellular domain of Notch1 and hence increased Notch signaling in a wide variety of human breast carcinomas. In addition, we show that increased RBP-Jkappa-dependent Notch signaling is sufficient to transform normal breast epithelial cells and that the mechanism of transformation is most likely through the suppression of apoptosis. More significantly, we show that attenuation of Notch signaling reverts the transformed phenotype of human breast cancer cell lines, suggesting that inhibition of Notch signaling may be a therapeutic strategy for this disease.

  17. Space-Time Joint Interference Cancellation Using Fuzzy-Inference-Based Adaptive Filtering Techniques in Frequency-Selective Multipath Channels

    Directory of Open Access Journals (Sweden)

    Chen Yu-Fan

    2006-01-01

    Full Text Available An adaptive minimum mean-square error (MMSE array receiver based on the fuzzy-logic recursive least-squares (RLS algorithm is developed for asynchronous DS-CDMA interference suppression in the presence of frequency-selective multipath fading. This receiver employs a fuzzy-logic control mechanism to perform the nonlinear mapping of the squared error and squared error variation, denoted by ( , , into a forgetting factor . For the real-time applicability, a computationally efficient version of the proposed receiver is derived based on the least-mean-square (LMS algorithm using the fuzzy-inference-controlled step-size . This receiver is capable of providing both fast convergence/tracking capability as well as small steady-state misadjustment as compared with conventional LMS- and RLS-based MMSE DS-CDMA receivers. Simulations show that the fuzzy-logic LMS and RLS algorithms outperform, respectively, other variable step-size LMS (VSS-LMS and variable forgetting factor RLS (VFF-RLS algorithms at least 3 dB and 1.5 dB in bit-error-rate (BER for multipath fading channels.

  18. Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman Filter

    Science.gov (United States)

    Han, Houzeng; Xu, Tianhe; Wang, Jian

    2016-01-01

    Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD) operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC) algorithm is implemented by integrating PPP with inertial navigation system (INS) using an Extended Kalman filter (EKF). The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies of the height

  19. Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman Filter

    Directory of Open Access Journals (Sweden)

    Houzeng Han

    2016-07-01

    Full Text Available Precise Point Positioning (PPP makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC algorithm is implemented by integrating PPP with inertial navigation system (INS using an Extended Kalman filter (EKF. The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies

  20. Linear parameter-varying model and adaptive filtering technique for detecting neuronal activities: an fNIRS study

    Science.gov (United States)

    Kamran, M. Ahmad; Hong, Keum-Shik

    2013-10-01

    Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique that measures brain activities by using near-infrared light of 650-950 nm wavelength. The major advantages of fNIRS are its low cost, portability, and good temporal resolution as a plausible solution to real-time imaging. Recent research has shown the great potential of fNIRS as a tool for brain-computer interfaces. Approach. This paper presents the first novel technique for fNIRS-based modelling of brain activities using the linear parameter-varying (LPV) method and adaptive signal processing. The output signal of each channel is assumed to be an output of an LPV system with unknown coefficients that are optimally estimated by the affine projection algorithm. The parameter vector is assumed to be Gaussian. Main results. The general linear model (GLM) is very popular and is a commonly used method for the analysis of functional MRI data, but it has certain limitations in the case of optical signals. The proposed model is more efficient in the sense that it allows the user to define more states. Moreover, unlike most previous models, it is online. The present results, showing improvement, were verified by random finger-tapping tasks in extensive experiments. We used 24 states, which can be reduced or increased depending on the cost of computation and requirements. Significance. The t-statistics were employed to determine the activation maps and to verify the significance of the results. Comparison of the proposed technique and two existing GLM-based algorithms shows an improvement in the estimation of haemodynamic response. Additionally, the convergence of the proposed algorithm is shown by error reduction in consecutive iterations.

  1. Loss of TGF-β Adaptor β2SP Activates Notch Signaling and SOX9 Expression in Esophageal Adenocarcinoma

    Science.gov (United States)

    Song, Shumei; Maru, Dipen M.; Ajani, Jaffer A.; Chan, Chia-Hsin; Honjo, Soichiro; Lin, Hui-Kuan; Correa, Arlene; Hofstetter, Wayne L.; Davila, Marta; Stroehlein, John; Mishra, Lopa

    2013-01-01

    TGF-β and Notch signaling pathways play important roles in regulating self-renewal of stem cells and gastrointestinal carcinogenesis. Loss of TGF-β signaling components activates Notch signaling in esophageal adenocarcinoma, but the basis for this effect has been unclear. Here we report that loss of TGF-β adapter β2SP (SPNB2) activates Notch signaling and its target SOX9 in primary fibroblasts or esophageal adenocarcinoma cells. Expression of the stem cell marker SOX9 was markedly higher in esophageal adenocarcinoma tumor tissues than normal tissues, and its higher nuclear staining in tumors correlated with poorer survival and lymph node invasion in esophageal adenocarcinoma patients. Downregulation of β2SP by lentivirus short hairpin RNA increased SOX9 transcription and expression, enhancing nuclear localization for both active Notch1 (intracellular Notch1, ICN1) and SOX9. In contrast, reintroduction into esophageal adenocarcinoma cells of β2SP and a dominant-negative mutant of the Notch coactivator mastermind-like (dnMAN) decreased SOX9 promoter activity. Tumor sphere formation and invasive capacity in vitro and tumor growth in vivo were increased in β2SP-silenced esophageal adenocarcinoma cells. Conversely, SOX9 silencing rescued the phenotype of esophageal adenocarcinoma cells with loss of β2SP. Interaction between Smad3 and ICN1 via Smad3 MH1 domain was also observed, with loss of β2SP increasing the binding between these proteins, inducing expression of Notch targets SOX9 and C-MYC, and decreasing expression of TGF-β targets p21(CDKN1A), p27 (CDKN1B), and E-cadherin. Taken together, our findings suggest that loss of β2SP switches TGF-β signaling from tumor suppression to tumor promotion by engaging Notch signaling and activating SOX9. PMID:23536563

  2. Dual Mechanism of Action of Resveratrol in Notch Signaling ...

    African Journals Online (AJOL)

    HeyL, Notch signaling target genes. Conclusion: Resveratrol plays an important role in the activation of Notch signaling pathway and may be of therapeutic benefit in the treatment of osteosarcoma. Keywords: Osteosarcoma, Dual action mechanism, Notch signaling pathway, Toxicity, Cell growth inhibition. Tropical Journal ...

  3. O-Fucose Modulates Notch-Controlled Blood Lineage Commitment

    Science.gov (United States)

    Yan, Quanjian; Yao, David; Wei, Lebing L.; Huang, Yuanshuai; Myers, Jay; Zhang, Lihua; Xin, Wei; Shim, Jeongsup; Man, Yunfang; Petryniak, Bronislawa; Gerson, Stanton; Lowe, John B.; Zhou, Lan

    2010-01-01

    Notch receptors are cell surface molecules essential for cell fate determination. Notch signaling is subject to tight regulation at multiple levels, including the posttranslational modification of Notch receptors by O-linked fucosylation, a reaction that is catalyzed by protein O-fucosyltransferase-1 (Pofut1). Our previous studies identified a myeloproliferative phenotype in mice conditionally deficient in cellular fucosylation that is attributable to a loss of Notch-dependent suppression of myelopoiesis. Here, we report that hematopoietic stem cells deficient in cellular fucosylation display decreased frequency and defective repopulating ability as well as decreased lymphoid but increased myeloid developmental potential. This phenotype may be attributed to suppressed Notch ligand binding and reduced downstream signaling of Notch activity in hematopoietic stem cells. Consistent with this finding, we further demonstrate that mouse embryonic stem cells deficient in Notch1 (Notch1−/−) or Pofut1 (Pofut1−/−) fail to generate T lymphocytes but differentiate into myeloid cells while coculturing with Notch ligand–expressing bone marrow stromal cells in vitro. Moreover, in vivo hematopoietic reconstitution of CD34+ progenitor cells derived from either Notch1−/− or Pofut1−/− embryonic stem cells show enhanced granulopoiesis with depressed lymphoid lineage development. Together, these results indicate that Notch signaling maintains hematopoietic lineage homeostasis by promoting lymphoid development and suppressing overt myelopoiesis, in part through processes controlled by O-linked fucosylation of Notch receptors. PMID:20363915

  4. Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction-V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions.

    Science.gov (United States)

    Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T

    2017-08-12

    The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P V 90% showed superior LCD and had the highest CNR in the liver, aorta, and, pancreas, measuring 7.32 ± 3.22, 11.60 ± 4.25, and 4.60 ± 2.31, respectively, compared with the next best series of ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.

  5. Adaptive iterative dose reduction algorithm in CT: Effect on image quality compared with filtered back projection in body phantoms of different sizes

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Milim; Lee, Jeong Min; Son, Hyo Shin; Han, Joon Koo; Choi, Byung Ihn [College of Medicine, Seoul National University, Seoul (Korea, Republic of); Yoon, Jeong Hee; Choi, Jin Woo [Dept. of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of)

    2014-04-15

    To evaluate the impact of the adaptive iterative dose reduction (AIDR) three-dimensional (3D) algorithm in CT on noise reduction and the image quality compared to the filtered back projection (FBP) algorithm and to compare the effectiveness of AIDR 3D on noise reduction according to the body habitus using phantoms with different sizes. Three different-sized phantoms with diameters of 24 cm, 30 cm, and 40 cm were built up using the American College of Radiology CT accreditation phantom and layers of pork belly fat. Each phantom was scanned eight times using different mAs. Images were reconstructed using the FBP and three different strengths of the AIDR 3D. The image noise, the contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) of the phantom were assessed. Two radiologists assessed the image quality of the 4 image sets in consensus. The effectiveness of AIDR 3D on noise reduction compared with FBP were also compared according to the phantom sizes. Adaptive iterative dose reduction 3D significantly reduced the image noise compared with FBP and enhanced the SNR and CNR (p < 0.05) with improved image quality (p < 0.05). When a stronger reconstruction algorithm was used, greater increase of SNR and CNR as well as noise reduction was achieved (p < 0.05). The noise reduction effect of AIDR 3D was significantly greater in the 40-cm phantom than in the 24-cm or 30-cm phantoms (p < 0.05). The AIDR 3D algorithm is effective to reduce the image noise as well as to improve the image-quality parameters compared by FBP algorithm, and its effectiveness may increase as the phantom size increases.

  6. Notch-1 and notch-4 receptors as prognostic markers in breast cancer.

    Science.gov (United States)

    Yao, Katharine; Rizzo, Paola; Rajan, Prabha; Albain, Kathy; Rychlik, Karen; Shah, Sneha; Miele, Lucio

    2011-10-01

    Studies looking at immunohistochemical (IHC) staining of Notch receptors in breast cancer and correlation with known prognostic factors are sparse. IHC staining for nuclear, cytoplasmic, and membrane Notch-1 (N1), Notch-4 (N4), and Jagged-1 (JAG1) was performed and correlated with known prognostic factors. Of 48 breast cancers, 36 (67%) were invasive, mean age was 50 years (range 43-86 years), 37 (77%) were estrogen receptor (ERα) positive, and 13 (27%) node positive. There was significantly more marked N1 membranous staining in ERα-positive tumors (P membranous N4 significantly correlated with Ki67 (P membranous JAG1 significantly correlated with Ki67 (P markers is feasible and correlates with known prognostic factors consistent with a biological role of Notch signaling in breast cancer progression.

  7. Comparison of image quality between filtered back-projection and the adaptive statistical and novel model-based iterative reconstruction techniques in abdominal CT for renal calculi.

    Science.gov (United States)

    Vardhanabhuti, Varut; Ilyas, Sumaira; Gutteridge, Catherine; Freeman, Simon J; Roobottom, Carl A

    2013-10-01

    To compare image quality on computed tomographic (CT) images acquired with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) techniques in CT kidney/ureter/bladder (KUB) examination. Eighteen patients underwent standard protocol CT KUB at our institution. The same raw data were reconstructed using FBP, ASIR and MBIR. Objective [mean image noise, contrast-to-noise ratio (CNR) for kidney and mean attenuation values of subcutaneous fat] and subjective image parameters (image noise, image contrast, overall visibility of kidneys/ureters/bladder, visibility of small structures, and overall diagnostic confidence) were assessed using a scoring system from 1 (best) to 5 (worst). Objective image measurements revealed significantly less image noise and higher CNR and the same fat attenuation values for the MBIR technique (P ASIR and 3.08-3.31 for FBP. No significant difference was observed between FBP and ASIR (P > 0.05), while there was a significant difference between ASIR vs. MBIR (P ASIR and FBP CT KUB examinations. • There are many reconstruction options in CT. • Novel model-based iterative reconstruction (MBIR) showed the least noise and optimal image quality. • For CT of the kidneys/ureters/bladder, MBIR should be utilised, if available. • Further studies to reduce the dose while maintaining image quality should be pursued.

  8. Comparison of Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection for Detecting Hepatic Metastases on Submillisievert Low-Dose Computed Tomography.

    Science.gov (United States)

    Son, Jung Hee; Kim, Seung Ho; Yoon, Jung-Hee; Lee, Yedaun; Lim, Yun-Jung; Kim, Seon-Jeong

    The aim of the study was to compare the diagnostic performance of model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP) on submillisievert low-dose computed tomography (LDCT) for detecting hepatic metastases. Thirty-eight patients having hepatic metastases underwent abdomen CT. Computed tomography protocol consisted of routine standard-dose portal venous phase scan (120 kVp) and 90-second delayed low-dose scan (80 kVp). The LDCT images were reconstructed with FBP, ASIR, and MBIR, respectively. Two readers recorded the number of hepatic metastases on each image set. A total of 105 metastatic lesions were analyzed. For reader 1, sensitivity for detecting metastases was stationary between FBP (49%) and ASIR (52%, P = 0.0697); however, sensitivity increased in MBIR (66%, P = 0.0035). For reader 2, it was stationary for all the following sets: FBP (65%), ASIR (68%), and MBIR (67%, P > 0.05). The MBIR and ASIR showed a limited sensitivity for detecting hepatic metastases in submillisievert LDCT.

  9. Comparison of the image qualities of filtered back-projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction for CT venography at 80 kVp.

    Science.gov (United States)

    Kim, Jin Hyeok; Choo, Ki Seok; Moon, Tae Yong; Lee, Jun Woo; Jeon, Ung Bae; Kim, Tae Un; Hwang, Jae Yeon; Yun, Myeong-Ja; Jeong, Dong Wook; Lim, Soo Jin

    2016-07-01

    To evaluate the subjective and objective qualities of computed tomography (CT) venography images at 80 kVp using model-based iterative reconstruction (MBIR) and to compare these with those of filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) using the same CT data sets. Forty-four patients (mean age: 56.1 ± 18.1) who underwent 80 kVp CT venography (CTV) for the evaluation of deep vein thrombosis (DVT) during 4 months were enrolled in this retrospective study. The same raw data were reconstructed using FBP, ASIR, and MBIR. Objective and subjective image analysis were performed at the inferior vena cava (IVC), femoral vein, and popliteal vein. The mean CNR of MBIR was significantly greater than those of FBP and ASIR and images reconstructed using MBIR had significantly lower objective image noise (p ASIR (p ASIR regarding subjective and objective image qualities. • MBIR provides superior image quality compared with FBP and ASIR • CTV at 80kVp with MBIR improves diagnostic confidence in diagnosing DVT • CTV at 80kVp with MBIR presents better image quality with low radiation.

  10. Adaptive statistical iterative reconstruction versus filtered back projection in the same patient: 64 channel liver CT image quality and patient radiation dose

    Energy Technology Data Exchange (ETDEWEB)

    Mitsumori, Lee M.; Shuman, William P.; Busey, Janet M.; Kolokythas, Orpheus; Koprowicz, Kent M. [University of Washington School of Medicine, Department of Radiology, Seattle, WA (United States)

    2012-01-15

    To compare routine dose liver CT reconstructed with filtered back projection (FBP) versus low dose images reconstructed with FBP and adaptive statistical iterative reconstruction (ASIR). In this retrospective study, patients had a routine dose protocol reconstructed with FBP, and again within 17 months (median 6.1 months), had a low dose protocol reconstructed twice, with FBP and ASIR. These reconstructions were compared for noise, image quality, and radiation dose. Nineteen patients were included. (12 male, mean age 58). Noise was significantly lower in low dose images reconstructed with ASIR compared to routine dose images reconstructed with FBP (liver: p <.05, aorta: p < 0.001). Low dose FBP images were scored significantly lower for subjective image quality than low dose ASIR (2.1 {+-} 0.5, 3.2 {+-} 0.8, p < 0.001). There was no difference in subjective image quality scores between routine dose FBP images and low dose ASIR images (3.6 {+-} 0.5, 3.2 {+-} 0.8, NS).Radiation dose was 41% less for the low dose protocol (4.4 {+-} 2.4 mSv versus 7.5 {+-} 5.5 mSv, p < 0.05). Our initial results suggest low dose CT images reconstructed with ASIR may have lower measured noise, similar image quality, yet significantly less radiation dose compared with higher dose images reconstructed with FBP. (orig.)

  11. Quantitative analysis of emphysema and airway measurements according to iterative reconstruction algorithms: comparison of filtered back projection, adaptive statistical iterative reconstruction and model-based iterative reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Choo, Ji Yung [Seoul National University Medical Research Center, Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul (Korea, Republic of); Korea University Ansan Hospital, Ansan-si, Department of Radiology, Gyeonggi-do (Korea, Republic of); Goo, Jin Mo; Park, Chang Min; Park, Sang Joon [Seoul National University Medical Research Center, Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul (Korea, Republic of); Seoul National University, Cancer Research Institute, Seoul (Korea, Republic of); Lee, Chang Hyun; Shim, Mi-Suk [Seoul National University Medical Research Center, Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul (Korea, Republic of)

    2014-04-15

    To evaluate filtered back projection (FBP) and two iterative reconstruction (IR) algorithms and their effects on the quantitative analysis of lung parenchyma and airway measurements on computed tomography (CT) images. Low-dose chest CT obtained in 281 adult patients were reconstructed using three algorithms: FBP, adaptive statistical IR (ASIR) and model-based IR (MBIR). Measurements of each dataset were compared: total lung volume, emphysema index (EI), airway measurements of the lumen and wall area as well as average wall thickness. Accuracy of airway measurements of each algorithm was also evaluated using an airway phantom. EI using a threshold of -950 HU was significantly different among the three algorithms in decreasing order of FBP (2.30 %), ASIR (1.49 %) and MBIR (1.20 %) (P < 0.01). Wall thickness was also significantly different among the three algorithms with FBP (2.09 mm) demonstrating thicker walls than ASIR (2.00 mm) and MBIR (1.88 mm) (P < 0.01). Airway phantom analysis revealed that MBIR showed the most accurate value for airway measurements. The three algorithms presented different EIs and wall thicknesses, decreasing in the order of FBP, ASIR and MBIR. Thus, care should be taken in selecting the appropriate IR algorithm on quantitative analysis of the lung. (orig.)

  12. Quantitative analysis of emphysema and airway measurements according to iterative reconstruction algorithms: comparison of filtered back projection, adaptive statistical iterative reconstruction and model-based iterative reconstruction.

    Science.gov (United States)

    Choo, Ji Yung; Goo, Jin Mo; Lee, Chang Hyun; Park, Chang Min; Park, Sang Joon; Shim, Mi-Suk

    2014-04-01

    To evaluate filtered back projection (FBP) and two iterative reconstruction (IR) algorithms and their effects on the quantitative analysis of lung parenchyma and airway measurements on computed tomography (CT) images. Low-dose chest CT obtained in 281 adult patients were reconstructed using three algorithms: FBP, adaptive statistical IR (ASIR) and model-based IR (MBIR). Measurements of each dataset were compared: total lung volume, emphysema index (EI), airway measurements of the lumen and wall area as well as average wall thickness. Accuracy of airway measurements of each algorithm was also evaluated using an airway phantom. EI using a threshold of -950 HU was significantly different among the three algorithms in decreasing order of FBP (2.30 %), ASIR (1.49 %) and MBIR (1.20 %) (P algorithms with FBP (2.09 mm) demonstrating thicker walls than ASIR (2.00 mm) and MBIR (1.88 mm) (P analysis revealed that MBIR showed the most accurate value for airway measurements. The three algorithms presented different EIs and wall thicknesses, decreasing in the order of FBP, ASIR and MBIR. Thus, care should be taken in selecting the appropriate IR algorithm on quantitative analysis of the lung. • Computed tomography is increasingly used to provide objective measurements of intra-thoracic structures. • Iterative reconstruction algorithms can affect quantitative measurements of lung and airways. • Care should be taken in selecting reconstruction algorithms in longitudinal analysis. • Model-based iterative reconstruction seems to provide the most accurate airway measurements.

  13. A novel on-board state-of-charge estimation method for aged Li-ion batteries based on model adaptive extended Kalman filter

    Science.gov (United States)

    Sepasi, Saeed; Ghorbani, Reza; Liaw, Bor Yann

    2014-01-01

    A battery management system needs to have an accurate inline estimation of SOC for each individual cell in the battery pack. This estimation process poses challenges after substantial battery aging. This article presents a novel method based on model adaptive extended Kalman filter (MAEKF) to estimate SOC for Li-ion batteries. Sensitivity analysis of the electrical model verifies that the accuracy of SOC estimated by EKF is sensitive to resistors used in the cell's electrical model. In order to get the best estimation, values of resistors are obtained in an optimization process in the MAEKF. This method uses the fact of two sudden changes in the cell's voltage derivative with respect to time while discharging current is constant. These two points are assumed as reference points in which their SOC can be determined from cell's chemistry. The optimization algorithm uses the derivative of the cell's measured terminal voltage to allocate SOC of 92% and 15% for two reference points in the Vcell equation and updates cell's electrical model. The algorithm's process is fast and computationally inexpensive, making on-board estimation practical. The obtained results demonstrate that by using this method the estimated SOC error for aged Li-ion cells does not exceed 4%.

  14. Microwave Filters

    OpenAIRE

    Zhou, Jiafeng

    2010-01-01

    The general theory of microwave filter design based on lumped-element circuit is described in this chapter. The lowpass prototype filters with Butterworth, Chebyshev and quasielliptic characteristics are synthesized, and the prototype filters are then transformed to bandpass filters by lowpass to bandpass frequency mapping. By using immitance inverters ( J - or K -inverters), the bandpass filters can be realized by the same type of resonators. One design example is given to verify the theory ...

  15. On-line adaptive line frequency noise cancellation from a nuclear power measuring channel

    Directory of Open Access Journals (Sweden)

    Qadir Javed

    2011-01-01

    Full Text Available On-line software for adaptively canceling 50 Hz line frequency noise has been designed and tested at Pakistan Research Reactor 1. Line frequency noise causes much problem in weak signals acquisition. Sometimes this noise is so dominant that original signal is totally corrupted. Although notch filter can be used for eliminating this noise, but if signal of interest is in close vicinity of 50 Hz, then original signal is also attenuated and hence overall performance is degraded. Adaptive noise removal is a technique which could be employed for removing line frequency without degrading the desired signal. In this paper line frequency noise has been eliminated on-line from a nuclear power measuring channel. The adaptive LMS algorithm has been used to cancel 50 Hz noise. The algorithm has been implemented in labVIEW with NI 6024 data acquisition card. The quality of the acquired signal has been improved much as can be seen in experimental results.

  16. Inhibitory role of Notch1 in calcific aortic valve disease.

    Directory of Open Access Journals (Sweden)

    Asha Acharya

    Full Text Available Aortic valve calcification is the most common form of valvular heart disease, but the mechanisms of calcific aortic valve disease (CAVD are unknown. NOTCH1 mutations are associated with aortic valve malformations and adult-onset calcification in families with inherited disease. The Notch signaling pathway is critical for multiple cell differentiation processes, but its role in the development of CAVD is not well understood. The aim of this study was to investigate the molecular changes that occur with inhibition of Notch signaling in the aortic valve. Notch signaling pathway members are expressed in adult aortic valve cusps, and examination of diseased human aortic valves revealed decreased expression of NOTCH1 in areas of calcium deposition. To identify downstream mediators of Notch1, we examined gene expression changes that occur with chemical inhibition of Notch signaling in rat aortic valve interstitial cells (AVICs. We found significant downregulation of Sox9 along with several cartilage-specific genes that were direct targets of the transcription factor, Sox9. Loss of Sox9 expression has been published to be associated with aortic valve calcification. Utilizing an in vitro porcine aortic valve calcification model system, inhibition of Notch activity resulted in accelerated calcification while stimulation of Notch signaling attenuated the calcific process. Finally, the addition of Sox9 was able to prevent the calcification of porcine AVICs that occurs with Notch inhibition. In conclusion, loss of Notch signaling contributes to aortic valve calcification via a Sox9-dependent mechanism.

  17. Notch 1 signaling regulates peripheral T cell activation.

    Science.gov (United States)

    Eagar, Todd N; Tang, Qizhi; Wolfe, Michael; He, Yiping; Pear, Warren S; Bluestone, Jeffrey A

    2004-04-01

    Notch signaling has been identified as an important regulator of leukocyte differentiation and thymic maturation. Less is known about the role of Notch signaling in regulating mature T cells. We examined the role of Notch 1 in regulating peripheral T cell activity in vitro and in vivo. Coligation of Notch 1 together with TCR and CD28 resulted in a dramatic inhibition of T cell activation, proliferation, and cytokine production. This effect was dependent on presenilin activity and induced the expression of HES-1, suggestive of Notch 1 signaling. Biochemical analysis demonstrated an inhibition of AKT and GSK3beta phosphorylation following Notch 1 engagement while other biochemical signals such as TCR and ERK phosphorylation remained intact. Similar effects were observed in vivo in an adoptive transfer model. Therefore, Notch 1 signaling may play an important role in regulating naive T cell activation and homeostasis.

  18. Comparison of applied dose and image quality in staging CT of neuroendocrine tumor patients using standard filtered back projection and adaptive statistical iterative reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Böning, G., E-mail: georg.boening@charite.de [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Schäfer, M.; Grupp, U. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Kaul, D. [Department of Radiation Oncology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Kahn, J. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Pavel, M. [Department of Gastroenterology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Maurer, M.; Denecke, T.; Hamm, B.; Streitparth, F. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany)

    2015-08-15

    Highlights: • Iterative reconstruction (IR) in staging CT provides equal objective image quality compared to filtered back projection (FBP). • IR delivers excellent subjective quality and reduces effective dose compared to FBP. • In patients with neuroendocrine tumor (NET) or may other hypervascular abdominal tumors IR can be used without scarifying diagnostic confidence. - Abstract: Objective: To investigate whether dose reduction via adaptive statistical iterative reconstruction (ASIR) affects image quality and diagnostic accuracy in neuroendocrine tumor (NET) staging. Methods: A total of 28 NET patients were enrolled in the study. Inclusion criteria were histologically proven NET and visible tumor in abdominal computed tomography (CT). In an intraindividual study design, the patients underwent a baseline CT (filtered back projection, FBP) and follow-up CT (ASIR 40%) using matched scan parameters. Image quality was assessed subjectively using a 5-grade scoring system and objectively by determining signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs). Applied volume computed tomography dose index (CTDI{sub vol}) of each scan was taken from the dose report. Results: ASIR 40% significantly reduced CTDI{sub vol} (10.17 ± 3.06 mGy [FBP], 6.34 ± 2.25 mGy [ASIR] (p < 0.001) by 37.6% and significantly increased CNRs (complete tumor-to-liver, 2.76 ± 1.87 [FBP], 3.2 ± 2.32 [ASIR]) (p < 0.05) (complete tumor-to-muscle, 2.74 ± 2.67 [FBP], 4.31 ± 4.61 [ASIR]) (p < 0.05) compared to FBP. Subjective scoring revealed no significant changes for diagnostic confidence (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]), visibility of suspicious lesion (4.8 ± 0.5 [FBP], 4.8 ± 0.5 [ASIR]) and artifacts (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]). ASIR 40% significantly decreased scores for noise (4.3 ± 0.6 [FBP], 4.0 ± 0.8 [ASIR]) (p < 0.05), contrast (4.4 ± 0.6 [FBP], 4.1 ± 0.8 [ASIR]) (p < 0.001) and visibility of small structures (4.5 ± 0.7 [FBP], 4.3 ± 0.8 [ASIR]) (p < 0

  19. Photonic ring resonator filters for astronomical OH suppression

    Science.gov (United States)

    Ellis, S. C.; Kuhlmann, S.; Kuehn, K.; Spinka, H.; Underwood, D.; Gupta, R. R.; Ocola, L. E.; Liu, P.; Wei, G.; Stern, N. P.; Bland-Hawthorn, J.; Tuthill, P.

    2017-07-01

    Ring resonators provide a means of filtering specific wavelengths from a waveguide, and optionally dropping the filtered wavelengths into a second waveguide. Both of these features are potentially useful for astronomical instruments. In this paper we focus on their use as notch filters to remove the signal from atmospheric OH emission lines from astronomical spectra, however we also briefly discuss their use as frequency combs for wavelength calibration and as drop filters for Doppler planet searches. We derive the design requirements for ring resonators for OH suppression from theory and finite difference time domain simulations. We find that rings with small radii (0.9), but further optimisation is required to achieve higher Q and deeper notches, with current devices having $Q \\approx 4000$ and $\\approx 10$ dB suppression. The overall prospects for the use of ring resonators in astronomical instruments is promising, provided efficient fibre-chip coupling can be achieved.

  20. Water Filters

    Science.gov (United States)

    1993-01-01

    The Aquaspace H2OME Guardian Water Filter, available through Western Water International, Inc., reduces lead in water supplies. The filter is mounted on the faucet and the filter cartridge is placed in the "dead space" between sink and wall. This filter is one of several new filtration devices using the Aquaspace compound filter media, which combines company developed and NASA technology. Aquaspace filters are used in industrial, commercial, residential, and recreational environments as well as by developing nations where water is highly contaminated.

  1. Image quality of CT angiography with model-based iterative reconstruction in young children with congenital heart disease: comparison with filtered back projection and adaptive statistical iterative reconstruction.

    Science.gov (United States)

    Son, Sung Sil; Choo, Ki Seok; Jeon, Ung Bae; Jeon, Gye Rok; Nam, Kyung Jin; Kim, Tae Un; Yeom, Jeong A; Hwang, Jae Yeon; Jeong, Dong Wook; Lim, Soo Jin

    2015-06-01

    To retrospectively evaluate the image quality of CT angiography (CTA) reconstructed by model-based iterative reconstruction (MBIR) and to compare this with images obtained by filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR) in newborns and infants with congenital heart disease (CHD). Thirty-seven children (age 4.8 ± 3.7 months; weight 4.79 ± 0.47 kg) with suspected CHD underwent CTA on a 64detector MDCT without ECG gating (80 kVp, 40 mA using tube current modulation). Total dose length product was recorded in all patients. Images were reconstructed using FBP, ASIR, and MBIR. Objective image qualities (density, noise) were measured in the great vessels and heart chambers. The contrast-to-noise ratio (CNR) was calculated by measuring the density and noise of myocardial walls. Two radiologists evaluated images for subjective noise, diagnostic confidence, and sharpness at the level prior to the first branch of the main pulmonary artery. Images were compared with respect to reconstruction method, and reconstruction times were measured. Images from all patients were diagnostic, and the effective dose was 0.22 mSv. The objective image noise of MBIR was significantly lower than those of FBP and ASIR in the great vessels and heart chambers (P 0.05). Mean CNR values were 8.73 for FBP, 14.54 for ASIR, and 22.95 for MBIR. In addition, the subjective image noise of MBIR was significantly lower than those of the others (P ASIR had the highest score for diagnostic confidence (P reconstruction times were 5.1 ± 2.3 s for FBP and ASIR and 15.1 ± 2.4 min for MBIR. While CTA with MBIR in newborns and infants with CHD can reduce image noise and improve CNR more than other methods, it is more time-consuming than the other methods.

  2. Comparison of applied dose and image quality in staging CT of neuroendocrine tumor patients using standard filtered back projection and adaptive statistical iterative reconstruction.

    Science.gov (United States)

    Böning, G; Schäfer, M; Grupp, U; Kaul, D; Kahn, J; Pavel, M; Maurer, M; Denecke, T; Hamm, B; Streitparth, F

    2015-08-01

    To investigate whether dose reduction via adaptive statistical iterative reconstruction (ASIR) affects image quality and diagnostic accuracy in neuroendocrine tumor (NET) staging. A total of 28 NET patients were enrolled in the study. Inclusion criteria were histologically proven NET and visible tumor in abdominal computed tomography (CT). In an intraindividual study design, the patients underwent a baseline CT (filtered back projection, FBP) and follow-up CT (ASIR 40%) using matched scan parameters. Image quality was assessed subjectively using a 5-grade scoring system and objectively by determining signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs). Applied volume computed tomography dose index (CTDIvol) of each scan was taken from the dose report. ASIR 40% significantly reduced CTDIvol (10.17±3.06mGy [FBP], 6.34±2.25mGy [ASIR] (pASIR]) (pASIR]) (pASIR]), visibility of suspicious lesion (4.8±0.5 [FBP], 4.8±0.5 [ASIR]) and artifacts (5.0±0 [FBP], 5.0±0 [ASIR]). ASIR 40% significantly decreased scores for noise (4.3±0.6 [FBP], 4.0±0.8 [ASIR]) (pASIR]) (pASIR]) (pASIR can be used to reduce radiation dose without sacrificing image quality and diagnostic confidence in staging CT of NET patients. This may be beneficial for patients with frequent follow-up and significant cumulative radiation exposure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  3. Low-dose computed tomographic urography using adaptive iterative dose reduction 3-dimensional: comparison with routine-dose computed tomography with filtered back projection.

    Science.gov (United States)

    Juri, Hiroshi; Matsuki, Mitsuru; Inada, Yuki; Tsuboyama, Takahiro; Kumano, Seishi; Azuma, Haruhito; Narumi, Yoshifumi

    2013-01-01

    The aim of this study was to evaluate the image quality of low-dose computed tomographic (CT) urography using adaptive iterative dose reduction 3-dimensional (AIDR 3D) compared with routine-dose CT using filtered back projection (FBP). Thirty patients underwent low- and routine-dose CT scans in the nephrographic and excretory phases of CT urography. Low-dose CT was reconstructed with AIDR 3D, and routine-dose CT was reconstructed with FBP. In quantitative analyses, image noises were measured on the renal cortex, aorta, retroperitoneal fat, and psoas muscle in both CT scans and compared. Qualitative analyses of the urinary system were performed in both CT scans and compared. These results were compared on the basis of the body mass index (BMI) of the patients. The CT dose index (CTDIvol) was measured, and the dose reduction was calculated. In quantitative analyses, image noises in all organs on low-dose CT were less than those on routine-dose CT in both phases independently of the patient's BMI. There were no statistical differences between low- and routine-dose CT for diagnostic acceptability on all urinary systems in both phases independently of the patient's BMI. The average CTDIvol on routine-dose CT was 14.5 mGy in the nephrographic phase and 9.2 mGy in the excretory phase. The average CTDIvol on low-dose CT was 4.2 mGy in the nephrographic phase and 2.7 mGy in the excretory phase. Low-dose CT urography using AIDR 3D can offer diagnostic acceptability comparable with routine-dose CT urography with FBP with approximately 70% dose reduction.

  4. Notch signaling as a therapeutic target for breast cancer treatment?

    Science.gov (United States)

    Han, Jianxun; Hendzel, Michael J; Allalunis-Turner, Joan

    2011-05-31

    Aberrant Notch signaling can induce mammary gland carcinoma in transgenic mice, and high expressions of Notch receptors and ligands have been linked to poor clinical outcomes in human patients with breast cancer. This suggests that inhibition of Notch signaling may be beneficial for breast cancer treatment. In this review, we critically evaluate the evidence that supports or challenges the hypothesis that inhibition of Notch signaling would be advantageous in breast cancer management. We find that there are many remaining uncertainties that must be addressed experimentally if we are to exploit inhibition of Notch signaling as a treatment approach in breast cancer. Nonetheless, Notch inhibition, in combination with other therapies, is a promising avenue for future management of breast cancer. Furthermore, since aberrant Notch4 activity can induce mammary gland carcinoma in the absence of RBPjκ, a better understanding of the components of RBPjκ-independent oncogenic Notch signaling pathways and their contribution to Notch-induced tumorigenesis would facilitate the deployment of Notch inhibition strategies for effective treatment of breast cancer.

  5. Inhibition of Delta-induced Notch signaling using fucose analogs.

    Science.gov (United States)

    Schneider, Michael; Kumar, Vivek; Nordstrøm, Lars Ulrik; Feng, Lei; Takeuchi, Hideyuki; Hao, Huilin; Luca, Vincent C; Garcia, K Christopher; Stanley, Pamela; Wu, Peng; Haltiwanger, Robert S

    2018-01-01

    Notch is a cell-surface receptor that controls cell-fate decisions and is regulated by O-glycans attached to epidermal growth factor-like (EGF) repeats in its extracellular domain. Protein O-fucosyltransferase 1 (Pofut1) modifies EGF repeats with O-fucose and is essential for Notch signaling. Constitutive activation of Notch signaling has been associated with a variety of human malignancies. Therefore, tools that inhibit Notch activity are being developed as cancer therapeutics. To this end, we screened L-fucose analogs for their effects on Notch signaling. Two analogs, 6-alkynyl and 6-alkenyl fucose, were substrates of Pofut1 and were incorporated directly into Notch EGF repeats in cells. Both analogs were potent inhibitors of binding to and activation of Notch1 by Notch ligands Dll1 and Dll4, but not by Jag1. Mutagenesis and modeling studies suggest that incorporation of the analogs into EGF8 of Notch1 markedly reduces the ability of Delta ligands to bind and activate Notch1.

  6. Notch Regulates Macrophage-Mediated Inflammation in Diabetic Wound Healing

    Directory of Open Access Journals (Sweden)

    Andrew S. Kimball

    2017-06-01

    Full Text Available Macrophages are essential immune cells necessary for regulated inflammation during wound healing. Recent studies have identified that Notch plays a role in macrophage-mediated inflammation. Thus, we investigated the role of Notch signaling on wound macrophage phenotype and function during normal and diabetic wound healing. We found that Notch receptor and ligand expression are dynamic in wound macrophages during normal healing. Mice with a myeloid-specific Notch signaling defect (DNMAMLfloxedLyz2Cre+ demonstrated delayed early healing (days 1–3 and wound macrophages had decreased inflammatory gene expression. In our physiologic murine model of type 2 diabetes (T2D, Notch receptor expression was significantly increased in wound macrophages on day 6, following the initial inflammatory phase of wound healing, corresponding to increased inflammatory cytokine expression. This increase in Notch1 and Notch2 was also observed in human monocytes from patients with T2D. Further, in prediabetic mice with a genetic Notch signaling defect (DNMAMLfloxedLyz2Cre+ on a high-fat diet, improved wound healing was seen at late time points (days 6–7. These findings suggest that Notch is critical for the early inflammatory phase of wound healing and directs production of macrophage-dependent inflammatory mediators. These results identify that canonical Notch signaling is important in directing macrophage function in wound repair and define a translational target for the treatment of non-healing diabetic wounds.

  7. DOL behaviour of end-notched beams

    DEFF Research Database (Denmark)

    Gustafsson, P.J.; Hoffmeyer, Preben; Valentin, G.

    1998-01-01

    The long-term loading strength of end-notched beams made of glulam and LVL was tested. The beams were of various sizes, with and without a moisture sealing at the notch. Tests were conducted in open shelter climates, and at constant and cyclic relative humidity. The short-term strength was tested...... after conditioning in the various climates. Both the short-term and long-term strength of beams without moisture sealing was significantly affected by transcient moisture conditions, e.g. the moisture variations due to change of the time of the year. The strength was only slightly affected...... by the magnitude of the humidity, if this was kept constant. Duration of load strength reduction factors were evaluated for six months of loading. Average reduction in ultimate failure strength ranged from 0.68 for small LVL beams without moisture sealing tested during spring and summer to 0.81 for large glulam...

  8. Generalized Selection Weighted Vector Filters

    Directory of Open Access Journals (Sweden)

    Rastislav Lukac

    2004-09-01

    Full Text Available This paper introduces a class of nonlinear multichannel filters capable of removing impulsive noise in color images. The here-proposed generalized selection weighted vector filter class constitutes a powerful filtering framework for multichannel signal processing. Previously defined multichannel filters such as vector median filter, basic vector directional filter, directional-distance filter, weighted vector median filters, and weighted vector directional filters are treated from a global viewpoint using the proposed framework. Robust order-statistic concepts and increased degree of freedom in filter design make the proposed method attractive for a variety of applications. Introduced multichannel sigmoidal adaptation of the filter parameters and its modifications allow to accommodate the filter parameters to varying signal and noise statistics. Simulation studies reported in this paper indicate that the proposed filter class is computationally attractive, yields excellent performance, and is able to preserve fine details and color information while efficiently suppressing impulsive noise. This paper is an extended version of the paper by Lukac et al. presented at the 2003 IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP '03 in Grado, Italy.

  9. Water Filters

    Science.gov (United States)

    1987-01-01

    A compact, lightweight electrolytic water filter generates silver ions in concentrations of 50 to 100 parts per billion in the water flow system. Silver ions serve as effective bactericide/deodorizers. Ray Ward requested and received from NASA a technical information package on the Shuttle filter, and used it as basis for his own initial development, a home use filter.

  10. O-GlcNAc on NOTCH1 EGF repeats regulates ligand-induced Notch signaling and vascular development in mammals

    Science.gov (United States)

    Sawaguchi, Shogo; Varshney, Shweta; Ogawa, Mitsutaka; Sakaidani, Yuta; Yagi, Hirokazu; Takeshita, Kyosuke; Murohara, Toyoaki; Kato, Koichi; Sundaram, Subha; Stanley, Pamela; Okajima, Tetsuya

    2017-01-01

    The glycosyltransferase EOGT transfers O-GlcNAc to a consensus site in epidermal growth factor-like (EGF) repeats of a limited number of secreted and membrane proteins, including Notch receptors. In EOGT-deficient cells, the binding of DLL1 and DLL4, but not JAG1, canonical Notch ligands was reduced, and ligand-induced Notch signaling was impaired. Mutagenesis of O-GlcNAc sites on NOTCH1 also resulted in decreased binding of DLL4. EOGT functions were investigated in retinal angiogenesis that depends on Notch signaling. Global or endothelial cell-specific deletion of Eogt resulted in defective retinal angiogenesis, with a mild phenotype similar to that caused by reduced Notch signaling in retina. Combined deficiency of different Notch1 mutant alleles exacerbated the abnormalities in Eogt−/− retina, and Notch target gene expression was decreased in Eogt−/−endothelial cells. Thus, O-GlcNAc on EGF repeats of Notch receptors mediates ligand-induced Notch signaling required in endothelial cells for optimal vascular development. DOI: http://dx.doi.org/10.7554/eLife.24419.001 PMID:28395734

  11. Repurposing Reelin: the new role of radial glia, Reelin and Notch in motor neuron migration.

    Science.gov (United States)

    Hawthorne, Alicia L

    2014-06-01

    The role of Reelin during cerebral cortical neuron migration has long been studied, but the Reelin signaling pathway and its possible interactions are just beginning to be unraveled. Reelin is not only important in cerebral cortical migration, but has recently been shown to interact with the Notch signaling pathway and to be critical for radial glial cell number and morphology. Lee and Song (2013) show a new Notch- and Reelin-dependent role for radial glia in the mouse spinal cord: to act as a fine filter that allows somatic motor neuron axons but not cell bodies to traverse out of the CNS. Here, the types of neuronal migration are discussed, focusing on motor neurons and cues for proper localization. The interaction of Reelin signaling with the Notch pathway is reviewed, which dictates the proper formation of radial glia in the spinal cord in order to prevent ectopic motor neuron migration (Lee and Song, 2013). Future studies may reveal novel interactions and further insights as to how Reelin functions throughout the developing nervous system. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Notch signaling inhibitor DAPT provides protection against acute craniocerebral injury.

    Directory of Open Access Journals (Sweden)

    Hong-Mei Zhang

    Full Text Available Notch signaling pathway is involved in many physiological and pathological processes. The γ-secretase inhibitor DAPT inhibits Notch signaling pathway and promotes nerve regeneration after cerebral ischemia. However, neuroprotective effects of DAPT against acute craniocerebral injury remain unclear. In this study, we established rat model of acute craniocerebral injury, and found that with the increase of damage grade, the expression of Notch and downstream protein Hes1 and Hes5 expression gradually increased. After the administration of DAPT, the expression of Notch, Hes1 and Hes5 was inhibited, apoptosis and oxidative stress decreased, neurological function and cognitive function improved. These results suggest that Notch signaling can be used as an indicator to assess the severity of post-traumatic brain injury. Notch inhibitor DAPT can reduce oxidative stress and apoptosis after acute craniocerebral injury, and is a potential drug for the treatment of acute craniocerebral injury.

  13. Inverse notch sensitivity: Cracks can make nonwoven fabrics stronger

    Science.gov (United States)

    Ridruejo, Alvaro; Jubera, Rafael; González, Carlos; LLorca, Javier

    2015-04-01

    The strength of materials is always reduced in the presence of notches and cracks and this phenomenon - known as notch sensitivity - is critical in structural design. Good structural materials (ductile metals, elastomers) tend to be notch insensitive, which was considered to be the optimum behavior. Here, we report that inverse notch insensitivity (where the failure stress of the notched specimen is higher than that of the unnotched counterpart) can be achieved in polypropylene nonwoven fabrics. This behavior is only possible because of the peculiar microstructure of nonwoven fabrics, in which fracture of interfiber bonds provides a source of non-linear deformation and leads to a change in the network topology. The former facilitates crack tip blunting, spreading damage in the ligament, while the re-orientation of the fibers perpendicular to the notch plane strengthens the material and improves the maximum load bearing capability.

  14. Optimal filtering

    CERN Document Server

    Anderson, Brian D O

    1979-01-01

    This graduate-level text augments and extends beyond undergraduate studies of signal processing, particularly in regard to communication systems and digital filtering theory. Vital for students in the fields of control and communications, its contents are also relevant to students in such diverse areas as statistics, economics, bioengineering, and operations research.Topics include filtering, linear systems, and estimation; the discrete-time Kalman filter; time-invariant filters; properties of Kalman filters; computational aspects; and smoothing of discrete-time signals. Additional subjects e

  15. Auditory filters at low-frequencies

    DEFF Research Database (Denmark)

    Orellana, Carlos Andrés Jurado; Pedersen, Christian Sejer; Møller, Henrik

    2009-01-01

    Prediction and assessment of low-frequency noise problems requires information about the auditory filter characteristics at low-frequencies. Unfortunately, data at low-frequencies is scarce and practically no results have been published for frequencies below 100 Hz. Extrapolation of ERB results...... from previous studies suggests the filter bandwidth keeps decreasing below 100 Hz, although at a relatively lower rate than at higher frequencies. Main characteristics of the auditory filter were studied from below 100 Hz up to 1000 Hz. Center frequencies evaluated were 50, 63, 125, 250, 500, and 1000...... Hz. The notched-noise method was used, with the noise masker at 40 dB spectral density. A rounded exponential auditory filter model (roex(p,r)) was used to fit the masking data. Preliminary data on 1 subject is discussed. Considering the system as a whole (e.g. without removing the assumed middle...

  16. A notch-wire composite antenna for polarization diversity reception

    OpenAIRE

    Kuga, Nobuhiro; Arai, H; Goto, N

    1998-01-01

    This paper presents a notch-wire composite antenna for polarization diversity reception in an indoor base-station system, A three-notched disk antenna and a wire antenna are proposed as component antennas for the horizontal and the vertical polarization, respectively. These component antennas are unified as a single composite diversity antenna by mounting the wire antenna on the notched disk. Antenna characteristics are calculated using the method of moments (MoM) with wire grid models and ex...

  17. Notch is required for long-term memory in Drosophila

    OpenAIRE

    Presente, Asaf; Boyles, Randy S.; Serway, Christine N.; de Belle, J. Steven; Andres, Andrew J.

    2004-01-01

    A role for Notch in the elaboration of existing neural processes is emerging that is distinct from the increasingly well understood function of this gene in binary cell-fate decisions. Several research groups, by using a variety of organisms, have shown that Notch is important in the development of neural ultrastructure. Simultaneously, Presenilin (Psn) was identified both as a key mediator of Notch signaling and as a site of genetic lesions that cause early-onset Alzheimer's disease. Here we...

  18. An Optical Additive Solc Filter for Deep Ultraviolet Applications

    Science.gov (United States)

    Manka, Charles; Nikitin, Sergei

    2008-10-01

    A number of optical applications in the deep ultra violet (DUV) range have limitations due to the absence of simple and reliable optical notch filters. This is important for resonant Raman applications that employ frequency agile laser illumination at many sequential DUV wavelengths. Our filter is based on widely known birefringent filter design originally proposed by Solc [I. Solc ``Birefringent chain filters'' JOSA 55, p.621 (1965)]. Rather than the transmission filter design of Solc, the additive Solc filter (ASF) described here is suitable for narrow-line rejection (constructed such a filter and present test results. Finally, we present a design which allows fiber delivery of DUV illumination wavelengths, rejects the quartz Raman lines generated in the fiber, but then rejects the backscattered unshifted light from a target and passes the Raman lines generated by the target material.

  19. Notch1 mutations are drivers of oral tumorigenesis

    Science.gov (United States)

    Jones, Sian; Brait, Mariana; Agrawal, Nishant; Koch, Wayne; McCord, Christine L.; Riley, David R.; Angiuoli, Samuel V.; Velculescu, Victor E.; Jiang, Wei-Wen; Sidransky, David

    2014-01-01

    Disruption of NOTCH1 signaling was recently discovered in head and neck cancer. This study aims to evaluate NOTCH1 alterations in the progression of oral squamous cell carcinoma (OSCC) and compare the occurrence of these mutations in Chinese and Caucasian populations. We used a high-throughput-PCR-based enrichment technology and next generation sequencing (NGS) to sequence NOTCH1 in 144 samples collected in China. Forty nine samples were normal oral mucosa from patients undergoing oral surgery, 45 were oral leukoplakia biopsies and 50 were chemoradiation naïve OSCC samples with 22 paired-normal tissues from the adjacent unaffected areas. NOTCH1 mutations were found in 54% of primary OSCC and 60% of pre-malignant lesions. Importantly, almost 60% of leukoplakia patients with mutated NOTCH1 carried mutations that were also identified in OSCC, indicating an important role of these clonal events in the progression of early neoplasms. We then compared all known NOTCH1 mutations identified in Chinese OSCC patients with those reported in Caucasians to date. Although we found obvious overlaps in critical regulatory NOTCH1 domains alterations and identified specific mutations shared by both groups, possible gain-of-function mutations were predominantly seen in Chinese population. Our findings demonstrate that pre-malignant lesions display NOTCH1 mutations at an early stage and are thus bona fide drivers of OSCC progression. Moreover, our results reveal that NOTCH1 promotes distinct tumorigenic mechanisms in patients from different ethnical populations. PMID:25406187

  20. Competition between Delta and the Abruptex domain of Notch

    Directory of Open Access Journals (Sweden)

    Baker Nicholas E

    2008-01-01

    Full Text Available Abstract Background Extracellular domains of the Notch family of signalling receptors contain many EGF repeat domains, as do their major ligands. Some EGF repeats are modified by O-fucosylation, and most have no identified role in ligand binding. Results Using a binding assay with purified proteins in vitro, it was determined that, in addition to binding to Delta, the ligand binding region of Notch bound to EGF repeats 22–27 of Notch, but not to other EGF repeat regions of Notch. EGF repeats 22–27 of Drosophila Notch overlap the genetically-defined 'Abruptex' region, and competed with Delta for binding to proteins containing the ligand-binding domain. Delta differed from the Abruptex domain in showing markedly enhanced binding at acid pH. Both Delta and the Abruptex region are heavily modified by protein O-fucosylation, but the split mutation of Drosophila Notch, which affects O-fucosylation of EGF repeat 14, did not affect binding of Notch to either Delta or the Abruptex region. Conclusion The Abruptex region may serve as a barrier to Notch activation by competing for the ligand-binding domain of Notch.