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Sample records for online filtering based

  1. 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.

  2. Online Variational Bayesian Filtering-Based Mobile Target Tracking in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Bingpeng Zhou

    2014-11-01

    Full Text Available The received signal strength (RSS-based online tracking for a mobile node in wireless sensor networks (WSNs is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision’s randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer–Rao Lower Bound (BCRLB analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

  3. Online variational Bayesian filtering-based mobile target tracking in wireless sensor networks.

    Science.gov (United States)

    Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

    2014-11-11

    The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer-Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

  4. Research on a Lamb Wave and Particle Filter-Based On-Line Crack Propagation Prognosis Method.

    Science.gov (United States)

    Chen, Jian; Yuan, Shenfang; Qiu, Lei; Cai, Jian; Yang, Weibo

    2016-03-03

    Prognostics and health management techniques have drawn widespread attention due to their ability to facilitate maintenance activities based on need. On-line prognosis of fatigue crack propagation can offer information for optimizing operation and maintenance strategies in real-time. This paper proposes a Lamb wave-particle filter (LW-PF)-based method for on-line prognosis of fatigue crack propagation which takes advantages of the possibility of on-line monitoring to evaluate the actual crack length and uses a particle filter to deal with the crack evolution and monitoring uncertainties. The piezoelectric transducers (PZTs)-based active Lamb wave method is adopted for on-line crack monitoring. The state space model relating to crack propagation is established by the data-driven and finite element methods. Fatigue experiments performed on hole-edge crack specimens have validated the advantages of the proposed method.

  5. Research on a Lamb Wave and Particle Filter-Based On-Line Crack Propagation Prognosis Method

    Directory of Open Access Journals (Sweden)

    Jian Chen

    2016-03-01

    Full Text Available Prognostics and health management techniques have drawn widespread attention due to their ability to facilitate maintenance activities based on need. On-line prognosis of fatigue crack propagation can offer information for optimizing operation and maintenance strategies in real-time. This paper proposes a Lamb wave-particle filter (LW-PF-based method for on-line prognosis of fatigue crack propagation which takes advantages of the possibility of on-line monitoring to evaluate the actual crack length and uses a particle filter to deal with the crack evolution and monitoring uncertainties. The piezoelectric transducers (PZTs-based active Lamb wave method is adopted for on-line crack monitoring. The state space model relating to crack propagation is established by the data-driven and finite element methods. Fatigue experiments performed on hole-edge crack specimens have validated the advantages of the proposed method.

  6. Online Sensor Fault Detection Based on an Improved Strong Tracking Filter

    Science.gov (United States)

    Wang, Lijuan; Wu, Lifeng; Guan, Yong; Wang, Guohui

    2015-01-01

    We propose a method for online sensor fault detection that is based on the evolving Strong Tracking Filter (STCKF). The cubature rule is used to estimate states to improve the accuracy of making estimates in a nonlinear case. A residual is the difference in value between an estimated value and the true value. A residual will be regarded as a signal that includes fault information. The threshold is set at a reasonable level, and will be compared with residuals to determine whether or not the sensor is faulty. The proposed method requires only a nominal plant model and uses STCKF to estimate the original state vector. The effectiveness of the algorithm is verified by simulation on a drum-boiler model. PMID:25690553

  7. Online Internal Temperature Estimation for Lithium-Ion Batteries Based on Kalman Filter

    Directory of Open Access Journals (Sweden)

    Jinlei Sun

    2015-05-01

    Full Text Available The battery internal temperature estimation is important for the thermal safety in applications, because the internal temperature is hard to measure directly. In this work, an online internal temperature estimation method based on a simplified thermal model using a Kalman filter is proposed. As an improvement, the influences of entropy change and overpotential on heat generation are analyzed quantitatively. The model parameters are identified through a current pulse test. The charge/discharge experiments under different current rates are carried out on the same battery to verify the estimation results. The internal and surface temperatures are measured with thermocouples for result validation and model construction. The accuracy of the estimated result is validated with a maximum estimation error of around 1 K.

  8. On-line prognosis of fatigue crack propagation based on Gaussian weight-mixture proposal particle filter.

    Science.gov (United States)

    Chen, Jian; Yuan, Shenfang; Qiu, Lei; Wang, Hui; Yang, Weibo

    2017-07-25

    Accurate on-line prognosis of fatigue crack propagation is of great meaning for prognostics and health management (PHM) technologies to ensure structural integrity, which is a challenging task because of uncertainties which arise from sources such as intrinsic material properties, loading, and environmental factors. The particle filter algorithm has been proved to be a powerful tool to deal with prognostic problems those are affected by uncertainties. However, most studies adopted the basic particle filter algorithm, which uses the transition probability density function as the importance density and may suffer from serious particle degeneracy problem. This paper proposes an on-line fatigue crack propagation prognosis method based on a novel Gaussian weight-mixture proposal particle filter and the active guided wave based on-line crack monitoring. Based on the on-line crack measurement, the mixture of the measurement probability density function and the transition probability density function is proposed to be the importance density. In addition, an on-line dynamic update procedure is proposed to adjust the parameter of the state equation. The proposed method is verified on the fatigue test of attachment lugs which are a kind of important joint components in aircraft structures. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. An online model-based method for state of energy estimation of lithium-ion batteries using dual filters

    Science.gov (United States)

    Dong, Guangzhong; Chen, Zonghai; Wei, Jingwen; Zhang, Chenbin; Wang, Peng

    2016-01-01

    The state-of-energy of lithium-ion batteries is an important evaluation index for energy storage systems in electric vehicles and smart grids. To improve the battery state-of-energy estimation accuracy and reliability, an online model-based estimation approach is proposed against uncertain dynamic load currents and environment temperatures. Firstly, a three-dimensional response surface open-circuit-voltage model is built up to improve the battery state-of-energy estimation accuracy, taking various temperatures into account. Secondly, a total-available-energy-capacity model that involves temperatures and discharge rates is reconstructed to improve the accuracy of the battery model. An extended-Kalman-filter and particle-filter based dual filters algorithm is then developed to establish an online model-based estimator for the battery state-of-energy. The extended-Kalman-filter is employed to update parameters of the battery model using real-time battery current and voltage at each sampling interval, while the particle-filter is applied to estimate the battery state-of-energy. Finally, the proposed approach is verified by experiments conducted on a LiFePO4 lithium-ion battery under different operating currents and temperatures. Experimental results indicate that the battery model simulates battery dynamics robustly with high accuracy, and the estimates of the dual filters converge to the real state-of-energy within an error of ±4%.

  10. Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

    Science.gov (United States)

    Kos, Marko; Grašič, Matej; Kačič, Zdravko

    2009-12-01

    This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE). The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

  11. Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy

    Directory of Open Access Journals (Sweden)

    Zdravko Kačič

    2009-01-01

    Full Text Available This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE. The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material.

  12. Analysis of a Kalman filter based method for on-line estimation of atmospheric dispersion parameters using radiation monitoring data

    DEFF Research Database (Denmark)

    Drews, Martin; Lauritzen, Bent; Madsen, Henrik

    2005-01-01

    A Kalman filter method is discussed for on-line estimation of radioactive release and atmospheric dispersion from a time series of off-site radiation monitoring data. The method is based on a state space approach, where a stochastic system equation describes the dynamics of the plume model...... parameters, and the observables are linked to the state variables through a static measurement equation. The method is analysed for three simple state space models using experimental data obtained at a nuclear research reactor. Compared to direct measurements of the atmospheric dispersion, the Kalman filter...... estimates are found to agree well with the measured parameters, provided that the radiation measurements are spread out in the cross-wind direction. For less optimal detector placement it proves difficult to distinguish variations in the source term and plume height; yet the Kalman filter yields consistent...

  13. On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure

    Directory of Open Access Journals (Sweden)

    Yuanqiang Ren

    2017-05-01

    Full Text Available Structural health monitoring (SHM of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

  14. On-Line Multi-Damage Scanning Spatial-Wavenumber Filter Based Imaging Method for Aircraft Composite Structure.

    Science.gov (United States)

    Ren, Yuanqiang; Qiu, Lei; Yuan, Shenfang; Bao, Qiao

    2017-05-11

    Structural health monitoring (SHM) of aircraft composite structure is helpful to increase reliability and reduce maintenance costs. Due to the great effectiveness in distinguishing particular guided wave modes and identifying the propagation direction, the spatial-wavenumber filter technique has emerged as an interesting SHM topic. In this paper, a new scanning spatial-wavenumber filter (SSWF) based imaging method for multiple damages is proposed to conduct on-line monitoring of aircraft composite structures. Firstly, an on-line multi-damage SSWF is established, including the fundamental principle of SSWF for multiple damages based on a linear piezoelectric (PZT) sensor array, and a corresponding wavenumber-time imaging mechanism by using the multi-damage scattering signal. Secondly, through combining the on-line multi-damage SSWF and a PZT 2D cross-shaped array, an image-mapping method is proposed to conduct wavenumber synthesis and convert the two wavenumber-time images obtained by the PZT 2D cross-shaped array to an angle-distance image, from which the multiple damages can be directly recognized and located. In the experimental validation, both simulated multi-damage and real multi-damage introduced by repeated impacts are performed on a composite plate structure. The maximum localization error is less than 2 cm, which shows good performance of the multi-damage imaging method. Compared with the existing spatial-wavenumber filter based damage evaluation methods, the proposed method requires no more than the multi-damage scattering signal and can be performed without depending on any wavenumber modeling or measuring. Besides, this method locates multiple damages by imaging instead of the geometric method, which helps to improve the signal-to-noise ratio. Thus, it can be easily applied to on-line multi-damage monitoring of aircraft composite structures.

  15. On-line crack prognosis in attachment lug using Lamb wave-deterministic resampling particle filter-based method

    Science.gov (United States)

    Yuan, Shenfang; Chen, Jian; Yang, Weibo; Qiu, Lei

    2017-08-01

    Fatigue crack growth prognosis is important for prolonging service time, improving safety, and reducing maintenance cost in many safety-critical systems, such as in aircraft, wind turbines, bridges, and nuclear plants. Combining fatigue crack growth models with the particle filter (PF) method has proved promising to deal with the uncertainties during fatigue crack growth and reach a more accurate prognosis. However, research on prognosis methods integrating on-line crack monitoring with the PF method is still lacking, as well as experimental verifications. Besides, the PF methods adopted so far are almost all sequential importance resampling-based PFs, which usually encounter sample impoverishment problems, and hence performs poorly. To solve these problems, in this paper, the piezoelectric transducers (PZTs)-based active Lamb wave method is adopted for on-line crack monitoring. The deterministic resampling PF (DRPF) is proposed to be used in fatigue crack growth prognosis, which can overcome the sample impoverishment problem. The proposed method is verified through fatigue tests of attachment lugs, which are a kind of important joint component in aerospace systems.

  16. Convergent Filter Bases

    OpenAIRE

    Coghetto Roland

    2015-01-01

    We are inspired by the work of Henri Cartan [16], Bourbaki [10] (TG. I Filtres) and Claude Wagschal [34]. We define the base of filter, image filter, convergent filter bases, limit filter and the filter base of tails (fr: filtre des sections).

  17. Convergent Filter Bases

    Directory of Open Access Journals (Sweden)

    Coghetto Roland

    2015-09-01

    Full Text Available We are inspired by the work of Henri Cartan [16], Bourbaki [10] (TG. I Filtres and Claude Wagschal [34]. We define the base of filter, image filter, convergent filter bases, limit filter and the filter base of tails (fr: filtre des sections.

  18. GA103 a microprogrammable processor for online filtering

    CERN Document Server

    Calzas, A; Danon, G

    1981-01-01

    GA103 is a 16 bit microprogrammable processor, which emulates the PDP 11 instruction set. It is based on the Am2900 slices. It allows user- implemented microinstructions and addition of hardwired processors. It will perform online filtering tasks in the NA14 experiment at CERN, based on the reconstruction of transverse momentum of photons detected in a lead glass calorimeter. (3 refs).

  19. Online Identification with Reliability Criterion and State of Charge Estimation Based on a Fuzzy Adaptive Extended Kalman Filter for Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Zhongwei Deng

    2016-06-01

    Full Text Available In the field of state of charge (SOC estimation, the Kalman filter has been widely used for many years, although its performance strongly depends on the accuracy of the battery model as well as the noise covariance. The Kalman gain determines the confidence coefficient of the battery model by adjusting the weight of open circuit voltage (OCV correction, and has a strong correlation with the measurement noise covariance (R. In this paper, the online identification method is applied to acquire the real model parameters under different operation conditions. A criterion based on the OCV error is proposed to evaluate the reliability of online parameters. Besides, the equivalent circuit model produces an intrinsic model error which is dependent on the load current, and the property that a high battery current or a large current change induces a large model error can be observed. Based on the above prior knowledge, a fuzzy model is established to compensate the model error through updating R. Combining the positive strategy (i.e., online identification and negative strategy (i.e., fuzzy model, a more reliable and robust SOC estimation algorithm is proposed. The experiment results verify the proposed reliability criterion and SOC estimation method under various conditions for LiFePO4 batteries.

  20. Internet Filtering Technology and Aversive Online Experiences in Adolescents.

    Science.gov (United States)

    Przybylski, Andrew K; Nash, Victoria

    2017-05-01

    To evaluate the effectiveness of Internet filtering tools designed to shield adolescents from aversive experiences online. A total of 1030 in-home interviews were conducted with early adolescents aged from 12 to 15 years (M = 13.50, SD = 1.18) and their caregivers. Caregivers were asked about their use of Internet filtering and adolescent participants were interviewed about their recent online experiences. Contrary to our hypotheses, policy, and industry advice regarding the assumed benefits of filtering we found convincing evidence that Internet filters were not effective at shielding early adolescents from aversive online experiences. Preregistered prospective and randomised controlled trials are needed to determine the extent to which Internet filtering technology supports vs thwarts young people online and if their widespread use justifies their financial and informational costs. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. An On-Line Modeling Based Kalman Filtering Process for Time-Interval-Variable Sequences with Application to Astronomic Surveying

    Institute of Scientific and Technical Information of China (English)

    韩建国; 孙才红; 李彦琴

    2003-01-01

    The problem of variable sampling time interval which appears in application of Kalman Filtering is analyzed and the corresponding filtering process with or without present transition matrix is suggested, then an application experiment for astronomical surveying is introduced. In this process, the known stochastically variable sampling time intervals play the roles as deterministic input sequences of the state-space description, and the corresponding matrix and (if needed) state transition matrix can be established by performing real-time and structure-linear system identification.

  2. Analysis of a Kalman filter based method for on-line estimation of atmospheric dispersion parameters using radiation monitoring data

    DEFF Research Database (Denmark)

    Drews, Martin; Lauritzen, Bent; Madsen, Henrik

    2005-01-01

    parameters, and the observables are linked to the state variables through a static measurement equation. The method is analysed for three simple state space models using experimental data obtained at a nuclear research reactor. Compared to direct measurements of the atmospheric dispersion, the Kalman filter...... estimates are found to agree well with the measured parameters, provided that the radiation measurements are spread out in the cross-wind direction. For less optimal detector placement it proves difficult to distinguish variations in the source term and plume height; yet the Kalman filter yields consistent...... scheme are outlined, to account for realistic accident scenarios....

  3. Sensor Fusion Based on an Integrated Neural Network and Probability Density Function (PDF) Dual Kalman Filter for On-Line Estimation of Vehicle Parameters and States.

    Science.gov (United States)

    Vargas-Melendez, Leandro; Boada, Beatriz L; Boada, Maria Jesus L; Gauchia, Antonio; Diaz, Vicente

    2017-04-29

    Vehicles with a high center of gravity (COG), such as light trucks and heavy vehicles, are prone to rollover. This kind of accident causes nearly 33 % of all deaths from passenger vehicle crashes. Nowadays, these vehicles are incorporating roll stability control (RSC) systems to improve their safety. Most of the RSC systems require the vehicle roll angle as a known input variable to predict the lateral load transfer. The vehicle roll angle can be directly measured by a dual antenna global positioning system (GPS), but it is expensive. For this reason, it is important to estimate the vehicle roll angle from sensors installed onboard in current vehicles. On the other hand, the knowledge of the vehicle's parameters values is essential to obtain an accurate vehicle response. Some of vehicle parameters cannot be easily obtained and they can vary over time. In this paper, an algorithm for the simultaneous on-line estimation of vehicle's roll angle and parameters is proposed. This algorithm uses a probability density function (PDF)-based truncation method in combination with a dual Kalman filter (DKF), to guarantee that both vehicle's states and parameters are within bounds that have a physical meaning, using the information obtained from sensors mounted on vehicles. Experimental results show the effectiveness of the proposed algorithm.

  4. On-line probabilistic classification with particle filters

    DEFF Research Database (Denmark)

    Højen-Sørensen, Pedro; de Freitas, N.; Fog, Torben L.

    2000-01-01

    We apply particle filters to the problem of on-line classification with possibly overlapping classes. This allows us to compute the probabilities of class membership as the classes evolve. Although we adopt neural network classifiers, the work can be extended to any other parametric classification...

  5. AMADEUS on-line trigger and filtering methods

    Energy Technology Data Exchange (ETDEWEB)

    Neff, M. [Erlangen Centre for Astroparticle Physics (ECAP), Friedrich-Alexander-Universitaet Erlangen-Nuernberg, Physikalisches Institut, Erwin-Rommel-Strasse 1, D-91058 Erlangen (Germany)], E-mail: max.neff@physik.uni-erlangen.de; Anton, G.; Graf, K.; Hoessl, J.; Katz, U.; Lahmann, R.; Richardt, C. [Erlangen Centre for Astroparticle Physics (ECAP), Friedrich-Alexander-Universitaet Erlangen-Nuernberg, Physikalisches Institut, Erwin-Rommel-Strasse 1, D-91058 Erlangen (Germany)

    2009-06-01

    AMADEUS is a system designed to investigate the method of acoustic particle detection for high energy neutrinos and the acoustic environment in the deep sea as part of the ANTARES neutrino telescope. In this context, six local clusters of six acoustic sensors each were integrated into the ANTARES infrastructure. The first three clusters have been taking data since December 2007 and the second three since the completion of ANTARES in May 2008. In the paper, the methods used for the on-line triggering and filtering of the data acquired with the AMADEUS set-up are described. On-shore, a dedicated computer-cluster is used to control the off-shore DAQ hardware, to process and store the acoustic data arriving from the sensors. On this cluster different data filtering schemes and triggers are implemented. Transient signals are selected by a variable threshold, which is self-adjusting to the changing conditions of the deep sea. For bipolar pulses-the characteristic acoustic signature of a neutrino-a pattern recognition is used based on cross-correlating the output of the sensors with a pre-defined bipolar pulse. To study the characteristics of the ambient noise in the deep sea an amount of unfiltered data is stored in regular intervals.

  6. Particle filter based entropy

    NARCIS (Netherlands)

    Boers, Y.; Driessen, Hans; Bagchi, Arunabha; Mandal, Pranab K.

    For many problems in the field of tracking or even the wider area of filtering the a posteriori description of the uncertainty can oftentimes not be described by a simple Gaussian density function. In such situations the characterization of the uncertainty by a mean and a covariance does not capture

  7. The Atlas Experiment On-Line Monitoring And Filtering As An Example Of Real-Time Application

    Directory of Open Access Journals (Sweden)

    K. Korcyl

    2008-01-01

    Full Text Available The ATLAS detector, recording LHC particles’ interactions, produces events with rate of40 MHz and size of 1.6 MB. The processes with new and interesting physics phenomena arevery rare, thus an efficient on-line filtering system (trigger is necessary. The asynchronouspart of that system relays on few thousands of computing nodes running the filtering software.Applying refined filtering criteria results in increase of processing times what may lead tolack of processing resources installed on CERN site. We propose extension to this part ofthe system based on submission of the real-time filtering tasks into the Grid.

  8. Information Filtering Based on Users' Negative Opinions

    Science.gov (United States)

    Guo, Qiang; Li, Yang; Liu, Jian-Guo

    2013-05-01

    The process of heat conduction (HC) has recently found application in the information filtering [Zhang et al., Phys. Rev. Lett.99, 154301 (2007)], which is of high diversity but low accuracy. The classical HC model predicts users' potential interested objects based on their interesting objects regardless to the negative opinions. In terms of the users' rating scores, we present an improved user-based HC (UHC) information model by taking into account users' positive and negative opinions. Firstly, the objects rated by users are divided into positive and negative categories, then the predicted interesting and dislike object lists are generated by the UHC model. Finally, the recommendation lists are constructed by filtering out the dislike objects from the interesting lists. By implementing the new model based on nine similarity measures, the experimental results for MovieLens and Netflix datasets show that the new model considering negative opinions could greatly enhance the accuracy, measured by the average ranking score, from 0.049 to 0.036 for Netflix and from 0.1025 to 0.0570 for Movielens dataset, reduced by 26.53% and 44.39%, respectively. Since users prefer to give positive ratings rather than negative ones, the negative opinions contain much more information than the positive ones, the negative opinions, therefore, are very important for understanding users' online collective behaviors and improving the performance of HC model.

  9. Gradient based filtering of digital elevation models

    DEFF Research Database (Denmark)

    Knudsen, Thomas; Andersen, Rune Carbuhn

    We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based on ...... in the landscape are washed out and misrepresented....

  10. Gradient based filtering of digital elevation models

    DEFF Research Database (Denmark)

    Knudsen, Thomas; Andersen, Rune Carbuhn

    We present a filtering method for digital terrain models (DTMs). The method is based on mathematical morphological filtering within gradient (slope) defined domains. The intention with the filtering procedure is to improbé the cartographic quality of height contours generated from a DTM based...

  11. Development and Validation of Search Filters to Identify Articles on Family Medicine in Online Medical Databases.

    Science.gov (United States)

    Pols, David H J; Bramer, Wichor M; Bindels, Patrick J E; van de Laar, Floris A; Bohnen, Arthur M

    2015-01-01

    Physicians and researchers in the field of family medicine often need to find relevant articles in online medical databases for a variety of reasons. Because a search filter may help improve the efficiency and quality of such searches, we aimed to develop and validate search filters to identify research studies of relevance to family medicine. Using a new and objective method for search filter development, we developed and validated 2 search filters for family medicine. The sensitive filter had a sensitivity of 96.8% and a specificity of 74.9%. The specific filter had a specificity of 97.4% and a sensitivity of 90.3%. Our new filters should aid literature searches in the family medicine field. The sensitive filter may help researchers conducting systematic reviews, whereas the specific filter may help family physicians find answers to clinical questions at the point of care when time is limited.

  12. Bayesian target tracking based on particle filter

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    For being able to deal with the nonlinear or non-Gaussian problems, particle filters have been studied by many researchers. Based on particle filter, the extended Kalman filter (EKF) proposal function is applied to Bayesian target tracking. Markov chain Monte Carlo (MCMC) method, the resampling step, etc novel techniques are also introduced into Bayesian target tracking. And the simulation results confirm the improved particle filter with these techniques outperforms the basic one.

  13. Digital notch filter based active damping for LCL filters

    DEFF Research Database (Denmark)

    Yao, Wenli; Yang, Yongheng; Zhang, Xiaobin

    2015-01-01

    . 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...... in the z-domain. Simulations and experiments are carried out to verify the proposed active damping method. Both results have confirmed that the notch filter based active damping can ensure the entire system stability in the case of resonances with a good system performance....

  14. Development and Validation of Search Filters to Identify Articles on Family Medicine in Online Medical Databases

    NARCIS (Netherlands)

    Pols, D.H.; Bramer, W.M.; Bindels, P.J.; Laar, F.A. van de; Bohnen, A.M.

    2015-01-01

    Physicians and researchers in the field of family medicine often need to find relevant articles in online medical databases for a variety of reasons. Because a search filter may help improve the efficiency and quality of such searches, we aimed to develop and validate search filters to identify

  15. Development and validation of search filters to identify articles on family medicine in online medical databases

    NARCIS (Netherlands)

    D.H.J. Pols (David); W.M. Bramer (Wichor); P.J.E. Bindels (Patrick J.E.); F.A. van de Laar (Floris A.); A.M. Bohnen

    2015-01-01

    textabstractPhysicians and researchers in the field of family medicine often need to find relevant articles in online medical databases for a variety of reasons. Because a search filter may help improve the efficiency and quality of such searches, we aimed to develop and validate search filters to

  16. Development and Validation of Search Filters to Identify Articles on Family Medicine in Online Medical Databases

    NARCIS (Netherlands)

    Pols, D.H.; Bramer, W.M.; Bindels, P.J.; Laar, F.A. van de; Bohnen, A.M.

    2015-01-01

    Physicians and researchers in the field of family medicine often need to find relevant articles in online medical databases for a variety of reasons. Because a search filter may help improve the efficiency and quality of such searches, we aimed to develop and validate search filters to identify rese

  17. Development and validation of search filters to identify articles on family medicine in online medical databases

    NARCIS (Netherlands)

    D.H.J. Pols (David); W.M. Bramer (Wichor M); P.J.E. Bindels (Patrick J.E.); F.A. van de Laar (Floris A.); A.M. Bohnen

    2015-01-01

    textabstractPhysicians and researchers in the field of family medicine often need to find relevant articles in online medical databases for a variety of reasons. Because a search filter may help improve the efficiency and quality of such searches, we aimed to develop and validate search filters to i

  18. Linear Regression Based Real-Time Filtering

    Directory of Open Access Journals (Sweden)

    Misel Batmend

    2013-01-01

    Full Text Available This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.

  19. Filter based phase distortions in extracellular spikes.

    Science.gov (United States)

    Yael, Dorin; Bar-Gad, Izhar

    2017-01-01

    Extracellular recordings are the primary tool for extracting neuronal spike trains in-vivo. One of the crucial pre-processing stages of this signal is the high-pass filtration used to isolate neuronal spiking activity. Filters are characterized by changes in the magnitude and phase of different frequencies. While filters are typically chosen for their effect on magnitudes, little attention has been paid to the impact of these filters on the phase of each frequency. In this study we show that in the case of nonlinear phase shifts generated by most online and offline filters, the signal is severely distorted, resulting in an alteration of the spike waveform. This distortion leads to a shape that deviates from the original waveform as a function of its constituent frequencies, and a dramatic reduction in the SNR of the waveform that disrupts spike detectability. Currently, the vast majority of articles utilizing extracellular data are subject to these distortions since most commercial and academic hardware and software utilize nonlinear phase filters. We show that this severe problem can be avoided by recording wide-band signals followed by zero phase filtering, or alternatively corrected by reversed filtering of a narrow-band filtered, and in some cases even segmented signals. Implementation of either zero phase filtering or phase correction of the nonlinear phase filtering reproduces the original spike waveforms and increases the spike detection rates while reducing the number of false negative and positive errors. This process, in turn, helps eliminate subsequent errors in downstream analyses and misinterpretations of the results.

  20. Filter based phase distortions in extracellular spikes

    Science.gov (United States)

    Yael, Dorin

    2017-01-01

    Extracellular recordings are the primary tool for extracting neuronal spike trains in-vivo. One of the crucial pre-processing stages of this signal is the high-pass filtration used to isolate neuronal spiking activity. Filters are characterized by changes in the magnitude and phase of different frequencies. While filters are typically chosen for their effect on magnitudes, little attention has been paid to the impact of these filters on the phase of each frequency. In this study we show that in the case of nonlinear phase shifts generated by most online and offline filters, the signal is severely distorted, resulting in an alteration of the spike waveform. This distortion leads to a shape that deviates from the original waveform as a function of its constituent frequencies, and a dramatic reduction in the SNR of the waveform that disrupts spike detectability. Currently, the vast majority of articles utilizing extracellular data are subject to these distortions since most commercial and academic hardware and software utilize nonlinear phase filters. We show that this severe problem can be avoided by recording wide-band signals followed by zero phase filtering, or alternatively corrected by reversed filtering of a narrow-band filtered, and in some cases even segmented signals. Implementation of either zero phase filtering or phase correction of the nonlinear phase filtering reproduces the original spike waveforms and increases the spike detection rates while reducing the number of false negative and positive errors. This process, in turn, helps eliminate subsequent errors in downstream analyses and misinterpretations of the results. PMID:28358895

  1. Model based optimization of EMC input filters

    Energy Technology Data Exchange (ETDEWEB)

    Raggl, K; Kolar, J. W. [Swiss Federal Institute of Technology, Power Electronic Systems Laboratory, Zuerich (Switzerland); Nussbaumer, T. [Levitronix GmbH, Zuerich (Switzerland)

    2008-07-01

    Input filters of power converters for compliance with regulatory electromagnetic compatibility (EMC) standards are often over-dimensioned in practice due to a non-optimal selection of number of filter stages and/or the lack of solid volumetric models of the inductor cores. This paper presents a systematic filter design approach based on a specific filter attenuation requirement and volumetric component parameters. It is shown that a minimal volume can be found for a certain optimal number of filter stages for both the differential mode (DM) and common mode (CM) filter. The considerations are carried out exemplarily for an EMC input filter of a single phase power converter for the power levels of 100 W, 300 W, and 500 W. (author)

  2. Multiway Filtering Based on Multilinear Algebra Tools

    Directory of Open Access Journals (Sweden)

    Salah Bourennane

    2010-03-01

    Full Text Available This paper presents some recent filtering methods based on the lower-rank tensor approximation approach for denoising tensor signals. In this approach, multicomponent data are represented by tensors, that is, multiway arrays, and the presented tensor filtering methods rely on multilinear algebra. First, the classical channel-by-channel SVD-based filtering method is overviewed. Then, an extension of the classical matrix filtering method is presented. It is based on the lower rank- K ,...,Kn  1 truncation of the HOSVD which performsa multimode Principal Component Analysis (PCA and is implicitly developed for an additive white Gaussian noise. Two tensor filtering methods recently developed by the authors are also overviewed. The performances and comparative results between all these tensor filtering methods are presented for the cases of noise reduction in color images.

  3. Multiway Filtering Based on Multilinear Algebra Tools

    Science.gov (United States)

    Bourennane, Salah; Fossati, Caroline

    This paper presents some recent filtering methods based on the lower-rank tensor approximation approach for denoising tensor signals. In this approach, multicomponent data are represented by tensors, that is, multiway arrays, and the presented tensor filtering methods rely on multilinear algebra. First, the classical channel-by-channel SVD-based filtering method is overviewed. Then, an extension of the classical matrix filtering method is presented. It is based on the lower rank-(K 1,...,K N ) truncation of the HOSVD which performs a multimode Principal Component Analysis (PCA) and is implicitly developed for an additive white Gaussian noise. Two tensor filtering methods recently developed by the authors are also overviewed. The performances and comparative results between all these tensor filtering methods are presented for the cases of noise reduction in color images.

  4. A SEMANTIC-BASED COLLABORATIVE FILTERING FOR RECOMMENDATION SYSTEMS

    OpenAIRE

    D.Jagadish *, A.Vishnu Kumar, R.Mani Raj

    2016-01-01

    In the present days the web domain is improved with new types of services, with the increase in service and cloud computing. As a result new forms of web content collecting/designing is done based on the numerous openly available web services online. These services are utilized in many ways by different domains and with the exponential growth of these web services users are experiencing difficulties in finding and utilizing a best matching service for their mashup. A collaborative filtering a...

  5. Prediction of XRF analyzers error for elements on-line assaying using Kalman Filter

    Institute of Scientific and Technical Information of China (English)

    Nakhaei F; Sam A; Mosavi MR; Nakhaei A

    2012-01-01

    Determination of chemical elements assay plays an important role in mineral processing operations.This factor is used to control process accuracy,recovery calculation and plant profitability.The new assaying methods including chemical methods,X-ray fluorescence and atomic absorption spectrometry are advanced and accurate.However,in some applications,such as on-line assaying process,high accuracy is required.In this paper,an algorithm based on Kalman Filter is presented to predict on-line XRF errors.This research has been carried out on the basis of based the industrial real data collection for evaluating the performance of the presented algorithm.The measurements and analysis for this study were conducted at the Sarcheshmeh Copper Concentrator Plant located in Iran.The quality of the obtained results was very satisfied; so that the RMS errors of prediction obtained for Cu and Mo grade assaying errors in rougher feed were less than 0.039 and 0.002 and in final flotation concentration less than 0.58 and 0.074,respectively.The results indicate that the mentioned method is quite accurate to reduce the on-line XRF errors measurement.

  6. Polarization control based interference microwave photonic filters

    Science.gov (United States)

    Madziar, Krzysztof; Galwas, Bogdan

    2016-12-01

    In this paper we present a concept of multi-line Microwave Photonic Filter (MPF) based on polarization beam splitting and polarization control in each line. Coefficients of investigated filter are determined by attenuation of its lines and that on the other hand can be manipulated by change of the polarization in the fiber. Presented results involve scattering parameters (S21) measurements of optical path over polarization control unit rotation, scattering parameters (S21) characteristics of investigated filter and transmission optimization capabilities.

  7. Problem-Based Learning Online

    DEFF Research Database (Denmark)

    Kolbæk, Ditte; Nortvig, Anne-Mette

    2017-01-01

    Problem- and Project-Based Learning (PBL) is a widely used pedagogical method in higher education. Although PBL encourages self-directed learning and works with the students’ own projects and problems, it also includes teacher presentations, discussions and group reflections, both on......-campus and online. Therefore, the teacher’s plans might be relevant to the students’ projects, but that is not always the case. This study investigates how master’s students interact with an online Problem-Based Learning design and examines how technology influences these interactions. The empirical data stem from...... lessons at an online master’s course, and they were collected and analyzed using a netnographic approach. The study finds that concepts like self-directed learning and active involvement of everyone can have very different meanings from the teachers’ and the students’ points of view. If the students do...

  8. Nuclear counting filter based on a centered Skellam test and a double exponential smoothing

    Energy Technology Data Exchange (ETDEWEB)

    Coulon, Romain; Kondrasovs, Vladimir; Dumazert, Jonathan; Rohee, Emmanuel; Normand Stephane [CEA, LIST, Laboratoire Capteurs et Architectures Electroniques, F-91191 Gif-sur-Yvette, (France)

    2015-07-01

    Online nuclear counting represents a challenge due to the stochastic nature of radioactivity. The count data have to be filtered in order to provide a precise and accurate estimation of the count rate, this with a response time compatible with the application in view. An innovative filter is presented in this paper addressing this issue. It is a nonlinear filter based on a Centered Skellam Test (CST) giving a local maximum likelihood estimation of the signal based on a Poisson distribution assumption. This nonlinear approach allows to smooth the counting signal while maintaining a fast response when brutal change activity occur. The filter has been improved by the implementation of a Brown's double Exponential Smoothing (BES). The filter has been validated and compared to other state of the art smoothing filters. The CST-BES filter shows a significant improvement compared to all tested smoothing filters. (authors)

  9. Intelligent neural-network-based adaptive power-line conditioner for real-time harmonics filtering

    Energy Technology Data Exchange (ETDEWEB)

    Lin, H.C. [Chien Kuo Institute of Technology (China). Dept. of Automation Engineering

    2004-09-01

    Conventional approaches for harmonic filtering usually employ either passive or active filtering techniques or a combination of both. The paper proposes an alternative intelligent adaptive power line conditioner (I-APLC), which. is a form of neural-network- based adaptive harmonic filtering. The I-APLC makes use of one supervised learning rule (backpropagation) which underlies the adaptive self-learning in realising the optimal filter weight vector. Experimental. results obtained via a prototype model of the DC variable-speed motor verified that I-APLC is feasible in terms of real-time tracking, adaptive harmonic filtering, faster training mid convergence speeds, and simplicity in the online hardware implementation. (author)

  10. CCII based fractional filters of different orders

    Directory of Open Access Journals (Sweden)

    Ahmed Soltan

    2014-03-01

    Full Text Available This paper aims to generalize the design of continuous-time filters to the fractional domain with different orders and validates the theoretical results with two different CCII based filters. In particular, the proposed study introduces the generalized formulas for the previous fractional-order analysis of equal orders. The fractional-order filters enhance the design flexibility and prove that the integer-order performance is a very narrow subset from the fractional-order behavior due to the extra degrees of freedom. The general fundamentals of these filters are presented by calculating the maximum and minimum frequencies, the half power frequency and the right phase frequency which are considered a critical issue for the filter design. Different numerical solutions for the generalized fractional order low pass filters with two different fractional order elements are introduced and verified by the circuit simulations of two fractional-order filters: Kerwin–Huelsman–Newcomb (KHN and Tow-Tomas CCII-based filters, showing great matching.

  11. Dominant Correlogram Based Particle Filter Tracking

    Institute of Scientific and Technical Information of China (English)

    MAO Yan-fen; SHI Peng-fei

    2005-01-01

    A novel dominant correlogram based particle filter was proposed for an object tracking in visual surveillance. Particle filter outperforms the Kalman filter in non-linear and non-Gaussian estimation problem. This paper proposed incorporating spatial information into visual feature, and yields a reliable likelihood description of the observation and prediction. A similarity-ratio is defined to evaluate the effectivity of different similarity measurements in weighing samples. The experimental results demonstrate the effective and robust performance compared with the histogram based tracking in traffic scenes.

  12. Image Filtering Based on Improved Information Entropy

    Institute of Scientific and Technical Information of China (English)

    JINGXiaojun; LIUYulin; XIONGYuqing

    2004-01-01

    An image filtering based on improved information entropy is proposed in this paper, which can overcome the shortcomings of hybrid linear and non-linear filtering algorithm. Due to the shortcomings of information entropy in the field of data fusion, we introduce the consistency constraint factor of sub-source report and subsource performance difference parameter, propose the concept of fusion entropy, utilize its amendment and regularity function on sub-source decision-making matrix, bring into play the competency, redundency and complementarity of information fusion, suppress and delete fault and invalid information, strengthen and preserve correct and useful information, overcome the risk of error reporting on single source critical point and the shortcomings of reliability and error tolerating, add the decision-making criteria of multiple sub-source fusion, finally improve filtering quality. Subsequent experiments show its validity and improved filtering performance, thus providing a new way of image filtering technique.

  13. Internet filters and entry pages do not protect children from online alcohol marketing.

    Science.gov (United States)

    Jones, Sandra C; Thom, Jeffrey A; Davoren, Sondra; Barrie, Lance

    2014-02-01

    We review programs and policies to prevent children from accessing alcohol marketing online. To update the literature, we present our recent studies that assess (i) in-built barriers to underage access to alcohol brand websites and (ii) commercial internet filters. Alcohol websites typically had poor filter systems for preventing entry of underage persons; only half of the sites required the user to provide a date of birth, and none had any means of preventing users from trying again. Even the most effective commercial internet filters allowed access to one-third of the sites we examined.

  14. On-line event filtering using the 168/E in CERN experiment NA4

    CERN Document Server

    Bogaerts, A; Eck, C; Lacourt, A; Ogilvie, J; Øverås, H; Petersen, J O; Rothan, B

    1981-01-01

    Summary form only given, as follows. The application of the 168/E IBM emulator as an on-line filter computer in experiment NA4 at the CERN SPS is described. Programs for the 168/E, developed and compiled on the IBM 370/168, are transferred in executable format to the NORD on- line computer through CERNET. The program modules are subsequently loaded into the 168/E program memory (32 kw, 24 bits) using a CAMAC interface module. This unit, when operated in a CAMAC dataway spy mode, also allows transfers of experimental data directly from CAMAC to the 168/E data memory (128 kbytes). However, in the burst environment of the SPS, events are usually buffered in the NORD computer memory. Filter programs include the data checking and tracking routines of the existing off-line production program. Because of the relatively small program size, complicated overlay structures are avoided. Based on IBM 370/168 performance figures for the production program, the 168/E program execution time per event is estimated to about 30...

  15. Adaptive Rate Sampling and Filtering Based on Level Crossing Sampling

    Directory of Open Access Journals (Sweden)

    Saeed Mian Qaisar

    2009-01-01

    Full Text Available The recent sophistications in areas of mobile systems and sensor networks demand more and more processing resources. In order to maintain the system autonomy, energy saving is becoming one of the most difficult industrial challenges, in mobile computing. Most of efforts to achieve this goal are focused on improving the embedded systems design and the battery technology, but very few studies target to exploit the input signal time-varying nature. This paper aims to achieve power efficiency by intelligently adapting the processing activity to the input signal local characteristics. It is done by completely rethinking the processing chain, by adopting a non conventional sampling scheme and adaptive rate filtering. The proposed approach, based on the LCSS (Level Crossing Sampling Scheme presents two filtering techniques, able to adapt their sampling rate and filter order by online analyzing the input signal variations. Indeed, the principle is to intelligently exploit the signal local characteristics—which is usually never considered—to filter only the relevant signal parts, by employing the relevant order filters. This idea leads towards a drastic gain in the computational efficiency and hence in the processing power when compared to the classical techniques.

  16. 基于自适应UKF算法的MEMS陀螺空中在线标定技术%In-flight on-line calibration method for MEMS gyroscope based on adaptive unscented Kalman filter algorithm

    Institute of Scientific and Technical Information of China (English)

    秦伟; 苑伟政; 常洪龙; 薛亮

    2011-01-01

    The attitude sensors need to be calibrated on-line in order to guarantee the performance of system in the application of the micro-satellite.A real-time drift error estimation method of MEMS gyroscope is presented by using three-axis magnetometer measurements without any external attitude reference.The unscented Kalman filter (UKF) is applied as the optimal estimation algorithm, the gyroscope drift is used as the filter state vector, and the finite difference of magnetometers observation is established as the measurement vector.Since the measurements of the magnetometers are susceptible to interferences, and this would lead to inaccuracy of the filter model, the adaptive UKF is applied to decrease the drift estimation errors of the gyroscope by monitoring the measurements vectors and adjusting its covariance matrix on-line.The experiment results indicate that the accuracy of the calibrated MEMS gyroscopes has improved about 30%, and the filter parameters are adjusted automatically when the magnetometer measurements are deteriorated, which make the filter convergence.Furthermore, the accuracy of dynamic attitude computed by the calibrated MEMS gyroscope is smaller than 2°.%为保证微型卫星定位应用中系统精度与稳定性,需要对姿态传感器进行实时在线标定.在无外界姿态参考时,提出一种用三轴磁强计测量值来实时估计MEMs陀螺的零漂误差的方法,采用UKF滤波算法,将陀螺漂移作为滤波状态向量,通过建立三轴磁强计测量微分方程,作为系统量测方程实现陀螺漂移的最优估计.针对磁强计测量信息易受干扰导致滤波量测模型不准确的问题,将自适应因子引入到UKF中,通过在线监控和调整测量误差,减少陀螺标定的估计误差,增强系统性能.实验结果表明,经过标定,MEMS陀螺精度提高约30%,并且在磁强计有外界干扰时,陀螺的标定结果收敛.将标定后的MEMS陀螺进行姿态解算,其动态误差小于2°.

  17. 光纤陀螺随机漂移在线建模实时滤波技术%Real-time Filtering Research Based on On-line Modeling Random Drift of FOG

    Institute of Scientific and Technical Information of China (English)

    金毅; 吴训忠; 谢聂; 郭创

    2015-01-01

    Establishing the model of FOG’s random drift and compensating in the filter is an effective method to improve the output precision of FOG. For traditional random drift of fiber optical gyroscope has some shortages like off-line, needing pre-process and the off-line models, which are usually not universal for environmental changing, a new modeling and filtering way is put forward. First, based on a large amount of measured data, the traditional off-line AR model is improved, and a new method to build the model of FOG’s random drift is studied. Then, the comparison is made between the traditional Kalman filter andH∞ filter in real time. The result demonstrates that improved AR model has much applicability and the performance ofH∞ filter is better than Kalman filter. The minimum value of fitting accuracy is 91.6% andH∞ filter can improve the performance of filtering by almost 38.5% when analyzing ingle noise.%建立光纤陀螺随机漂移模型以便在滤波中加以补偿是提高光纤陀螺输出精度的有效方法。针对传统光纤陀螺随机漂移建模均采用离线形式,需预先处理数据,不具备普适性等问题,提出一种实时的建模滤波方法。首先,根据大量实测数据对传统离线模型进行改进,研究了一种基于AR模型的在线建立光纤陀螺随机漂移模型的方法。然后,比较了传统Kalman滤波器与H∞滤波器用于实时滤波的效果。实验结果表明,改进型AR模型拟合精度高、普适性强,单个噪声拟合精度最低值为91.6%。H∞滤波器效果优于传统的 Kalman 滤波器,分析单个噪声滤波效果时,H∞滤波器较Kalman滤波器性能最多可提高38.5%。

  18. 基于鲁棒信息滤波器的图像雅可比矩阵在线估计%Online Estimation of Image Jacobian Matrix Based on Robust Information Filter

    Institute of Scientific and Technical Information of China (English)

    张捷; 刘丁

    2011-01-01

    This paper reviews present mainstream uncalibrated estimations of image Jacobian matrix (UM) , and analyzes methods based on Kalman Filter, Fuzzy Adaptive Kalman Filter and Particle Filter, as well as their advantages and disadvantages in detail. In order to improve system estimation precision in unknown environment, this paper selects the estimation framework based on filtering theory, adjusts the system model, utilizes Robust Information Filter (RIF) to estimate IJM, and realizes moving-object-tracking accurately in simulation and industrial robot system respectively. RIF is robust to bounded noise with any distribution, both simulation and experimental results verify the effectiveness of the introduced method.%针对现有的图像雅可比矩阵无标定求解方法,分析了基于Kalman滤波、模糊自适应Kalman滤波和粒子滤波的图像雅可比矩阵在线估计的优缺点.为了进一步提高未知环境下的系统估计精度,选择基于滤波理论的估计框架,对系统模型进行调整,用鲁棒信息滤波器在线估计图像雅可比矩阵,该滤波算法对任意分布的有界噪声都具有较强的鲁棒性.仿真和实验结果表明,在未知系统噪声的情况下,该算法仍可以实现图像雅可比矩阵的精确估计.

  19. Information Audit Based on Image Content Filtering

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    At present, network information audit system is almost based on text information filtering, but badness information is embedded into image or image file directly by badness information provider, in order to avoid monitored by. The paper realizes an information audit system based on image content filtering. Taking the pornographic program identification for an example, the system can monitor the video including any abnormal human body information by matching the texture characters with those defined in advance, which consist of contrast, energy, correlation measure and entropy character measure and so on.

  20. Matched filter based iterative adaptive approach

    Science.gov (United States)

    Nepal, Ramesh; Zhang, Yan Rockee; Li, Zhengzheng; Blake, William

    2016-05-01

    Matched Filter sidelobes from diversified LPI waveform design and sensor resolution are two important considerations in radars and active sensors in general. Matched Filter sidelobes can potentially mask weaker targets, and low sensor resolution not only causes a high margin of error but also limits sensing in target-rich environment/ sector. The improvement in those factors, in part, concern with the transmitted waveform and consequently pulse compression techniques. An adaptive pulse compression algorithm is hence desired that can mitigate the aforementioned limitations. A new Matched Filter based Iterative Adaptive Approach, MF-IAA, as an extension to traditional Iterative Adaptive Approach, IAA, has been developed. MF-IAA takes its input as the Matched Filter output. The motivation here is to facilitate implementation of Iterative Adaptive Approach without disrupting the processing chain of traditional Matched Filter. Similar to IAA, MF-IAA is a user parameter free, iterative, weighted least square based spectral identification algorithm. This work focuses on the implementation of MF-IAA. The feasibility of MF-IAA is studied using a realistic airborne radar simulator as well as actual measured airborne radar data. The performance of MF-IAA is measured with different test waveforms, and different Signal-to-Noise (SNR) levels. In addition, Range-Doppler super-resolution using MF-IAA is investigated. Sidelobe reduction as well as super-resolution enhancement is validated. The robustness of MF-IAA with respect to different LPI waveforms and SNR levels is also demonstrated.

  1. Optimal Sensor Decision Based on Particle Filter

    Institute of Scientific and Technical Information of China (English)

    XU Meng; WANG Hong-wei; HU Shi-qiang

    2006-01-01

    A novel infrared and radar synergistic tracking algorithm, which is based on the idea of closed loop control, and target's motion model identification and particle filter approach, was put forward. In order to improve the observability and filtering divergence of infrared search and tracking, the unscented Kalman filter algorithm that has stronger ability of non-linear approximation was adopted. The polynomial and least square method based on radar and IRST measurements to identify the parameters of the model was proposed, and a "pseudo sensor" was suggested to estimate the target position according to the identified model even if the radar is turned off. At last,the average Kullback-Leibler discrimination distance based on particle filter was used to measure the tracking performance, based on tracking performance and fuzzy stochastic decision, the idea of closed loop was used to retrieve the module parameter of "pseudo sensor". The experimental result indicates that the algorithm can not only limit the radar activity effectively but also keep the tracking accuracy of active/passive system well.

  2. Multi scale feature based matched filter processing

    Institute of Scientific and Technical Information of China (English)

    LI Jun; HOU Chaohuan

    2004-01-01

    Using the extreme difference of self-similarity and kurtosis at large level scale of wavelet transform approximation between the PTFM (Pulse Trains of Frequency Modulated)signals and its reverberation, a feature-based matched filter method using the classify-beforedetect paragriam is proposed to improve the detection performance in reverberation and multipath environments. Processing the data of lake-trails showed that the processing gain of the proposed method is bigger than that of matched filter about 10 dB. In multipath environments, detection performance of matched filter become badly poorer, while that of the proposed method is improved better. It shows that the method is much more robust with the effect of multipath.

  3. Low power adder based auditory filter architecture.

    Science.gov (United States)

    Rahiman, P F Khaleelur; Jayanthi, V S

    2014-01-01

    Cochlea devices are powered up with the help of batteries and they should possess long working life to avoid replacing of devices at regular interval of years. Hence the devices with low power consumptions are required. In cochlea devices there are numerous filters, each responsible for frequency variant signals, which helps in identifying speech signals of different audible range. In this paper, multiplierless lookup table (LUT) based auditory filter is implemented. Power aware adder architectures are utilized to add the output samples of the LUT, available at every clock cycle. The design is developed and modeled using Verilog HDL, simulated using Mentor Graphics Model-Sim Simulator, and synthesized using Synopsys Design Compiler tool. The design was mapped to TSMC 65 nm technological node. The standard ASIC design methodology has been adapted to carry out the power analysis. The proposed FIR filter architecture has reduced the leakage power by 15% and increased its performance by 2.76%.

  4. A family of quantization based piecewise linear filter networks

    DEFF Research Database (Denmark)

    Sørensen, John Aasted

    1992-01-01

    A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization of...

  5. Chi-squared smoothed adaptive particle-filtering based prognosis

    Science.gov (United States)

    Ley, Christopher P.; Orchard, Marcos E.

    2017-01-01

    This paper presents a novel form of selecting the likelihood function of the standard sequential importance sampling/re-sampling particle filter (SIR-PF) with a combination of sliding window smoothing and chi-square statistic weighting, so as to: (a) increase the rate of convergence of a flexible state model with artificial evolution for online parameter learning (b) improve the performance of a particle-filter based prognosis algorithm. This is applied and tested with real data from oil total base number (TBN) measurements from three haul trucks. The oil data has high measurement uncertainty and an unknown phenomenological state model. Performance of the proposed algorithm is benchmarked against the standard form of SIR-PF estimation which utilises the Normal (Gaussian) likelihood function. Both implementations utilise the same particle filter based prognosis algorithm so as to provide a common comparison. A sensitivity analysis is also performed to further explore the effects of the combination of sliding window smoothing and chi-square statistic weighting to the SIR-PF.

  6. Nonlocal means filter-based speckle tracking.

    Science.gov (United States)

    Afsham, Narges; Rasoulian, Abtin; Najafi, Mohammad; Abolmaesumi, Purang; Rohling, Robert

    2015-08-01

    The objective of sensorless freehand 3-D ultrasound imaging is to eliminate the need for additional tracking hardware and reduce cost and complexity. However, the accuracy of current out-of-plane pose estimation is main obstacle for full 6-degree-of-freedom (DoF) tracking. We propose a new filter-based speckle tracking framework to increase the accuracy of out-of-plane displacement estimation. In this framework, we use the displacement estimation not only for the specific speckle pattern, but for the entire image. We develop a nonlocal means (NLM) filter based on a probabilistic normal variance mixture model of ultrasound, known as Rician-inverse Gaussian (RiIG). To aggregate the local displacement estimations, Stein's unbiased risk estimate (SURE) is used as a quality measure of the estimations. We derive an explicit analytical form of SURE for the RiIG model and use it as a weight factor. The proposed filter-based speckle tracking framework is formulated and evaluated for three commonly used noise models, including the RiIG model. The out-of-plane estimations are compared with our previously proposed model-based algorithm in a set of ex vivo experiments for different tissue types. We show that the proposed RiIG filter-based method is more accurate and less tissue-dependent than the other methods. The proposed method is also evaluated in vivo on the spines of five different subjects to assess the feasibility of a clinical application. The 6-DoF transform parameters are estimated and compared with the electromagnetic tracker measurements. The results show higher tracking accuracy for typical small lateral displacements and tilt rotations between image pairs.

  7. Improved image filter based on SPCNN

    Institute of Scientific and Technical Information of China (English)

    ZHANG YuDong; WU LeNan

    2008-01-01

    By extraction of the thoughts of non-linear model and adaptive model match, an improved Nagao filter is brought. Meanwhile a technique based on simplified pulse coupled neural network and used for noise positioning, is put forward. Combining the two methods above, we acquire a new method that can restore images corrupted by salt and pepper noise. Experiments show that this method is more preferable than other popular ones, and still works well while noise density fluctuates severely.

  8. Fingerprint Verification based on Gabor Filter Enhancement

    CERN Document Server

    Lavanya, B N; Venugopal, K R

    2009-01-01

    Human fingerprints are reliable characteristics for personnel identification as it is unique and persistence. A fingerprint pattern consists of ridges, valleys and minutiae. In this paper we propose Fingerprint Verification based on Gabor Filter Enhancement (FVGFE) algorithm for minutiae feature extraction and post processing based on 9 pixel neighborhood. A global feature extraction and fingerprints enhancement are based on Hong enhancement method which is simultaneously able to extract local ridge orientation and ridge frequency. It is observed that the Sensitivity and Specificity values are better compared to the existing algorithms.

  9. Ensembles of adaptive spatial filters increase BCI performance: an online evaluation

    Science.gov (United States)

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

    2016-08-01

    Objective: In electroencephalographic (EEG) data, signals from distinct sources within the brain are widely spread by volume conduction and superimposed such that sensors receive mixtures of a multitude of signals. This reduction of spatial information strongly hampers single-trial analysis of EEG data as, for example, required for brain-computer interfacing (BCI) when using features from spontaneous brain rhythms. Spatial filtering techniques are therefore greatly needed to extract meaningful information from EEG. Our goal is to show, in online operation, that common spatial pattern patches (CSPP) are valuable to counteract this problem. Approach: Even though the effect of spatial mixing can be encountered by spatial filters, there is a trade-off between performance and the requirement of calibration data. Laplacian derivations do not require calibration data at all, but their performance for single-trial classification is limited. Conversely, data-driven spatial filters, such as common spatial patterns (CSP), can lead to highly distinctive features; however they require a considerable amount of training data. Recently, we showed in an offline analysis that CSPP can establish a valuable compromise. In this paper, we confirm these results in an online BCI study. In order to demonstrate the paramount feature that CSPP requires little training data, we used them in an adaptive setting with 20 participants and focused on users who did not have success with previous BCI approaches. Main results: The results of the study show that CSPP adapts faster and thereby allows users to achieve better feedback within a shorter time than previous approaches performed with Laplacian derivations and CSP filters. The success of the experiment highlights that CSPP has the potential to further reduce BCI inefficiency. Significance: CSPP are a valuable compromise between CSP and Laplacian filters. They allow users to attain better feedback within a shorter time and thus reduce BCI

  10. Knowledge-based inference engine for online video dissemination

    Science.gov (United States)

    Zhou, Wensheng; Kuo, C.-C. Jay

    2000-10-01

    To facilitate easy access to rich information of multimedia over the Internet, we develop a knowledge-based classification system that supports automatic Indexing and filtering based on semantic concepts for the dissemination of on-line real-time media. Automatic segmentation, annotation and summarization of media for fast information browsing and updating are achieved in the same time. In the proposed system, a real-time scene-change detection proxy performs an initial video structuring process by splitting a video clip into scenes. Motional and visual features are extracted in real time for every detected scene by using online feature extraction proxies. Higher semantics are then derived through a joint use of low-level features along with inference rules in the knowledge base. Inference rules are derived through a supervised learning process based on representative samples. On-line media filtering based on semantic concepts becomes possible by using the proposed video inference engine. Video streams are either blocked or sent to certain channels depending on whether or not the video stream is matched with the user's profile. The proposed system is extensively evaluated by applying the engine to video of basketball games.

  11. Adaptive Filter Based on Gradient Information

    Institute of Scientific and Technical Information of China (English)

    JINGXiaojun; LIJiangfeng; YANGYixian

    2003-01-01

    In this paper, an adaptive smoothing filter algorithm based on gradient information is proposed. The new method solves the problem of conventional filer that can't smooth noise and sharp edge simultaneously. It is based on the iterative convolution of local adaptive template and the original image signal, the template has the property of diffusing anisotropically. In each iteration, the weight coefficients of filter are determined by the gradient function of each pixel, and they vary with the variety of the gradient function, thus reflects the degree of continuity of the gray value. The weight coefficients also depend on one parameter, which controls the amplitude of the breaking point that needs to be preserved during the iteration. This algorithm sharps the edge of image by iterative computation, and after several iterations the image is adaptively smoothed according to the edge blocking. The simulation results demonstrate that this algorithm can perform filtering effectively. It has appropriate computation complexity and is suitable for real-time processing.

  12. Information filtering based on wiki index database

    CERN Document Server

    Smirnov, A V

    2008-01-01

    In this paper we present a profile-based approach to information filtering by an analysis of the content of text documents. The Wikipedia index database is created and used to automatically generate the user profile from the user document collection. The problem-oriented Wikipedia subcorpora are created (using knowledge extracted from the user profile) for each topic of user interests. The index databases of these subcorpora are applied to filtering information flow (e.g., mails, news). Thus, the analyzed texts are classified into several topics explicitly presented in the user profile. The paper concentrates on the indexing part of the approach. The architecture of an application implementing the Wikipedia indexing is described. The indexing method is evaluated using the Russian and Simple English Wikipedia.

  13. Self-tuning decoupled fusion Kalman filter based on the Riccati equation

    Institute of Scientific and Technical Information of China (English)

    Xiaojun SUN; Peng ZHANG; Zili DENG

    2008-01-01

    An online noise variance estimator for multi-sensor systems with unknown noise variances is proposed by using the correlation method. Based on the Riccati equa-tion and optimal fusion rule "weighted by scalars for state components, a self-tuning component decoupled informa-tion fusion Kalman filter is presented. It is proved that the filter converges to the optimal fusion Kalman filter in a realization by dynamic error system analysis method, so that it has asymptotic optimality. Its effectiveness is demon-strated by simulation for a tracking system with 3 sensors.

  14. Linear filtering of images based on properties of vision.

    Science.gov (United States)

    Algazi, V R; Ford, G E; Chen, H

    1995-01-01

    The design of linear image filters based on properties of human visual perception has been shown to require the minimization of criterion functions in both the spatial and frequency domains. We extend this approach to continuous filters of infinite support. For lowpass filters, this leads to the concept of an ideal lowpass image filter that provides a response that is superior perceptually to that of the classical ideal lowpass filter.

  15. Adaptive integrated navigation filtering based on accelerometer calibration

    Directory of Open Access Journals (Sweden)

    Qifan Zhou

    2012-11-01

    Full Text Available In this paper, a novel GPS (Global Positioning System and DR (Dead Reckoning system which was based on the accelerometer and gyroscope integrated system was designed and implemented. In this system, the odometer used in traditional DR system was replaced by a MEMS tri-axis accelerometer in order to decrease the cost and the volume of the system. The system was integrated by the Kalman filter and a new mathematical model was introduced. In order to reasonably use the GPS information, an adaptive algorithm based on single measurement system which could estimate the measurement noise covariance was obtained. On the purpose of reducing the effect of the accumulated error caused by drift and bias of accelerometer, the accelerometer was calibrated online when GPS performed well. In this way, the integrated system could not only obtain the high-precision positioning in real time, but also perform stably in practice.

  16. Power active filter control based on a resonant disturbance observer

    OpenAIRE

    Ramos Fuentes, German A.; Cortés Romero, John Alexander; Zou, Zhixiang; Costa Castelló, Ramon; Zhou, Keliang

    2015-01-01

    Active filters are power electronics devices used to eliminate harmonics from the distribution network. This article presents an active disturbance rejection control scheme for active filters. The controller is based on a linear disturbance observer combined with a disturbance rejection scheme. The parameter tuning is based on a combined pole placement and an optimal estimation based on Kalman-Bucy filter. Proposed scheme is validated through simulation and experimental work in an active filter.

  17. Pascal-Interpolation-Based Noninteger Delay Filter and Low-Complexity Realization

    Directory of Open Access Journals (Sweden)

    P. Soontornwong

    2015-12-01

    Full Text Available This paper proposes a new method for designing the polynomial-interpolation-type noninteger-delay filter with a new structure formulation. Since the design formulation and the new realization structure are based on the discrete Pascal transform (DPT and Pascal interpolation, we call the resulting filter Pascal noninteger-delay filter. The kth-order Pascal polynomial is used to pass through the given (k+1 data points in achieving the kth-order Pascal filter. The Pascal noninteger-delay filter is a real-time filter that consists of two sections, which can be realized into the front-section and the back-section. The front-section contains multiplication-free digital filters, and the number of multiplications in the back-section just linearly increases as order becomes high. Since the new Pascal filter has low complexity and structure can adjust non-integer delay online, it is more suited for fast delay tuning. Consequently, the polynomial-interpolation-type delay filter can be achieved by using the Pascal approach with high efficiency and low-complexity structure.

  18. Improved Kalman Filter-Based Speech Enhancement with Perceptual Post-Filtering

    Institute of Scientific and Technical Information of China (English)

    WEIJianqiang; DULimin; YANZhaoli; ZENGHui

    2004-01-01

    In this paper, a Kalman filter-based speech enhancement algorithm with some improvements of previous work is presented. A new technique based on spectral subtraction is used for separation speech and noise characteristics from noisy speech and for the computation of speech and noise Autoregressive (AR) parameters. In order to obtain a Kalman filter output with high audible quality, a perceptual post-filter is placed at the output of the Kalman filter to smooth the enhanced speech spectra.Extensive experiments indicate that this newly proposed method works well.

  19. Extended Kalman Filter Based Neural Networks Controller For Hot Strip Rolling mill

    Science.gov (United States)

    Moussaoui, A. K.; Abbassi, H. A.; Bouazza, S.

    2008-06-01

    The present paper deals with the application of an Extended Kalman filter based adaptive Neural-Network control scheme to improve the performance of a hot strip rolling mill. The suggested Neural Network model was implemented using Bayesian Evidence based training algorithm. The control input was estimated iteratively by an on-line extended Kalman filter updating scheme basing on the inversion of the learned neural networks model. The performance of the controller is evaluated using an accurate model estimated from real rolling mill input/output data, and the usefulness of the suggested method is proved.

  20. Personalized Service System Based on Hybrid Filtering for Digital Library

    Institute of Scientific and Technical Information of China (English)

    GAO Fengrong; XING Chunxiao; DU Xiaoyong; WANG Shan

    2007-01-01

    Personalized service systems are an effective way to help users obtain recommendations for unseen items, within the enormous volume of information available based on their preferences. The most commonly used personalized service system methods are collaborative filtering, content-based filtering, and hybrid filtering. Unfortunately,each method has its drawbacks. This paper proposes a new method which unified partition-based collaborative filtering and meta-information filtering.In partition-based collaborative filtering the user-item rating matrix can be partitioned into low-dimensional dense materces using a matrixclustering algorithm. Recommendations are generated based on these low-dimensional matrices.Additionally,the very low ratings problem can be solved using meta-information filtering. The unified method is applied to a digital resource management system. The experimental results show the high efficiency and good performance of the new approach.

  1. SU-E-J-127: Implementation of An Online Replanning Tool for VMAT Using Flattening Filter-Free Beams

    Energy Technology Data Exchange (ETDEWEB)

    Ates, O; Ahunbay, E; Li, X [Medical College of Wisconsin, Milwaukee, WI (United States)

    2015-06-15

    Purpose: This is to report the implementation of an online replanning tool based on segment aperture morphing (SAM) for VMAT with flattening filter free (FFF) beams. Methods: Previously reported SAM algorithm modified to accommodate VMAT with FFF beams was implemented in a tool that was interfaced with a treatment planning system (Monaco, Elekta). The tool allows (1) to output the beam parameters of the original VMAT plan from Monaco, and (2) to input the apertures generated from the SAM algorithm into Monaco for the dose calculation on daily CT/CBCT/MRI in the following steps:(1) Quickly generating target contour based on the image of the day, using an auto-segmentation tool (ADMIRE, Elekta) with manual editing if necessary; (2) Morphing apertures based on the SAM in the original VMAT plan to account for the interfractional change of the target from the planning to the daily images; (3) Calculating dose distribution for new apertures with the same numbers of MU as in the original plan; (4) Transferring the new plan into a record & verify system (MOSAIQ, Elekta); (5) Performing a pre-delivery QA based on software; (6) Delivering the adaptive plan for the fraction.This workflow was implemented on a 16-CPU (2.6 GHz dual-core) hardware with GPU and was tested for sample cases of prostate, pancreas and lung tumors. Results: The online replanning process can be completed within 10 minutes. The adaptive plans generally have improved the plan quality when compared to the IGRT repositioning plans. The adaptive plans with FFF beams have better normal tissue sparing as compared with those of FF beams. Conclusion: The online replanning tool based on SAM can quickly generate adaptive VMAT plans using FFF beams with improved plan quality than those from the IGRT repositioning plans based on daily CT/CBCT/MRI and can be used clinically. This research was supported by Elekta Inc. (Crawley, UK)

  2. Accurate mask-based spatially regularized correlation filter for visual tracking

    Science.gov (United States)

    Gu, Xiaodong; Xu, Xinping

    2017-01-01

    Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

  3. The effect of heterogeneous dynamics of online users on information filtering

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Bo-Lun [Department of Computer Science, Yangzhou University of China, Yangzhou 225127 (China); Department of Computer Science, Nanjing University of Aeronautics and Astronautics of China, Nanjing 210016 (China); Department of Physics, University of Fribourg, Chemin du Musee 3, CH-1700 Fribourg (Switzerland); Zeng, An, E-mail: anzeng@bnu.edu.cn [School of Systems Science, Beijing Normal University, Beijing 100875 (China); Chen, Ling [Department of Computer Science, Yangzhou University of China, Yangzhou 225127 (China); Department of Computer Science, Nanjing University of Aeronautics and Astronautics of China, Nanjing 210016 (China)

    2015-11-06

    The rapid expansion of the Internet requires effective information filtering techniques to extract the most essential and relevant information for online users. Many recommendation algorithms have been proposed to predict the future items that a given user might be interested in. However, there is an important issue that has always been ignored so far in related works, namely the heterogeneous dynamics of online users. The interest of active users changes more often than that of less active users, which asks for different update frequency of their recommendation lists. In this paper, we develop a framework to study the effect of heterogeneous dynamics of users on the recommendation performance. We find that the personalized application of recommendation algorithms results in remarkable improvement in the recommendation accuracy and diversity. Our findings may help online retailers make better use of the existing recommendation methods. - Highlights: • We study the effect of heterogeneous dynamics of users on recommendation. • Due to the user heterogeneity, their amount of links in the probe set is different. • The personalized algorithm implementation improves the recommendation performance. • Our results suggest different update frequency for users – recommendation list.

  4. Impact imaging of aircraft composite structure based on a model-independent spatial-wavenumber filter.

    Science.gov (United States)

    Qiu, Lei; Liu, Bin; Yuan, Shenfang; Su, Zhongqing

    2016-01-01

    The spatial-wavenumber filtering technique is an effective approach to distinguish the propagating direction and wave mode of Lamb wave in spatial-wavenumber domain. Therefore, it has been gradually studied for damage evaluation in recent years. But for on-line impact monitoring in practical application, the main problem is how to realize the spatial-wavenumber filtering of impact signal when the wavenumber of high spatial resolution cannot be measured or the accurate wavenumber curve cannot be modeled. In this paper, a new model-independent spatial-wavenumber filter based impact imaging method is proposed. In this method, a 2D cross-shaped array constructed by two linear piezoelectric (PZT) sensor arrays is used to acquire impact signal on-line. The continuous complex Shannon wavelet transform is adopted to extract the frequency narrowband signals from the frequency wideband impact response signals of the PZT sensors. A model-independent spatial-wavenumber filter is designed based on the spatial-wavenumber filtering technique. Based on the designed filter, a wavenumber searching and best match mechanism is proposed to implement the spatial-wavenumber filtering of the frequency narrowband signals without modeling, which can be used to obtain a wavenumber-time image of the impact relative to a linear PZT sensor array. By using the two wavenumber-time images of the 2D cross-shaped array, the impact direction can be estimated without blind angle. The impact distance relative to the 2D cross-shaped array can be calculated by using the difference of time-of-flight between the frequency narrowband signals of two different central frequencies and the corresponding group velocities. The validations performed on a carbon fiber composite laminate plate and an aircraft composite oil tank show a good impact localization accuracy of the model-independent spatial-wavenumber filter based impact imaging method.

  5. Radar Image Texture Classification based on Gabor Filter Bank

    Directory of Open Access Journals (Sweden)

    Mbainaibeye Jérôme

    2014-01-01

    Full Text Available The aim of this paper is to design and develop a filter bank for the detection and classification of radar image texture with 4.6m resolution obtained by airborne synthetic Aperture Radar. The textures of this kind of images are more correlated and contain forms with random disposition. The design and the developing of the filter bank is based on Gabor filter. We have elaborated a set of filters applied to each set of feature texture allowing its identification and enhancement in comparison with other textures. The filter bank which we have elaborated is represented by a combination of different texture filters. After processing, the selected filter bank is the filter bank which allows the identification of all the textures of an image with a significant identification rate. This developed filter is applied to radar image and the obtained results are compared with those obtained by using filter banks issue from the generalized Gaussian models (GGM. We have shown that Gabor filter developed in this work gives the classification rate greater than the results obtained by Generalized Gaussian model. The main contribution of this work is the generation of the filter banks able to give an optimal filter bank for a given texture and in particular for radar image textures

  6. Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics

    Institute of Scientific and Technical Information of China (English)

    Zhaoxia PU; Joshua HACKER

    2009-01-01

    This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, ensemble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined.

  7. DOCCⅡ-based electronically tunable current-mode biquadratic filters

    Institute of Scientific and Technical Information of China (English)

    Wang Weidong

    2005-01-01

    A complete state variable current-mode biquadratic filter built by duo-output CCⅡ (DOCCⅡ) with variable current gain is presented. All the coefficients of the filter can be independently tuned through the variable current gain factors of the DOCCⅡ. Based on the principles upon which the general biquadratic filter was constructed, a universal electronically tunable current-mode filter is proposed which implements the low-pass, high-pass, band-pass, band-suppress and all-pass second order transfer functions simultaneously. The PSPICE simulations of frequency responses of second-order filter of are also given.

  8. Online cross-validation-based ensemble learning.

    Science.gov (United States)

    Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

    2017-05-04

    Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  9. Ring-resonator-based wavelength filters

    NARCIS (Netherlands)

    Geuzebroek, D.H.; Driessen, A.; Venghaus, H.

    2006-01-01

    Microring resonators (MR) represent a class of filters with characteristics very similar to those of Fabry–Perot filters. However, they offer the advantage that the injected and reflected signals are separated in individual waveguides, and in addition, their design does not require any facets or

  10. Multispectral image filtering method based on image fusion

    Science.gov (United States)

    Zhang, Wei; Chen, Wei

    2015-12-01

    This paper proposed a novel filter scheme by image fusion based on Nonsubsampled ContourletTransform(NSCT) for multispectral image. Firstly, an adaptive median filter is proposed which shows great advantage in speed and weak edge preserving. Secondly, the algorithm put bilateral filter and adaptive median filter on image respectively and gets two denoised images. Then perform NSCT multi-scale decomposition on the de-noised images and get detail sub-band and approximate sub-band. Thirdly, the detail sub-band and approximate sub-band are fused respectively. Finally, the object image is obtained by inverse NSCT. Simulation results show that the method has strong adaptability to deal with the textural images. And it can suppress noise effectively and preserve the image details. This algorithm has better filter performance than the Bilateral filter standard and median filter and theirs improved algorithms for different noise ratio.

  11. Optimization-based particle filter for state and parameter estimation

    Institute of Scientific and Technical Information of China (English)

    Li Fu; Qi Fei; Shi Guangming; Zhang Li

    2009-01-01

    In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.

  12. Design of Absorbing Wave Maker based on Digital Filters

    DEFF Research Database (Denmark)

    Christensen, Morten; Frigaard, Peter

    An absorbing wave maker operated by means of on-line signals from digital FIR filters is presented. Surface elevations are measured in two positions in front of the wave maker. The reflected wave train is seperated by the sum of the incident and reflected wave trains by means of digital filtering...... and subsequent superposition of the measured surface elevations. The motion of the wave paddle required to absorb reflected waves is determined and added to the original wave paddle control signal. Irregular wave tests involving test structures with different degrees of reflection show that excellent absorption...

  13. Si-based infrared optical filters

    Science.gov (United States)

    Balčytis, Armandas; Ryu, Meguya; Seniutinas, Gediminas; Nishijima, Yoshiaki; Hikima, Yuta; Zamengo, Massimiliano; Petruškevičius, Raimondas; Morikawa, Junko; Juodkazis, Saulius

    2015-12-01

    Pyramidal silicon nanospikes, termed black-Si (b-Si), with controlled height of 0.2 to 1 μm, were fabricated by plasma etching over 3-in wafers and were shown to act as variable density filters in a wide range of the IR spectrum 2.5 to 20 μm, with transmission and its spectral gradient dependent on the height of the spikes. Such variable density IR filters can be utilized for imaging and monitoring applications. Narrow IR notch filters were realized with gold mesh arrays on Si wafers prospective for applications in surface-enhanced IR absorption sensing and "cold materials" for heat radiation into atmospheric IR transmission window. Both types of filters for IR: spectrally variable and notch are made by simple fabrication methods.

  14. Gabor filter based fingerprint image enhancement

    Science.gov (United States)

    Wang, Jin-Xiang

    2013-03-01

    Fingerprint recognition technology has become the most reliable biometric technology due to its uniqueness and invariance, which has been most convenient and most reliable technique for personal authentication. The development of Automated Fingerprint Identification System is an urgent need for modern information security. Meanwhile, fingerprint preprocessing algorithm of fingerprint recognition technology has played an important part in Automatic Fingerprint Identification System. This article introduces the general steps in the fingerprint recognition technology, namely the image input, preprocessing, feature recognition, and fingerprint image enhancement. As the key to fingerprint identification technology, fingerprint image enhancement affects the accuracy of the system. It focuses on the characteristics of the fingerprint image, Gabor filters algorithm for fingerprint image enhancement, the theoretical basis of Gabor filters, and demonstration of the filter. The enhancement algorithm for fingerprint image is in the windows XP platform with matlab.65 as a development tool for the demonstration. The result shows that the Gabor filter is effective in fingerprint image enhancement technology.

  15. PKI Interoperability Based on Online Certificate Validation

    Directory of Open Access Journals (Sweden)

    Dinu Smadu

    2011-03-01

    Full Text Available One of the most important problems related to Public Key Infrastructures is the validation of the digital certificates. Certificate validation services can be based on offline and/or online schemes. Offline schemes have the major disadvantage that they cannot always give an up-to-date response. On the other side, the most used protocol for online validation, the Online Certificate Status Protocol [1], also has its drawbacks. It can only state if a certificate has been revoked or not. RFC 5055 [2] defines a more complex protocol, the Server-based Certificate Validation Protocol (SCVP, capable of building and validating the certification path. To implement a basic functionality of this new protocol, we will start from an existing project, the CADDISK and we will try to implement an OpenSSL module.

  16. Low Power Systolic Array Based Digital Filter for DSP Applications

    Directory of Open Access Journals (Sweden)

    S. Karthick

    2015-01-01

    Full Text Available Main concepts in DSP include filtering, averaging, modulating, and correlating the signals in digital form to estimate characteristic parameter of a signal into a desirable form. This paper presents a brief concept of low power datapath impact for Digital Signal Processing (DSP based biomedical application. Systolic array based digital filter used in signal processing of electrocardiogram analysis is presented with datapath architectural innovations in low power consumption perspective. Implementation was done with ASIC design methodology using TSMC 65 nm technological library node. The proposed systolic array filter has reduced leakage power up to 8.5% than the existing filter architectures.

  17. Low Power Systolic Array Based Digital Filter for DSP Applications.

    Science.gov (United States)

    Karthick, S; Valarmathy, S; Prabhu, E

    2015-01-01

    Main concepts in DSP include filtering, averaging, modulating, and correlating the signals in digital form to estimate characteristic parameter of a signal into a desirable form. This paper presents a brief concept of low power datapath impact for Digital Signal Processing (DSP) based biomedical application. Systolic array based digital filter used in signal processing of electrocardiogram analysis is presented with datapath architectural innovations in low power consumption perspective. Implementation was done with ASIC design methodology using TSMC 65 nm technological library node. The proposed systolic array filter has reduced leakage power up to 8.5% than the existing filter architectures.

  18. Michelson interferometer based interleaver design using classic IIR filter decomposition.

    Science.gov (United States)

    Cheng, Chi-Hao; Tang, Shasha

    2013-12-16

    An elegant method to design a Michelson interferometer based interleaver using a classic infinite impulse response (IIR) filter such as Butterworth, Chebyshev, and elliptic filters as a starting point are presented. The proposed design method allows engineers to design a Michelson interferometer based interleaver from specifications seamlessly. Simulation results are presented to demonstrate the validity of the proposed design method.

  19. Sigma Delta Modulation Based Ternary FIR Filter Mapping on FPGA

    Directory of Open Access Journals (Sweden)

    Tayabuddin Memon

    2011-07-01

    Full Text Available In this paper single-bit SDM (Sigma Delta Modulation based TFF (Ternary FIR Filter with balanced ternary coefficients (i.e. -1/0/+1 has been mapped on small commercially available FPGAs (Field Programmable Gate Arrays. Filter coefficients were obtained using second order sigma delta modulator. The filter structure is based on a hierarchical adder tree that can easily be pipelined for high performance purpose. Filter structure was coded in VHDL (Very High Speed Integrated Circuit Hardware Description Language and simulated in Quartus-II software. The filter exhibits low I/O (Input Output and core area usage and high performance-achieving clock speeds close to 200MHz on a low-cost FPGA and over 500MHz on a latest FPGA commercially available device. This single-bit ternary filter is intended to support video and audio processing applications in mobile communication systems.

  20. An integrated delta-sigma based IIR filter

    Science.gov (United States)

    Au, Dennis Kin-Wah

    Delta-sigma based infinite impulse response (IIR) filters are a recently developed circuit technique for efficiently realizing IIR filters operating directly on oversampled delta-sigma modulated signals. The design and single-chip implementation of a fifth-order delta-sigma based IIR filter are described. The filter coefficients are fully programmable and with the use of a structure that is inherently scaled for dynamic range, good filter performance is maintained over a wide variety of transfer functions. To eliminate multi-bit multiplications, five second-order digital delta-sigma modulators were used and dynamic range improvement was obtained through the use of multi-bit quantizers in these modulators. The filter was implemented as a very large scale integration chip using 1.2 micron complementary metal oxide semiconductor technology, occupying an area of 4,355 by 5,962 square microns. Simulations indicate that the clock range should operate up to 45 MHz.

  1. Noncausal spatial prediction filtering based on an ARMA model

    Institute of Scientific and Technical Information of China (English)

    Liu Zhipeng; Chen Xiaohong; Li Jingye

    2009-01-01

    Conventional f-x prediction filtering methods are based on an autoregressive model. The error section is first computed as a source noise but is removed as additive noise to obtain the signal, which results in an assumption inconsistency before and after filtering. In this paper, an autoregressive, moving-average model is employed to avoid the model inconsistency. Based on the ARMA model, a noncasual prediction filter is computed and a self-deconvolved projection filter is used for estimating additive noise in order to suppress random noise. The 1-D ARMA model is also extended to the 2-D spatial domain, which is the basis for noncasual spatial prediction filtering for random noise attenuation on 3-D seismic data. Synthetic and field data processing indicate this method can suppress random noise more effectively and preserve the signal simultaneously and does much better than other conventional prediction filtering methods.

  2. Vehicle Sideslip Angle Estimation Based on Hybrid Kalman Filter

    Directory of Open Access Journals (Sweden)

    Jing Li

    2016-01-01

    Full Text Available Vehicle sideslip angle is essential for active safety control systems. This paper presents a new hybrid Kalman filter to estimate vehicle sideslip angle based on the 3-DoF nonlinear vehicle dynamic model combined with Magic Formula tire model. The hybrid Kalman filter is realized by combining square-root cubature Kalman filter (SCKF, which has quick convergence and numerical stability, with square-root cubature based receding horizon Kalman FIR filter (SCRHKF, which has robustness against model uncertainty and temporary noise. Moreover, SCKF and SCRHKF work in parallel, and the estimation outputs of two filters are merged by interacting multiple model (IMM approach. Experimental results show the accuracy and robustness of the hybrid Kalman filter.

  3. Triplet based online track finding in the PANDA-STT

    Science.gov (United States)

    Mertens, M. C.; Panda Collaboration

    2014-04-01

    The PANDA-Experiment at the future FAIR facility in Darmstadt will study antiproton-proton collisions in a fixed-target setup with a phase-space cooled antiproton beam with a momentum from 1.5 to 15 GeV/c at a nominal interaction rate of 2 · 107 s-1. The data acquisition of the detectors has to run in a triggerless mode and the physics events of interest are identified by an online event filter. Tracking information is a key input for the event filter to distinguish signal events from background. A variety of tracking algorithms is foreseen to process the different track topologies. The so-called Triplet Finder, which is presented here, is a track finding algorithm based on the central straw tube tracker (STT) of PANDA. The algorithm focuses on mathematical simplicity and robustness to allow an online processing of the incoming detector hits. The algorithm and results of a proof-of-concept implementation are presented.

  4. Fuzzy neural network image filter based on GA

    Institute of Scientific and Technical Information of China (English)

    刘涵; 刘丁; 李琦

    2004-01-01

    A new nonlinear image filter using fuzzy neural network based on genetic algorithm is proposed. The learning of network parameters is performed by genetic algorithm with the efficient binary encoding scheme. In the following,fuzzy reasoning embedded in the network aims at restoring noisy pixels without degrading the quality of fine details. It is shown by experiments that the filter is very effective in removing impulse noise and significantly outperforms conventional filters.

  5. Biogas Filter Based on Local Natural Zeolite Materials

    OpenAIRE

    Satriyo Krido Wahono; Wahyu Anggo Rizal

    2014-01-01

    UPT BPPTK LIPI has created a biogas filter tool to improve the purity of methane in the biogas. The device shaped cylindrical tube containing absorbent materials which based on local natural zeolite of Indonesia. The absorbent has been activated and modified with other materials. This absorbtion material has multi-adsorption capacity for almost impurities gas of biogas. The biogas  filter increase methane content of biogas for 5-20%. The biogas filter improve the biogas’s performance such as ...

  6. An enhancement algorithm for low quality fingerprint image based on edge filter and Gabor filter

    Science.gov (United States)

    Xue, Jun-tao; Liu, Jie; Liu, Zheng-guang

    2009-07-01

    On account of restriction of man-made and collection environment, the fingerprint image generally has low quality, especially a contaminated background. In this paper, an enhancement algorithm based on edge filter and Gabor filter is proposed to solve this kind of fingerprint image. Firstly, a gray-based algorithm is used to enhance the edge and segment the image. Then, a multilevel block size method is used to extract the orientation field from segmented fingerprint image. Finally, Gabor filter is used to fulfill the enhancement of the fingerprint image. The experiment results show that the proposed enhancement algorithm is effective than the normal Gabor filter algorithm. The fingerprint image enhance by our algorithm has better enhancement effect, so it is helpful for the subsequent research, such as classification, feature exaction and identification.

  7. Online damage detection in structural systems applications of proper orthogonal decomposition, and Kalman and particle filters

    CERN Document Server

    Eftekhar Azam, Saeed

    2014-01-01

    This monograph assesses in depth the application of recursive Bayesian filters in structural health monitoring. Although the methods and algorithms used here are well established in the field of automatic control, their application in the realm of civil engineering has to date been limited. The monograph is therefore intended as a reference for structural and civil engineers who wish to conduct research in this field. To this end, the main notions underlying the families of Kalman and particle filters are scrutinized through explanations within the text and numerous numerical examples. The main limitations to their application in monitoring of high-rise buildings are discussed, and a remedy based on a synergy of reduced order modeling (based on proper orthogonal decomposition) and Bayesian estimation is proposed. The performance and effectiveness of the proposed algorithm is demonstrated via pseudo-experimental evaluations.

  8. CMS OnlineWeb-Based Monitoring

    Science.gov (United States)

    Badgett, William; Chakaberia, Irakli; Lopez-Perez, Juan Antonio; Maeshima, Kaori; Maruyama, Sho; Soha, Aron; Sulmanas, Balys; Wan, Zongru

    For large international High Energy Physics experiments, modern web technologies make the online monitoring of detector status, data acquisition status, trigger rates, luminosity, etc., accessible for the collaborators anywhere and anytime. This helps the collaborating experts monitor the status of the experiment, identify the problems and improve data taking efficiency. We present the online Web-Based Monitoring project of the CMS experiment at the LHC at CERN.The data sources are relational databasesandvarious messaging systems. The projectprovidesavast amountof in-depth information including real-time data, historical trends and correlations in a user-friendly way.

  9. Optimal Source-Based Filtering of Malicious Traffic

    CERN Document Server

    Soldo, Fabio; Markopoulou, Athina

    2010-01-01

    In this paper, we consider the problem of blocking malicious traffic on the Internet, via source-based filtering. In particular, we consider filtering via access control lists (ACLs): these are already available at the routers today but are a scarce resource because they are stored in the expensive ternary content addressable memory (TCAM). Aggregation (by filtering source prefixes instead of individual IP addresses) helps reduce the number of filters, but comes also at the cost of blocking legitimate traffic originating from the filtered prefixes. We show how to optimally choose which source prefixes to filter, for a variety of realistic attack scenarios and operators' policies. In each scenario, we design optimal, yet computationally efficient, algorithms. Using logs from Dshield.org, we evaluate the algorithms and demonstrate that they bring significant benefit in practice.

  10. A new mixed-mode filter based on MDDCCs

    Science.gov (United States)

    Wang, Lixue; Wang, Chunyue; Zhang, Junru; Liang, Xiao; Jiang, Shuangshuang

    2015-12-01

    A new mixed mode filter based on MDDCC (Modify Differential Difference Current Conveyor) is proposed, the structure of filter is simple, the circuit consist of only three active MDDCCs, five resistors and three grounded capacitors. The filter can realize the filter of current mode and voltage mode, which can realize the function of low pass biquad, band pass biquad and high pass biquad simultaneously. The computer simulation of PSPICE uses 0.18μm TSMC CMOS and the theoretical results are validated the proposed circuit.

  11. Radar Image Texture Classification based on Gabor Filter Bank

    OpenAIRE

    Mbainaibeye Jérôme; Olfa Marrakchi Charfi

    2014-01-01

    The aim of this paper is to design and develop a filter bank for the detection and classification of radar image texture with 4.6m resolution obtained by airborne synthetic Aperture Radar. The textures of this kind of images are more correlated and contain forms with random disposition. The design and the developing of the filter bank is based on Gabor filter. We have elaborated a set of filters applied to each set of feature texture allowing its identification and enhancement in comparison w...

  12. Multi-scale retinex with color restoration image enhancement based on Gaussian filtering and guided filtering

    Science.gov (United States)

    Ma, Jinxiang; Fan, Xinnan; Ni, Jianjun; Zhu, Xifang; Xiong, Chao

    2017-07-01

    In order to restore image color and enhance contrast of remote sensing image without suffering from color cast and insufficient detail enhancement, a novel improved multi-scale retinex with color restoration (MSRCR) image enhancement algorithm based on Gaussian filtering and guided filtering was proposed in this paper. Firstly, multi-scale Gaussian filtering functions were used to deal with the original image to obtain the rough illumination components. Secondly, accurate illumination components were acquired by using the guided filtering functions. Then, combining with four-direction Sobel edge detector, a self-adaptive weight selection nonlinear image enhancement was carried out. Finally, a series of evaluate metrics such as mean, MSE, PSNR, contrast and information entropy were used to assess the enhancement algorithm. The results showed that the proposed algorithm can suppress effectively noise interference, enhance the image quality and restore image color effectively.

  13. Cost-Based Domain Filtering for Stochastic Constraint Programming

    NARCIS (Netherlands)

    Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.

    2008-01-01

    Cost-based filtering is a novel approach that combines techniques from Operations Research and Constraint Programming to filter from decision variable domains values that do not lead to better solutions [7]. Stochastic Constraint Programming is a framework for modeling combinatorial optimization pro

  14. 3D Wavelet-Based Filter and Method

    Science.gov (United States)

    Moss, William C.; Haase, Sebastian; Sedat, John W.

    2008-08-12

    A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.

  15. Hyperconnected Attribute Filters Based on k-Flat Zones

    NARCIS (Netherlands)

    Ouzounis, Georgios K.; Wilkinson, Michael H.F.

    2011-01-01

    In this paper, we present a new method for attribute filtering, combining contrast and structural information. Using hyperconnectivity based on k-flat zones, we improve the ability of attribute filters to retain internal details in detected objects. Simultaneously, we improve the suppression of smal

  16. Cost-Based Domain Filtering for Stochastic Constraint Programming

    NARCIS (Netherlands)

    Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.

    2008-01-01

    Cost-based filtering is a novel approach that combines techniques from Operations Research and Constraint Programming to filter from decision variable domains values that do not lead to better solutions [7]. Stochastic Constraint Programming is a framework for modeling combinatorial optimization pro

  17. Hyperconnected Attribute Filters Based on k-Flat Zones

    NARCIS (Netherlands)

    Ouzounis, Georgios K.; Wilkinson, Michael H.F.

    In this paper, we present a new method for attribute filtering, combining contrast and structural information. Using hyperconnectivity based on k-flat zones, we improve the ability of attribute filters to retain internal details in detected objects. Simultaneously, we improve the suppression of

  18. Particle filtering based structural assessment with acoustic emission sensing

    Science.gov (United States)

    Yan, Wuzhao; Abdelrahman, Marwa; Zhang, Bin; Ziehl, Paul

    2017-02-01

    Nuclear structures are designed to withstand severe loading events under various stresses. Over time, aging of structural systems constructed with concrete and steel will occur. This deterioration may reduce service life of nuclear facilities and/or lead to unnecessary or untimely repairs. Therefore, online monitoring of structures in nuclear power plants and waste storage has drawn significant attention in recent years. Of many existing non-destructive evaluation and structural monitoring approaches, acoustic emission is promising for assessment of structural damage because it is non-intrusive and is sensitive to corrosion and crack growth in reinforced concrete elements. To provide a rapid, actionable, and graphical means for interpretation Intensity Analysis plots have been developed. This approach provides a means for classification of damage. Since the acoustic emission measurement is only an indirect indicator of structural damage, potentially corrupted by non-genuine data, it is more suitable to estimate the states of corrosion and cracking in a Bayesian estimation framework. In this paper, we will utilize the accelerated corrosion data from a specimen at the University of South Carolina to develop a particle filtering-based diagnosis and prognosis algorithm. Promising features of the proposed algorithm are described in terms of corrosion state estimation and prediction of degradation over time to a predefined threshold.

  19. Dip-separated structural filtering using seislet transform and adaptive empirical mode decomposition based dip filter

    Science.gov (United States)

    Chen, Yangkang

    2016-07-01

    The seislet transform has been demonstrated to have a better compression performance for seismic data compared with other well-known sparsity promoting transforms, thus it can be used to remove random noise by simply applying a thresholding operator in the seislet domain. Since the seislet transform compresses the seismic data along the local structures, the seislet thresholding can be viewed as a simple structural filtering approach. Because of the dependence on a precise local slope estimation, the seislet transform usually suffers from low compression ratio and high reconstruction error for seismic profiles that have dip conflicts. In order to remove the limitation of seislet thresholding in dealing with conflicting-dip data, I propose a dip-separated filtering strategy. In this method, I first use an adaptive empirical mode decomposition based dip filter to separate the seismic data into several dip bands (5 or 6). Next, I apply seislet thresholding to each separated dip component to remove random noise. Then I combine all the denoised components to form the final denoised data. Compared with other dip filters, the empirical mode decomposition based dip filter is data-adaptive. One only needs to specify the number of dip components to be separated. Both complicated synthetic and field data examples show superior performance of my proposed approach than the traditional alternatives. The dip-separated structural filtering is not limited to seislet thresholding, and can also be extended to all those methods that require slope information.

  20. Variable Step Size Maximum Correntropy Criteria Based Adaptive Filtering Algorithm

    Directory of Open Access Journals (Sweden)

    S. Radhika

    2016-04-01

    Full Text Available Maximum correntropy criterion (MCC based adaptive filters are found to be robust against impulsive interference. This paper proposes a novel MCC based adaptive filter with variable step size in order to obtain improved performance in terms of both convergence rate and steady state error with robustness against impulsive interference. The optimal variable step size is obtained by minimizing the Mean Square Deviation (MSD error from one iteration to the other. Simulation results in the context of a highly impulsive system identification scenario show that the proposed algorithm has faster convergence and lesser steady state error than the conventional MCC based adaptive filters.

  1. Covariance matching based adaptive unscented Kalman filter for direct filtering in INS/GNSS integration

    Science.gov (United States)

    Meng, Yang; Gao, Shesheng; Zhong, Yongmin; Hu, Gaoge; Subic, Aleksandar

    2016-03-01

    The use of the direct filtering approach for INS/GNSS integrated navigation introduces nonlinearity into the system state equation. As the unscented Kalman filter (UKF) is a promising method for nonlinear problems, an obvious solution is to incorporate the UKF concept in the direct filtering approach to address the nonlinearity involved in INS/GNSS integrated navigation. However, the performance of the standard UKF is dependent on the accurate statistical characterizations of system noise. If the noise distributions of inertial instruments and GNSS receivers are not appropriately described, the standard UKF will produce deteriorated or even divergent navigation solutions. This paper presents an adaptive UKF with noise statistic estimator to overcome the limitation of the standard UKF. According to the covariance matching technique, the innovation and residual sequences are used to determine the covariance matrices of the process and measurement noises. The proposed algorithm can estimate and adjust the system noise statistics online, and thus enhance the adaptive capability of the standard UKF. Simulation and experimental results demonstrate that the performance of the proposed algorithm is significantly superior to that of the standard UKF and adaptive-robust UKF under the condition without accurate knowledge on system noise, leading to improved navigation precision.

  2. Artificial neural network (ANN)-based prediction of depth filter loading capacity for filter sizing.

    Science.gov (United States)

    Agarwal, Harshit; Rathore, Anurag S; Hadpe, Sandeep Ramesh; Alva, Solomon J

    2016-11-01

    This article presents an application of artificial neural network (ANN) modelling towards prediction of depth filter loading capacity for clarification of a monoclonal antibody (mAb) product during commercial manufacturing. The effect of operating parameters on filter loading capacity was evaluated based on the analysis of change in the differential pressure (DP) as a function of time. The proposed ANN model uses inlet stream properties (feed turbidity, feed cell count, feed cell viability), flux, and time to predict the corresponding DP. The ANN contained a single output layer with ten neurons in hidden layer and employed a sigmoidal activation function. This network was trained with 174 training points, 37 validation points, and 37 test points. Further, a pressure cut-off of 1.1 bar was used for sizing the filter area required under each operating condition. The modelling results showed that there was excellent agreement between the predicted and experimental data with a regression coefficient (R(2) ) of 0.98. The developed ANN model was used for performing variable depth filter sizing for different clarification lots. Monte-Carlo simulation was performed to estimate the cost savings by using different filter areas for different clarification lots rather than using the same filter area. A 10% saving in cost of goods was obtained for this operation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1436-1443, 2016.

  3. A filter based encoding model for mouse retinal ganglion cells.

    Science.gov (United States)

    Zhong, Q; Roychowdhury, V; Boykin, P; Jacobs, A; Nirenberg, S

    2005-01-01

    We adopt a system theoretic approach and explore the model of retinal ganglion cells as linear filters followed by a maximum-likelihood Bayesian predictor. We evaluate the model by using cross-validation, i.e., first the model parameters are estimated using a training set, and then the prediction error is computed (by comparing the stochastic rate predicted by the model with the rate code of the response) for a test set. As in system identification theory, we present spatially uniform stimuli to the retina, whose temporal intensity is drawn independently from a Gaussian distribution, and we simultaneously record the spike trains from multiple neurons. The optimal linear filter for each cell is obtained by maximizing the mutual information between the filtered stimulus values and the output of the cell (as measured in terms of a stochastic rate code). Our results show that the model presented in this paper performs well on the test set, and it outperforms the identity Bayesian model and the traditional linear model. Moreover, in order to reduce the number of optimal filters needed for prediction, we cluster the cells based on the filters' shapes, and use the cluster consensus filters to predict the firing rates of all neurons in the same class. We obtain almost the same performance with these cluster filters. These results provide hope that filter-based retinal prosthetics might be an effective and feasible idea.

  4. Online Project Based Learning in Innovation Management.

    Science.gov (United States)

    O'Sullivan, David

    2003-01-01

    An innovation management course has three strands with face-to-face and online components: (1) seminars with online course notes and slides; (2) assignments (group online case studies, tutorials, in-class presentations); and (3) assessment (online, oral, in-class, written). Students are able to benchmark their work online and teachers use the…

  5. New temporal high-pass filter nonuniformity correction based on bilateral filter

    Science.gov (United States)

    Zuo, Chao; Chen, Qian; Gu, Guohua; Qian, Weixian

    2011-03-01

    A thorough analysis of low convergence speed and ghosting artifacts in temporal high-pass filter correction has been undertaken in this paper and it has found out that the keys of these problems are the interference of a large sum of unrelated scene information in the nonuniformity correction (NUC) process. In order to overcome these drawbacks, a new scene-based NUC technique based on bilateral filter has been developed. This method separates the original input frames into two parts and it estimates the NUC parameters only by using the residuals. The experimental results have shown that it can significantly increase convergence speed and reduce ghosting artifacts.

  6. IMU-Based Online Kinematic Calibration of Robot Manipulator

    Directory of Open Access Journals (Sweden)

    Guanglong Du

    2013-01-01

    Full Text Available Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA and Kalman Filter (KF to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

  7. IMU-based online kinematic calibration of robot manipulator.

    Science.gov (United States)

    Du, Guanglong; Zhang, Ping

    2013-01-01

    Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods.

  8. Image Filtering Based on Mathematical Morphology and Visual Perception Principle

    Institute of Scientific and Technical Information of China (English)

    JINGXiaojun; YUNong; SHANGYong

    2004-01-01

    The operation of a morphological filter can be divided into two basic problems that include morphological operation and Structuring element (SE) selection. The rules for morphological operations are predefined, so the filter's properties depend merely on the selection of SE. How to design adaptively the optimal morphological filter so as to automatically and delicately complete the tasks of target detection and recognition, becomes one of the current research hotspots and subtle technical problems. Based on the filtering theory of the mathematical morphology, by introducing appropriate visual perception principle, this paper presents how to design the filtering architecture and its target detection model through the optimal parameter training. By this way it can provide good detection results and robust adaptability to image targets with clutter background. It is sure to provide a new approach to automatic target recognition with mathematical morphology theory.

  9. Distortion Parameters Analysis Method Based on Improved Filtering Algorithm

    Directory of Open Access Journals (Sweden)

    ZHANG Shutuan

    2013-10-01

    Full Text Available In order to realize the accurate distortion parameters test of aircraft power supply system, and satisfy the requirement of corresponding equipment in the aircraft, the novel power parameters test system based on improved filtering algorithm is introduced in this paper. The hardware of the test system has the characters of s portable and high-speed data acquisition and processing, and the software parts utilize the software Labwindows/CVI as exploitation software, and adopt the pre-processing technique and adding filtering algorithm. Compare with the traditional filtering algorithm, the test system adopted improved filtering algorithm can help to increase the test accuracy. The application shows that the test system with improved filtering algorithm can realize the accurate test results, and reach to the design requirements.  

  10. Gravity gradient-terrain aided navigation based on particle filter

    Science.gov (United States)

    Xiong, Ling; Ma, Jie; Tian, Jin-Wen

    2009-10-01

    Based on Particle Filter, Gravity Gradient-Terrain aided position technology is proposed in this paper. With the sensitivity of gravity gradient to terrain, the gravity gradient reference map can be computed from the local terrain elevation data. The position can be actualized through matching the real-time measured gravity gradient data to the prepared gravity gradient reference map. The most widely used approximate filtering method is the extended Kaman filter (EKF). EKF is computationally simple but, the convergence of the state estimation for the position is not guaranteed. Particle filter (PF) makes use of the non-linear state and measurement functions, no linearization technology is needed. PF can assure the convergence of the state estimation which follows from the classical results on convergence of Bayesian estimators. Simulations have been done and Particle filter has been shown to be a superior alternative to the EKF in the gravity gradient-terrain matching navigation systems.

  11. Assessing a robust ensemble-based Kalman filter for efficient ecosystem data assimilation of the Cretan Sea

    Science.gov (United States)

    Triantafyllou, G.; Hoteit, I.; Luo, X.; Tsiaras, K.; Petihakis, G.

    2013-09-01

    An application of an ensemble-based robust filter for data assimilation into an ecosystem model of the Cretan Sea is presented and discussed. The ecosystem model comprises two on-line coupled sub-models: the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM). The filtering scheme is based on the Singular Evolutive Interpolated Kalman (SEIK) filter which is implemented with a time-local H∞ filtering strategy to enhance robustness and performances during periods of strong ecosystem variability. Assimilation experiments in the Cretan Sea indicate that robustness can be achieved in the SEIK filter by introducing an adaptive inflation scheme of the modes of the filter error covariance matrix. Twin-experiments are performed to evaluate the performance of the assimilation system and to study the benefits of using robust filtering in an ensemble filtering framework. Pseudo-observations of surface chlorophyll, extracted from a model reference run, were assimilated every two days. Simulation results suggest that the adaptive inflation scheme significantly improves the behavior of the SEIK filter during periods of strong ecosystem variability.

  12. Assessing a robust ensemble-based Kalman filter for efficient ecosystem data assimilation of the Cretan Sea

    KAUST Repository

    Triantafyllou, George N.

    2013-09-01

    An application of an ensemble-based robust filter for data assimilation into an ecosystem model of the Cretan Sea is presented and discussed. The ecosystem model comprises two on-line coupled sub-models: the Princeton Ocean Model (POM) and the European Regional Seas Ecosystem Model (ERSEM). The filtering scheme is based on the Singular Evolutive Interpolated Kalman (SEIK) filter which is implemented with a time-local H∞ filtering strategy to enhance robustness and performances during periods of strong ecosystem variability. Assimilation experiments in the Cretan Sea indicate that robustness can be achieved in the SEIK filter by introducing an adaptive inflation scheme of the modes of the filter error covariance matrix. Twin-experiments are performed to evaluate the performance of the assimilation system and to study the benefits of using robust filtering in an ensemble filtering framework. Pseudo-observations of surface chlorophyll, extracted from a model reference run, were assimilated every two days. Simulation results suggest that the adaptive inflation scheme significantly improves the behavior of the SEIK filter during periods of strong ecosystem variability. © 2012 Elsevier B.V.

  13. Predicting online ratings based on the opinion spreading process

    Science.gov (United States)

    He, Xing-Sheng; Zhou, Ming-Yang; Zhuo, Zhao; Fu, Zhong-Qian; Liu, Jian-Guo

    2015-10-01

    Predicting users' online ratings is always a challenge issue and has drawn lots of attention. In this paper, we present a rating prediction method by combining the user opinion spreading process with the collaborative filtering algorithm, where user similarity is defined by measuring the amount of opinion a user transfers to another based on the primitive user-item rating matrix. The proposed method could produce a more precise rating prediction for each unrated user-item pair. In addition, we introduce a tunable parameter λ to regulate the preferential diffusion relevant to the degree of both opinion sender and receiver. The numerical results for Movielens and Netflix data sets show that this algorithm has a better accuracy than the standard user-based collaborative filtering algorithm using Cosine and Pearson correlation without increasing computational complexity. By tuning λ, our method could further boost the prediction accuracy when using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) as measurements. In the optimal cases, on Movielens and Netflix data sets, the corresponding algorithmic accuracy (MAE and RMSE) are improved 11.26% and 8.84%, 13.49% and 10.52% compared to the item average method, respectively.

  14. Improved OCV Model of a Li-Ion NMC Battery for Online SOC Estimation Using the Extended Kalman Filter

    Directory of Open Access Journals (Sweden)

    Ines Baccouche

    2017-05-01

    Full Text Available Accurate modeling of the nonlinear relationship between the open circuit voltage (OCV and the state of charge (SOC is required for adaptive SOC estimation during the lithium-ion (Li-ion battery operation. Online SOC estimation should meet several constraints, such as the computational cost, the number of parameters, as well as the accuracy of the model. In this paper, these challenges are considered by proposing an improved simplified and accurate OCV model of a nickel manganese cobalt (NMC Li-ion battery, based on an empirical analytical characterization approach. In fact, composed of double exponential and simple quadratic functions containing only five parameters, the proposed model accurately follows the experimental curve with a minor fitting error of 1 mV. The model is also valid at a wide temperature range and takes into account the voltage hysteresis of the OCV. Using this model in SOC estimation by the extended Kalman filter (EKF contributes to minimizing the execution time and to reducing the SOC estimation error to only 3% compared to other existing models where the estimation error is about 5%. Experiments are also performed to prove that the proposed OCV model incorporated in the EKF estimator exhibits good reliability and precision under various loading profiles and temperatures.

  15. Biogas Filter Based on Local Natural Zeolite Materials

    Directory of Open Access Journals (Sweden)

    Satriyo Krido Wahono

    2014-02-01

    Full Text Available UPT BPPTK LIPI has created a biogas filter tool to improve the purity of methane in the biogas. The device shaped cylindrical tube containing absorbent materials which based on local natural zeolite of Indonesia. The absorbent has been activated and modified with other materials. This absorbtion material has multi-adsorption capacity for almost impurities gas of biogas. The biogas  filter increase methane content of biogas for 5-20%. The biogas filter improve the biogas’s performance such as increasing methane contents, increasing heating value, reduction of odors, reduction of corrosion potential, increasing the efficiency and stability of the generator.

  16. Miniature Microwave Bandpass Filter Based on EBG Structures

    DEFF Research Database (Denmark)

    Zhurbenko, Vitaliy; Krozer, Viktor; Meincke, Peter

    2006-01-01

    A new design of a planar microwave filter, based on rejection band properties of an electrically small electromagnetic bandgap (EBG) structure, is proposed. The proposed EBG structure demonstrates effective impedance manipulation, exhibits a simple analysis, and is about three times smaller...... as compared to stepped-impedance hairpin (SIH) resonators with similar response. The new bandpass filter has a reduced footprint and can be fabricated in standard thick-film manufacturing technology. Measured and simulated results exhibit good agreement. The measured results show improvement in the filter...

  17. Reliable hydraulic turbine governor based on identification and adaptive filtering

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, J.; Doraiswami, R.

    1986-01-01

    A scheme for improving reliable operation of a PID governor of a hydraulic turbine generating unit is proposed. The parameters of governor and actuators are identified on-line to, a) detect their anomalous behaviours, b) facilitate the calibration of the proportional integral and derivative gain settings. An adaptive filter is used to detect the lightly damped oscillations of the system. The proposed scheme was verified via simulation on the real data obtained from one of Mactaquac hydro-generating units of New Brunswick Electrical Power Commission. The simulation results show that the proposed scheme can indeed provide an accurate and rapid detection of the abnormal system operations.

  18. Optical notch filter design based on digital signal processing

    Institute of Scientific and Technical Information of China (English)

    GUO Sen; ZHANG Juan; LI Xue

    2011-01-01

    Based on digital signal processing theory, a novel method of designing optical notch filter is proposed for Mach-Zehnder interferometer with cascaded optical fiber rings coupled structure. The method is simple and effective, and it can be used to implement the designing of the optical notch filter which has arbitrary number of notch points in one free spectrum range (FSR). A design example of notch filter based on cascaded single-fiber-rings is given. On this basis, an improved cascaded double-fiber-rings structure is presented to eliminate the effect of phase shift caused by the single-fiber-ring structure. This new structure can improve the stability and applicability of system. The change of output intensity spectrum is finally investigated for each design parameter and the tuning characteristics of the notch filter are also discussed.

  19. Spin-Filter Polarimeter: On-line Proton and Deuteron Polarimetry in Real Time

    Science.gov (United States)

    Ropera, B.; Mendez, C.; Dunham, B.; Clegg, C.

    1996-05-01

    The Spin-Filter Polarimeter system (SFP)(A.J. Mendez, et al.), submitted to Rev. of Scientific Instruments monitors the nuclear polarization of the H^± or D^± ions produced by the Atomic Beam Polarized Ion Source (ABPIS) at Triangle Universities Nuclear Laboratory (TUNL). This system is based on the "spin-filter," a rf cavity designed for use in the Lamb-shift polarized ion source developed at Los Alamos National Laboratory(J.L. McKibben, et al.), Phys. Rev. Lett. 20, 1180 (1968). The SFP determines the polarization of the H^± or D^± ions by measuring the relative hyperfine state populations of the 2S_1/2 metastable H or D atoms produced as a by-product of the negative ionization process (H^+ + 2e^-arrow H^-) in the ABPIS. SFP polarization measurements taken concurrently with calibrated nuclear polarimeters resulted in absolute rms differences of 0.023 or less. Principle of operation, description of hardware, comparison measurements, and impressions gained from the use of the SFP as a real time tuning device and absolute polarization monitor will be discussed.

  20. Nonlinear Filter Based Image Denoising Using AMF Approach

    CERN Document Server

    Thivakaran, T K

    2010-01-01

    This paper proposes a new technique based on nonlinear Adaptive Median filter (AMF) for image restoration. Image denoising is a common procedure in digital image processing aiming at the removal of noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. This procedure is traditionally performed in the spatial or frequency domain by filtering. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly e...

  1. Ground point filtering of UAV-based photogrammetric point clouds

    Science.gov (United States)

    Anders, Niels; Seijmonsbergen, Arie; Masselink, Rens; Keesstra, Saskia

    2016-04-01

    Unmanned Aerial Vehicles (UAVs) have proved invaluable for generating high-resolution and multi-temporal imagery. Based on photographic surveys, 3D surface reconstructions can be derived photogrammetrically so producing point clouds, orthophotos and surface models. For geomorphological or ecological applications it may be necessary to separate ground points from vegetation points. Existing filtering methods are designed for point clouds derived using other methods, e.g. laser scanning. The purpose of this paper is to test three filtering algorithms for the extraction of ground points from point clouds derived from low-altitude aerial photography. Three subareas were selected from a single flight which represent different scenarios: 1) low relief, sparsely vegetated area, 2) low relief, moderately vegetated area, 3) medium relief and moderately vegetated area. The three filtering methods are used to classify ground points in different ways, based on 1) RGB color values from training samples, 2) TIN densification as implemented in LAStools, and 3) an iterative surface lowering algorithm. Ground points are then interpolated into a digital terrain model using inverse distance weighting. The results suggest that different landscapes require different filtering methods for optimal ground point extraction. While iterative surface lowering and TIN densification are fully automated, color-based classification require fine-tuning in order to optimize the filtering results. Finally, we conclude that filtering photogrammetric point clouds could provide a cheap alternative to laser scan surveys for creating digital terrain models in sparsely vegetated areas.

  2. Physics-based prognostic modelling of filter clogging phenomena

    Science.gov (United States)

    Eker, Omer F.; Camci, Fatih; Jennions, Ian K.

    2016-06-01

    In industry, contaminant filtration is a common process to achieve a desired level of purification, since contaminants in liquids such as fuel may lead to performance drop and rapid wear propagation. Generally, clogging of filter phenomena is the primary failure mode leading to the replacement or cleansing of filter. Cascading failures and weak performance of the system are the unfortunate outcomes due to a clogged filter. Even though filtration and clogging phenomena and their effects of several observable parameters have been studied for quite some time in the literature, progression of clogging and its use for prognostics purposes have not been addressed yet. In this work, a physics based clogging progression model is presented. The proposed model that bases on a well-known pressure drop equation is able to model three phases of the clogging phenomena, last of which has not been modelled in the literature yet. In addition, the presented model is integrated with particle filters to predict the future clogging levels and to estimate the remaining useful life of fuel filters. The presented model has been implemented on the data collected from an experimental rig in the lab environment. In the rig, pressure drop across the filter, flow rate, and filter mesh images are recorded throughout the accelerated degradation experiments. The presented physics based model has been applied to the data obtained from the rig. The remaining useful lives of the filters used in the experimental rig have been reported in the paper. The results show that the presented methodology provides significantly accurate and precise prognostic results.

  3. CMS OnlineWeb-Based Monitoring

    CERN Document Server

    Wan, Zongru; Chakaberia, Irakli; Lopez-Perez, Juan Antonio; Maeshima, Kaori; Maruyama, Sho; Soha, Aron; Sulmanas, Balys; Wan, Zongru

    2012-01-01

    For large international High Energy Physics experiments, modern web technologies make the online monitoring of detector status, data acquisition status, trigger rates, luminosity, etc., accessible for the collaborators anywhere and anytime. This helps the collaborating experts monitor the status of the experiment, identify the problems, and improve data-taking efficiency. We present the Web-Based Monitoring project of the CMS experiment at the LHC of CERN. The data sources are relational databases and various messaging systems. The project provides a vast amount of in-depth information including real time data, historical trend, and correlations, in a user friendly way.

  4. Wavelet transform based ECG signal filtering implemented on FPGA

    Directory of Open Access Journals (Sweden)

    Germán-Salló Zoltán

    2011-12-01

    Full Text Available Filtering electrocardiographic (ECG signals is always a challenge because the accuracy of their interpretation depends strongly on filtering results. The Discrete Wavelet Transform (DWT is an efficient, new and useful tool for signal processing applications and it’s adopted in many domains as biomedical signal filtering. This transform came about from different fields, including mathematics, physics and signal processing, it has a growing applicability due to its so-called multiresolution analyzing capabilities. FPGAs are reconfigurable logic devices made up of arrays of logic cells and routing channels having some specific characteristics which allow to use them in signal processing applications. This paper presents a DWT based ECG signal denoising method implemented on FPGA, using Matlab specific Xilinx tool, as System Generator, the procedure is simulated and evaluated through filtering specific parameters.

  5. Particle filter-based prognostics: Review, discussion and perspectives

    Science.gov (United States)

    Jouin, Marine; Gouriveau, Rafael; Hissel, Daniel; Péra, Marie-Cécile; Zerhouni, Noureddine

    2016-05-01

    Particle filters are of great concern in a large variety of engineering fields such as robotics, statistics or automatics. Recently, it has developed among Prognostics and Health Management (PHM) applications for diagnostics and prognostics. According to some authors, it has ever become a state-of-the-art technique for prognostics. Nowadays, around 50 papers dealing with prognostics based on particle filters can be found in the literature. However, no comprehensive review has been proposed on the subject until now. This paper aims at analyzing the way particle filters are used in that context. The development of the tool in the prognostics' field is discussed before entering the details of its practical use and implementation. Current issues are identified, analyzed and some solutions or work trails are proposed. All this aims at highlighting future perspectives as well as helping new users to start with particle filters in the goal of prognostics.

  6. SMS Spam Filtering Technique Based on Artificial Immune System

    Directory of Open Access Journals (Sweden)

    Tarek M Mahmoud

    2012-03-01

    Full Text Available The Short Message Service (SMS have an important economic impact for end users and service providers. Spam is a serious universal problem that causes problems for almost all users. Several studies have been presented, including implementations of spam filters that prevent spam from reaching their destination. Nave Bayesian algorithm is one of the most effective approaches used in filtering techniques. The computational power of smart phones are increasing, making increasingly possible to perform spam filtering at these devices as a mobile agent application, leading to better personalization and effectiveness. The challenge of filtering SMS spam is that the short messages often consist of few words composed of abbreviations and idioms. In this paper, we propose an anti-spam technique based on Artificial Immune System (AIS for filtering SMS spam messages. The proposed technique utilizes a set of some features that can be used as inputs to spam detection model. The idea is to classify message using trained dataset that contains Phone Numbers, Spam Words, and Detectors. Our proposed technique utilizes a double collection of bulk SMS messages Spam and Ham in the training process. We state a set of stages that help us to build dataset such as tokenizer, stop word filter, and training process. Experimental results presented in this paper are based on iPhone Operating System (iOS. The results applied to the testing messages show that the proposed system can classify the SMS spam and ham with accurate compared with Nave Bayesian algorithm.

  7. Web-based Factors Affecting Online Purchasing Behaviour

    Science.gov (United States)

    Ariff, Mohd Shoki Md; Sze Yan, Ng; Zakuan, Norhayati; Zaidi Bahari, Ahamad; Jusoh, Ahmad

    2013-06-01

    The growing use of internet and online purchasing among young consumers in Malaysia provides a huge prospect in e-commerce market, specifically for B2C segment. In this market, if E-marketers know the web-based factors affecting online buyers' behaviour, and the effect of these factors on behaviour of online consumers, then they can develop their marketing strategies to convert potential customers into active one, while retaining existing online customers. Review of previous studies related to the online purchasing behaviour in B2C market has point out that the conceptualization and empirical validation of the online purchasing behaviour of Information and Communication Technology (ICT) literate users, or ICT professional, in Malaysia has not been clearly addressed. This paper focuses on (i) web-based factors which online buyers (ICT professional) keep in mind while shopping online; and (ii) the effect of web-based factors on online purchasing behaviour. Based on the extensive literature review, a conceptual framework of 24 items of five factors was constructed to determine web-based factors affecting online purchasing behaviour of ICT professional. Analysis of data was performed based on the 310 questionnaires, which were collected using a stratified random sampling method, from ICT undergraduate students in a public university in Malaysia. The Exploratory factor analysis performed showed that five factors affecting online purchase behaviour are Information Quality, Fulfilment/Reliability/Customer Service, Website Design, Quick and Details, and Privacy/Security. The result of Multiple Regression Analysis indicated that Information Quality, Quick and Details, and Privacy/Security affect positively online purchase behaviour. The results provide a usable model for measuring web-based factors affecting buyers' online purchase behaviour in B2C market, as well as for online shopping companies to focus on the factors that will increase customers' online purchase.

  8. Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

    Science.gov (United States)

    Simon, Donald L.; Garg, Sanjay

    2010-01-01

    A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

  9. PARTICLE FILTER BASED VEHICLE TRACKING APPROACH WITH IMPROVED RESAMPLING STAGE

    Directory of Open Access Journals (Sweden)

    Wei Leong Khong

    2014-02-01

    Full Text Available Optical sensors based vehicle tracking can be widely implemented in traffic surveillance and flow control. The vast development of video surveillance infrastructure in recent years has drawn the current research focus towards vehicle tracking using high-end and low cost optical sensors. However, tracking vehicles via such sensors could be challenging due to the high probability of changing vehicle appearance and illumination, besides the occlusion and overlapping incidents. Particle filter has been proven as an approach which can overcome nonlinear and non-Gaussian situations caused by cluttered background and occlusion incidents. Unfortunately, conventional particle filter approach encounters particle degeneracy especially during and after the occlusion. Particle filter with sampling important resampling (SIR is an important step to overcome the drawback of particle filter, but SIR faced the problem of sample impoverishment when heavy particles are statistically selected many times. In this work, genetic algorithm has been proposed to be implemented in the particle filter resampling stage, where the estimated position can converge faster to hit the real position of target vehicle under various occlusion incidents. The experimental results show that the improved particle filter with genetic algorithm resampling method manages to increase the tracking accuracy and meanwhile reduce the particle sample size in the resampling stage.

  10. Design of thin-film filters for resolution improvements in filter-array based spectrometers using DSP

    Science.gov (United States)

    Lee, Woong-Bi; Kim, Cheolsun; Ju, Gun Wu; Lee, Yong Tak; Lee, Heung-No

    2016-05-01

    Miniature spectrometers have been widely developed in various academic and industrial applications such as bio-medical, chemical and environmental engineering. As a family of spectrometers, optical filter-array based spectrometers fabricated using CMOS or Nano technology provide miniaturization, superior portability and cost effectiveness. In filterarray based spectrometers, the resolution which represents the ability how closely resolve two neighboring spectra, depends on the number of filters and the characteristics of the transmission functions (TFs) of the filters. In practice, due to the small-size and low-cost fabrication, the number of filters is limited and the shape of the TF of each filter is nonideal. As a development of modern digital signal processing (DSP), the spectrometers are equipped with DSP algorithms not only to alleviate distortions due to unexpected noise or interferences among filters but also reconstruct the original signal spectrum. For a high-resolution spectrum reconstruction by the DSP, the TFs of the filters need to be sufficiently uncorrelated with each other. In this paper, we present a design of optical thin-film filters which have the uncorrelated TFs. Each filter consists of multiple layers of high- and low-refractive index materials deposited on a substrate. The proposed design helps the DSP algorithm to improve resolution with a small number of filters. We demonstrate that a resolution of 5 nm within a range from 500 nm to 1100 nm can be achieved with only 64 filters.

  11. Long-term visual tracking based on correlation filters

    Science.gov (United States)

    Wei, Quanlu; Lao, Songyang; Bai, Liang

    2017-03-01

    In order to accomplish the long term visual tracking task in complex scenes, solve problems of scale variation, appearance variation and tracking failure, a long term tracking algorithm is given based on the framework of collaborative correlation tracking. Firstly, we integrate several powerful features to boost the represent ability based on the kernel correlation filter, and extend the filter by embedding a scale factor into the kernelized matrix to handle the scale variation. Then, we use the Peak-Sidelobe Ratio to decide whether the object is tracked successfully, and a CUR filter for re-detection the object in case of tracking failure is learnt with random sampling. Corresponding experiment is performed on 17 challenging benchmark video sequences. Compared with the 8 existing state-of-the-art algorithms based on discriminative learning method, the results show that the proposed algorithm improves the tracking performance on several indexes, and is robust to complex scenes for long term visual tracking.

  12. Research on SINS Alignment Algorithm Based on FIR Filters

    Institute of Scientific and Technical Information of China (English)

    LIAN Jun-xiang; HU De-wen; WU Yuan-xin; HU Xiao-ping

    2007-01-01

    An inertial frame based alignment (IFBA) method is presented, especially for the applications on a rocking platform, e.g., marine applications. Defining the initial body frame as the inertial frame, the IFBA method achieves the alignment by virtue of a cascade of low-pass FIR filters, which attenuate the disturbing acceleration and maintain the gravity vector. The aligning time rests with the orders of the FIR filter group, and the method is suitable for large initial misali gnment case. An alignment scheme comprising a coarse phase by the IFBA method an d a fine phase by a Kalman filter is presented. Both vehicle-based and ship-based alignment experiments were carried out. The results show that the proposed scheme converges much faster than the traditional method at no cost of precision and also works well under any large initial misalignment.

  13. Design of a quadratic filter for contrast - assisted ultrasonic imaging based on 2D gaussian filters

    Directory of Open Access Journals (Sweden)

    Tosaporn Nilmanee

    2010-05-01

    Full Text Available We present a novel design of quadratic filters (QFs in the frequency domain in order to improve the quality of contrastassisted ultrasound images for medical diagnosis. The QF is designed as a 2D linear-phase filter. In addition, the magnitude is based on the sum of two 2D Gaussian filters. The centers of the Gaussian filters are placed at the locations where the power strength of signals from ultrasound contrast agent over surrounding tissue is maximal. The design parameters consist of two centers and a standard deviation (SD of the Gaussian filters. The coefficients of the QF are obtained using the inverse discreteFourier transform. The QFs from the proposed design method are evaluated using in vivo ultrasound data, i.e., the kidney of aguinea pig. We find that the appropriate SD and two center points of the QF for the in vivo data are at 0.34, (3.30, 3.30 and (-3.30,-3.30 MHz, respectively. Results show that the images produced from the output signals of the new design are superior to theoriginal B-mode both in terms of contrast and spatial resolution. The quadratic image provides clear visualization of thekidney shape and large vascular structures inside the kidney. The contrast-to-tissue ratio value of quadratic image is 24.8 dBcompared to -1.5 dB from the B-mode image. In addition, we can use this new design approach as an efficient tool to furtherimprove the QF in producing better contrast-assisted ultrasound images for medical diagnostic purposes.

  14. Subpixel edge detection method based on low-frequency filtering

    Science.gov (United States)

    Bylinsky, Yosip Y.; Kotyra, Andrzej; Gromaszek, Konrad; Iskakova, Aigul

    2016-09-01

    A method of edge detection in images is proposed basing that based on low-frequency filtering. The method uses polynomial interpolation to determine the coordinates of the edge point with subpixel accuracy. Some experiments have been results also have been provided.

  15. A consistent approach for image de-noising using spatial gradient based bilateral filter and smooth filtering

    Science.gov (United States)

    Tiwari, Mayank; Gupta, Bhupendra

    2016-07-01

    We propose an image noise removal method based on spatial gradient based bilateral filter and smooth filtering. Our method consist two step process; in first step, for a given noisy image we extract all of its patches and apply our newly developed spatial gradient based bilateral filter on each patch and get an reference image; in second step we perform smooth filtering on each pixel of the reference image. Experimental results show that our method is consistent and comparable or better than state-of-the-art.

  16. Research of Collaborative Filtering Recommendation Algorithm based on Network Structure

    Directory of Open Access Journals (Sweden)

    Hui PENG

    2013-10-01

    Full Text Available This paper combines the classic collaborative filtering algorithm with personalized recommendation algorithm based on network structure. For the data sparsity and malicious behavior problems of traditional collaborative filtering algorithm, the paper introduces a new kind of social network-based collaborative filtering algorithm. In order to improve the accuracy of the personalized recommendation technology, we first define empty state in the state space of multi-dimensional semi-Markov processes and obtain extended multi-dimensional semi-Markov processes which are combined with social network analysis theory, and then we get social network information flow model. The model describes the flow of information between the members of the social network. So, we propose collaborative filtering algorithm based on social network information flow model. The algorithm uses social network information and combines user trust with user interest and find nearest neighbors of the target user and then forms a project recommended to improve the accuracy of recommended. Compared with the traditional collaborative filtering algorithm, the algorithm can effectively alleviate the sparsity and malicious behavior problem, and significantly improve the quality of the recommendation system recommended.

  17. Fiber based polarization filter for radially and azimuthally polarized light.

    Science.gov (United States)

    Jocher, Christoph; Jauregui, Cesar; Voigtländer, Christian; Stutzki, Fabian; Nolte, Stefan; Limpert, Jens; Tünnermann, Andreas

    2011-09-26

    We demonstrate a new fiber based concept to filter azimuthally or radially polarized light. This concept is based on the lifting of the modal degeneracy that takes place in high numerical aperture fibers. In such fibers, the radially and azimuthally polarized modes can be spectrally separated using a fiber Bragg grating. As a proof of principle, we filter azimuthally polarized light in a commercially available fiber in which a fiber Bragg grating has been written by a femtosecond pulsed laser. © 2011 Optical Society of America

  18. Fabrication of optical filters based on polymer asymmetric Bragg couplers.

    Science.gov (United States)

    Chuang, Wei-Ching; Lee, An-Chen; Chao, Ching-Kong; Ho, Chi-Ting

    2009-09-28

    In this work, we successfully developed a process to fabricate dual-channel polymeric waveguide filters based on an asymmetric Bragg coupler (ABC) using holographic interference techniques, soft lithography, and micro molding. At the cross- and self-reflection Bragg wavelengths, the transmission dips of approximately -16.4 and -11.5 dB relative to the 3 dB background insertion loss and the 3 dB transmission bandwidths of approximately 0.6 and 0.5 nm were obtained from an ABC-based filter. The transmission spectrum overlaps when the effective index difference between two single waveguides is less than 0.002.

  19. Virus removal in ceramic depth filters based on diatomaceous earth.

    Science.gov (United States)

    Michen, Benjamin; Meder, Fabian; Rust, Annette; Fritsch, Johannes; Aneziris, Christos; Graule, Thomas

    2012-01-17

    Ceramic filter candles, based on the natural material diatomaceous earth, are widely used to purify water at the point-of-use. Although such depth filters are known to improve drinking water quality by removing human pathogenic protozoa and bacteria, their removal regarding viruses has rarely been investigated. These filters have relatively large pore diameters compared to the physical dimension of viruses. However, viruses may be retained by adsorption mechanisms due to intermolecular and surface forces. Here, we use three types of bacteriophages to investigate their removal during filtration and batch experiments conducted at different pH values and ionic strengths. Theoretical models based on DLVO-theory are applied in order to verify experimental results and assess surface forces involved in the adsorptive process. This was done by calculation of interaction energies between the filter surface and the viruses. For two small spherically shaped viruses (MS2 and PhiX174), these filters showed no significant removal. In the case of phage PhiX174, where attractive interactions were expected, due to electrostatic attraction of oppositely charged surfaces, only little adsorption was reported in the presence of divalent ions. Thus, we postulate the existence of an additional repulsive force between PhiX174 and the filter surface. It is hypothesized that such an additional energy barrier originates from either the phage's specific knobs that protrude from the viral capsid, enabling steric interactions, or hydration forces between the two hydrophilic interfaces of virus and filter. However, a larger-sized, tailed bacteriophage of the family Siphoviridae was removed by log 2 to 3, which is explained by postulating hydrophobic interactions.

  20. fNIRS-based online deception decoding

    Science.gov (United States)

    Hu, Xiao-Su; Hong, Keum-Shik; Ge, Shuzhi Sam

    2012-04-01

    Deception involves complex neural processes in the brain. Different techniques have been used to study and understand brain mechanisms during deception. Moreover, efforts have been made to develop schemes that can detect and differentiate deception and truth-telling. In this paper, a functional near-infrared spectroscopy (fNIRS)-based online brain deception decoding framework is developed. Deploying dual-wavelength fNIRS, we interrogate 16 locations in the forehead when eight able-bodied adults perform deception and truth-telling scenarios separately. By combining preprocessed oxy-hemoglobin and deoxy-hemoglobin signals, we develop subject-specific classifiers using the support vector machine. Deception and truth-telling states are classified correctly in seven out of eight subjects. A control experiment is also conducted to verify the deception-related hemodynamic response. The average classification accuracy is over 83.44% from these seven subjects. The obtained result suggests that the applicability of fNIRS as a brain imaging technique for online deception detection is very promising.

  1. Recursive three-dimensional model reconstruction based on Kalman filtering.

    Science.gov (United States)

    Yu, Ying Kin; Wong, Kin Hong; Chang, Michael Ming Yuen

    2005-06-01

    A recursive two-step method to recover structure and motion from image sequences based on Kalman filtering is described in this paper. The algorithm consists of two major steps. The first step is an extended Kalman filter (EKF) for the estimation of the object's pose. The second step is a set of EKFs, one for each model point, for the refinement of the positions of the model features in the three-dimensional (3-D) space. These two steps alternate from frame to frame. The initial model converges to the final structure as the image sequence is scanned sequentially. The performance of the algorithm is demonstrated with both synthetic data and real-world objects. Analytical and empirical comparisons are made among our approach, the interleaved bundle adjustment method, and the Kalman filtering-based recursive algorithm by Azarbayejani and Pentland. Our approach outperformed the other two algorithms in terms of computation speed without loss in the quality of model reconstruction.

  2. Kalman Filter Based Tracking in an Video Surveillance System

    Directory of Open Access Journals (Sweden)

    SULIMAN, C.

    2010-05-01

    Full Text Available In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtained from the Kalman filter, and we show the correct functionality of the Kalman filter based tracking. The tests were performed using video data taken with the help of a fix camera. The tested algorithm has shown promising results.

  3. Video Based Moving Object Tracking by Particle Filter

    Directory of Open Access Journals (Sweden)

    Md. Zahidul Islam

    2009-03-01

    Full Text Available Usually, the video based object tracking deal with non-stationary image stream that changes over time. Robust and Real time moving object tracking is a problematic issue in computer vision research area. Most of the existing algorithms are able to track only inpredefined and well controlled environment. Some cases, they don’t consider non-linearity problem. In our paper, we develop such a system which considers color information, distance transform (DT based shape information and also nonlinearity. Particle filtering has been proven very successful for non-gaussian and non-linear estimation problems. We examine the difficulties of video based tracking and step by step we analyze these issues. In our firstapproach, we develop the color based particle filter tracker that relies on the deterministic search of window, whose color content matches a reference histogram model. A simple HSV histogram-based color model is used to develop this observation system. Secondly, wedescribe a new approach for moving object tracking with particle filter by shape information. The shape similarity between a template and estimated regions in the video scene is measured by their normalized cross-correlation of distance transformed images. Our observation system of particle filter is based on shape from distance transformed edge features. Template is created instantly by selecting any object from the video scene by a rectangle. Finally, inthis paper we illustrate how our system is improved by using both these two cues with non linearity.

  4. 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.

  5. Online digital filter and QRS detector applicable in low resource ECG monitoring systems.

    Science.gov (United States)

    Tabakov, Serafim; Iliev, Ivo; Krasteva, Vessela

    2008-11-01

    The present work describes fast computation methods for real-time digital filtration and QRS detection, both applicable in autonomous personal ECG systems for long-term monitoring. Since such devices work under considerable artifacts of intensive body and electrode movements, the input filtering should provide high-quality ECG signals supporting the accurate ECG interpretation. In this respect, we propose a combined high-pass and power-line interference rejection filter, introducing the simple principle of averaging of samples with a predefined distance between them. In our implementation (sampling frequency of 250 Hz), we applied averaging over 17 samples distanced by 10 samples (Filter10x17), thus realizing a comb filter with a zero at 50 Hz and high-pass cut-off at 1.1 Hz. Filter10x17 affords very fast filtering procedure at the price of minimal computing resources. Another benefit concerns the small ECG distortions introduced by the filter, providing its powerful application in the preprocessing module of diagnostic systems analyzing the ECG morphology. Filter10x17 does not attenuate the QRS amplitude, or introduce significant ST-segment elevation/depression. The filter output produces a constant error, leading to uniform shifting of the entire P-QRS-T segment toward about 5% of the R-peak amplitude. Tests with standardized ECG signals proved that Filter10x17 is capable to remove very strong baseline wanderings, and to fully suppress 50 Hz interferences. By changing the number of the averaged samples and the distance between them, a filter design with different cut-off and zero frequency could be easily achieved. The real-time QRS detector is designed with simplified computations over single channel, low-resolution ECGs. It relies on simple evaluations of amplitudes and slopes, including history of their mean values estimated over the preceding beats, smart adjustable thresholds, as well as linear logical rules for identification of the R-peaks in real

  6. A new iterative speech enhancement scheme based on Kalman filtering

    DEFF Research Database (Denmark)

    Li, Chunjian; Andersen, Søren Vang

    2005-01-01

    Subtraction filter is introduced as an initialization procedure. Iterations are then made sequential inter-frame, exploiting the fact that the AR model changes slowly between neighboring frames. The proposed algorithm is computationally more efficient than a baseline EM algorithm due to its fast convergence...... for a high temporal resolution estimation of this variance. A Local Variance Estimator based on a Prediction Error Kalman Filter is designed for this high temporal resolution variance estimation. To achieve fast convergence and avoid local maxima of the likelihood function, a Weighted Power Spectral...

  7. Comparison of texture features based on Gabor filters

    NARCIS (Netherlands)

    Grigorescu, Simona E.; Petkov, Nicolai; Kruizinga, Peter

    2002-01-01

    Texture features that are based on the local power spectrum obtained by a bank of Gabor filters are compared. The features differ in the type of nonlinear post-processing which is applied to the local power spectrum. The following features are considered: Gabor energy, complex moments, and grating c

  8. Gaussian particle filter based pose and motion estimation

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Determination of relative three-dimensional (3D) position, orientation, and relative motion between two reference frames is an important problem in robotic guidance, manipulation, and assembly as well as in other fields such as photogrammetry.A solution to pose and motion estimation problem that uses two-dimensional (2D) intensity images from a single camera is desirable for real-time applications. The difficulty in performing this measurement is that the process of projecting 3D object features to 2D images is a nonlinear transformation. In this paper, the 3D transformation is modeled as a nonlinear stochastic system with the state estimation providing six degrees-of-freedom motion and position values, using line features in image plane as measuring inputs and dual quaternion to represent both rotation and translation in a unified notation. A filtering method called the Gaussian particle filter (GPF) based on the particle filtering concept is presented for 3D pose and motion estimation of a moving target from monocular image sequences. The method has been implemented with simulated data, and simulation results are provided along with comparisons to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF) to show the relative advantages of the GPF. Simulation results showed that GPF is a superior alternative to EKF and UKF.

  9. Critical Path Reduction of Distributed Arithmetic Based FIR Filter

    Directory of Open Access Journals (Sweden)

    Sunita Badave

    2016-03-01

    Full Text Available Operating speed, which is reciprocal of critical path computation time, is one of the prominent design matrices of finite impulse response (FIR filters. It is largely affected by both, system architecture as well as technique used to design arithmetic modules. A large computation time of multipliers in conventionally designed multipliers, limits the speed of system architecture. Distributed arithmetic is one of the techniques, used to provide multiplier-free multiplication in the implementation of FIR filter. However suffers from a sever limitation of exponential growth of look up table (LUT with order of filter. An improved distributed arithmetic technique is addressed here to design for system architecture of FIR filter. In proposed technique, a single large LUT of conventional DA is replaced by number of smaller indexed LUT pages to restrict exponential growth and to reduce system access time. It also eliminates the use of adders. Selection module selects the desired value from desired page, which leads to reduce computational time of critical path. Trade off between access times of LUT pages and selection module helps to achieve minimum critical path so as to maximize the operating speed. Implementations are targeted to Xilinx ISE, Virtex IV devices. FIR filter with 8 bit data width of input sample results are presented here. It is observed that, proposed design perform significantly faster as compared to the conventional DA and existing DA based designs.

  10. MEMS Based SINS/OD Filter for Land Vehicles’ Applications

    Directory of Open Access Journals (Sweden)

    Huisheng Liu

    2017-01-01

    Full Text Available A constrained low-cost SINS/OD filter aided with magnetometer is proposed in this paper. The filter is designed to provide a land vehicle navigation solution by fusing the measurements of the microelectromechanical systems based inertial measurement unit (MEMS IMU, the magnetometer (MAG, and the velocity measurement from odometer (OD. First, accelerometer and magnetometer integrated algorithm is studied to stabilize the attitude angle. Next, a SINS/OD/MAG integrated navigation system is designed and simulated, using an adaptive Kalman filter (AKF. It is shown that the accuracy of the integrated navigation system will be implemented to some extent. The field-test shows that the azimuth misalignment angle will diminish to less than 1°. Finally, an outliers detection algorithm is studied to estimate the velocity measurement bias of the odometer. The experimental results show the enhancement in restraining observation outliers that improves the precision of the integrated navigation system.

  11. Piecewise Filter of Infrared Image Based on Moment Theory

    Institute of Scientific and Technical Information of China (English)

    GAO Yang; LI Yan-jun; ZHANG Ke

    2007-01-01

    The disadvantages of IR images mostly include high noise, blurry edge and so on. The characteristics make the existent smoothing methods ineffective in preserving edge. To solve this problem, a piecewise moment filter (PMF) is put forward. By using moment and piecewise linear theory, the filter can preserve edge. Based on the statistical model of random noise, a related-coefficient method is presented to estimate the variance of noise. The edge region and model are then detected by the estimated variance. The expectation of first-order derivatives is used in getting the reliable offset of edge.At last, a fast moment filter of double-stair edge model is used to gain the piecewise smoothing results and reduce the calculation. The experimental result shows that the new method has a better capability than other methods in suppressing noise and preserving edge.

  12. A digital filtering scheme for SQUID based magnetocardiography

    Institute of Scientific and Technical Information of China (English)

    Zhu Xue-Min; Ren Yu-Feng; Yu Hong-Wei; Zhao Shi-Ping; Chen Geng-Hua; Zhang Li-Hua; Yang Qian-Sheng

    2006-01-01

    Considering the properties of slow change and quasi-periodicity of magnetocardiography (MCG) signal, we use an integrated technique of adaptive and low-pass filtering in dealing with two-channel MCG data measured by high Tc SQUIDs, The adaptive filter in the time domain is based on a noise feedback normalized least-mean-square (NLMS) algorithm, and the low-pass filter with a cutoff at 100Hz in the frequency domain characterized by Gaussian functions is combined with a notch at the power line frequency. In this way, both relevant and irrelevant noises in original MCG data are largely eliminated. The method may also be useful for other slowly varying quasi-periodical signals.

  13. Fast spectral color image segmentation based on filtering and clustering

    Science.gov (United States)

    Xing, Min; Li, Hongyu; Jia, Jinyuan; Parkkinen, Jussi

    2009-10-01

    This paper proposes a fast approach to spectral image segmentation. In the algorithm, two popular techniques are extended and applied to spectral color images: the mean-shift filtering and the kernel-based clustering. We claim that segmentation should be completed under illuminant F11 rather than directly using the original spectral reflectance, because such illumination can reduce data variability and expedite the following filtering. The modes obtained in the mean-shift filtering represent the local features of spectral images, and will be applied to segmentation in place of pixels. Since the modes are generally small in number, the eigendecomposition of kernel matrices, the crucial step in the kernelbased clustering, becomes much easier. The combination of these two techniques can efficiently enhance the performance of segmentation. Experiments show that the proposed segmentation method is feasible and very promising for spectral color images.

  14. Research on Kalman-filter based multisensor data fusion

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Multisensor data fusion has played a significant role in diverse areas ranging from local robot guidance to global military theatre defense etc.Various multisensor data fusion methods have been extensively investigated by researchers,of which Klaman filtering is one of the most important.Kalman filtering is the best-known recursive least mean-square algorithm to optimally estimate the unknown.states of a dynamic system,which has found widespread application in many areas.The scope of the work is restricted to investigate the various data fusion and track fusion techniques based on the Kalman Filter methods.then a new method of state fusion is proposed.Finally the simulation results demonstrate the effectiveness of the introduced method.

  15. Research on the filtering characteristic of single phase series hybrid active power filter based on fundamental magnetic flux compensation

    Science.gov (United States)

    Tian, Jun; Chen, Qiaofu; Zhang, Yuqi

    2012-12-01

    In this article, the PWM inverter works as a controlled fundamental current source in the single phase series hybrid active power filter (APF) based on fundamental magnetic flux compensation (FMFC). The series transformer can exhibit the self-impedance of primary winding to harmonic current, which forces harmonic current to flow into passive power filter. With the influence of harmonic current, the voltage of primary winding of transformer is a harmonic voltage, which makes the inverter output currents have a certain harmonic component, and it degrades the filtering characteristics. On the basis of PWM inverter, the mathematical model of series hybrid APF is established, and the filtering characteristics of single phase APF are analysed in detail. Three methods are gained to improve filtering characteristics: reasonably designing the inverter output filter inductance, increasing series transformer ratio and adopting voltage feed-forward control. Experimental results show that the proposed APF has greater validity.

  16. Real-time modeling and online filtering of the stochastic error in a fiber optic current transducer

    Science.gov (United States)

    Wang, Lihui; Wei, Guangjin; Zhu, Yunan; Liu, Jian; Tian, Zhengqi

    2016-10-01

    The stochastic error characteristics of a fiber optic current transducer (FOCT) influence the relay protection, electric-energy metering, and other devices in the spacer layer. Real-time modeling and online filtering of the FOCT’s stochastic error tends to be an effective method for improving the measurement accuracy of the FOCT. This paper first pretreats and inspects the FOCT data, statistically. Then, the model order is set by the AIC principle to establish an ARMA (2,1) model and model’s applicability is tested. Finally, a Kalman filter is adopted to reduce the noise in the FOCT data. The results of the experiment and the simulation demonstrate that there is a notable decrease in the stochastic error after time series modeling and Kalman filtering. Besides, the mean-variance is decreased by two orders. All the stochastic error coefficients are decreased by the total variance method; the BI is decreased by 41.4%, the RRW is decreased by 67.5%, and the RR is decreased by 53.4%. Consequently, the method can reduce the stochastic error and improve the measurement accuracy of the FOCT, effectively.

  17. Fractal Dimension Invariant Filtering and Its CNN-based Implementation

    OpenAIRE

    Xu, Hongteng; Yan, Junchi; Persson, Nils; Lin, Weiyao; Zha, Hongyuan

    2016-01-01

    Fractal analysis has been widely used in computer vision, especially in texture image processing and texture analysis. The key concept of fractal-based image model is the fractal dimension, which is invariant to bi-Lipschitz transformation of image, and thus capable of representing intrinsic structural information of image robustly. However, the invariance of fractal dimension generally does not hold after filtering, which limits the application of fractal-based image model. In this paper, we...

  18. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    Science.gov (United States)

    Kim, Deok-Hwan

    As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

  19. Filter for speckle noise reduction based on compressive sensing

    Science.gov (United States)

    Leportier, Thibault; Park, Min-Chul

    2016-12-01

    In holographic reconstruction, speckle noise is a serious factor that may degrade the image quality greatly. Several methods have been proposed, so far, to filter speckle from hologram reconstruction. The first approach is based on averaging several speckle patterns. The second solution is to apply a filter on the reconstructed image. In the first case, several holograms should be acquired, while compromise between speckle reduction and edge preservation is usually a challenge in the case of digital filtering. We propose a method to filter speckle noise based on compressive sensing (CS). CS is a method that has been demonstrated recently to reconstruct images with a sampling inferior to the Nyquist rate. By applying several times the CS algorithm on the hologram reconstruction with different initial downsampling, several versions of the same images can be reconstructed with slightly different speckle patterns. Then, speckle noise can be greatly decreased while preserving sharpness of the image. We demonstrate the effectiveness of our proposed method with simulations as well as with holograms acquired by phase-shifting method.

  20. Scattering-angle based filtering of the waveform inversion gradients

    KAUST Repository

    Alkhalifah, Tariq Ali

    2014-11-22

    Full waveform inversion (FWI) requires a hierarchical approach to maneuver the complex non-linearity associated with the problem of velocity update. In anisotropic media, the non-linearity becomes far more complex with the potential trade-off between the multiparameter description of the model. A gradient filter helps us in accessing the parts of the gradient that are suitable to combat the potential non-linearity and parameter trade-off. The filter is based on representing the gradient in the time-lag normalized domain, in which the low scattering angle of the gradient update is initially muted out in the FWI implementation, in what we may refer to as a scattering angle continuation process. The result is a low wavelength update dominated by the transmission part of the update gradient. In this case, even 10 Hz data can produce vertically near-zero wavenumber updates suitable for a background correction of the model. Relaxing the filtering at a later stage in the FWI implementation allows for smaller scattering angles to contribute higher-resolution information to the model. The benefits of the extended domain based filtering of the gradient is not only it\\'s ability in providing low wavenumber gradients guided by the scattering angle, but also in its potential to provide gradients free of unphysical energy that may correspond to unrealistic scattering angles.

  1. A Geometric Particle Filter for Template-Based Visual Tracking.

    Science.gov (United States)

    Junghyun Kwon; Hee Seok Lee; Park, Frank C; Kyoung Mu Lee

    2014-04-01

    Existing approaches to template-based visual tracking, in which the objective is to continuously estimate the spatial transformation parameters of an object template over video frames, have primarily been based on deterministic optimization, which as is well-known can result in convergence to local optima. To overcome this limitation of the deterministic optimization approach, in this paper we present a novel particle filtering approach to template-based visual tracking. We formulate the problem as a particle filtering problem on matrix Lie groups, specifically the three-dimensional Special Linear group SL(3) and the two-dimensional affine group Aff(2). Computational performance and robustness are enhanced through a number of features: (i) Gaussian importance functions on the groups are iteratively constructed via local linearization; (ii) the inverse formulation of the Jacobian calculation is used; (iii) template resizing is performed; and (iv) parent-child particles are developed and used. Extensive experimental results using challenging video sequences demonstrate the enhanced performance and robustness of our particle filtering-based approach to template-based visual tracking. We also show that our approach outperforms several state-of-the-art template-based visual tracking methods via experiments using the publicly available benchmark data set.

  2. a Min-Cut Based Filter for Airborne LIDAR Data

    Science.gov (United States)

    Ural, Serkan; Shan, Jie

    2016-06-01

    LiDAR (Light Detection and Ranging) is a routinely employed technology as a 3-D data collection technique for topographic mapping. Conventional workflows for analyzing LiDAR data require the ground to be determined prior to extracting other features of interest. Filtering the terrain points is one of the fundamental processes to acquire higher-level information from unstructured LiDAR point data. There are many ground-filtering algorithms in literature, spanning several broad categories regarding their strategies. Most of the earlier algorithms examine only the local characteristics of the points or grids, such as the slope, and elevation discontinuities. Since considering only the local properties restricts the filtering performance due to the complexity of the terrain and the features, some recent methods utilize global properties of the terrain as well. This paper presents a new ground filtering method, Min-cut Based Filtering (MBF), which takes both local and global properties of the points into account. MBF considers ground filtering as a labeling task. First, an energy function is designed on a graph, where LiDAR points are considered as the nodes on the graph that are connected to each other as well as to two auxiliary nodes representing ground and off-ground labels. The graph is constructed such that the data costs are assigned to the edges connecting the points to the auxiliary nodes, and the smoothness costs to the edges between points. Data and smoothness terms of the energy function are formulated using point elevations and approximate ground information. The data term conducts the likelihood of the points being ground or off-ground while the smoothness term enforces spatial coherence between neighboring points. The energy function is optimized by finding the minimum-cut on the graph via the alpha-expansion algorithm. The resulting graph-cut provides the labeling of the point cloud as ground and off-ground points. Evaluation of the proposed method on

  3. New control algorithm for shunt active filters, based on self-tuned vector filter

    OpenAIRE

    Perales Esteve, Manuel Ángel; Mora Jiménez, José Luis; Carrasco Solís, Juan Manuel; García Franquelo, Leopoldo

    2001-01-01

    A new, improved, method for calculating the reference of a shunt active filter is presented. This method lays on a filter, which is able to extract the main component of a vector signal. This filter acts as a Phase-Locked Loop, capturing a particular frequency. The output of this filter is in phase with the frequency isolated, and has its amplitude. Simulation and experimental results confirms the validity of the proposed algorithm.

  4. Efficient Kernel-Based Ensemble Gaussian Mixture Filtering

    KAUST Repository

    Liu, Bo

    2015-11-11

    We consider the Bayesian filtering problem for data assimilation following the kernel-based ensemble Gaussian-mixture filtering (EnGMF) approach introduced by Anderson and Anderson (1999). In this approach, the posterior distribution of the system state is propagated with the model using the ensemble Monte Carlo method, providing a forecast ensemble that is then used to construct a prior Gaussian-mixture (GM) based on the kernel density estimator. This results in two update steps: a Kalman filter (KF)-like update of the ensemble members and a particle filter (PF)-like update of the weights, followed by a resampling step to start a new forecast cycle. After formulating EnGMF for any observational operator, we analyze the influence of the bandwidth parameter of the kernel function on the covariance of the posterior distribution. We then focus on two aspects: i) the efficient implementation of EnGMF with (relatively) small ensembles, where we propose a new deterministic resampling strategy preserving the first two moments of the posterior GM to limit the sampling error; and ii) the analysis of the effect of the bandwidth parameter on contributions of KF and PF updates and on the weights variance. Numerical results using the Lorenz-96 model are presented to assess the behavior of EnGMF with deterministic resampling, study its sensitivity to different parameters and settings, and evaluate its performance against ensemble KFs. The proposed EnGMF approach with deterministic resampling suggests improved estimates in all tested scenarios, and is shown to require less localization and to be less sensitive to the choice of filtering parameters.

  5. Localization using omnivision-based manifold particle filters

    Science.gov (United States)

    Wong, Adelia; Yousefhussien, Mohammed; Ptucha, Raymond

    2015-01-01

    Developing precise and low-cost spatial localization algorithms is an essential component for autonomous navigation systems. Data collection must be of sufficient detail to distinguish unique locations, yet coarse enough to enable real-time processing. Active proximity sensors such as sonar and rangefinders have been used for interior localization, but sonar sensors are generally coarse and rangefinders are generally expensive. Passive sensors such as video cameras are low cost and feature-rich, but suffer from high dimensions and excessive bandwidth. This paper presents a novel approach to indoor localization using a low cost video camera and spherical mirror. Omnidirectional captured images undergo normalization and unwarping to a canonical representation more suitable for processing. Training images along with indoor maps are fed into a semi-supervised linear extension of graph embedding manifold learning algorithm to learn a low dimensional surface which represents the interior of a building. The manifold surface descriptor is used as a semantic signature for particle filter localization. Test frames are conditioned, mapped to a low dimensional surface, and then localized via an adaptive particle filter algorithm. These particles are temporally filtered for the final localization estimate. The proposed method, termed omnivision-based manifold particle filters, reduces convergence lag and increases overall efficiency.

  6. Acoustic cardiac signals analysis: a Kalman filter-based approach.

    Science.gov (United States)

    Salleh, Sheik Hussain; Hussain, Hadrina Sheik; Swee, Tan Tian; Ting, Chee-Ming; Noor, Alias Mohd; Pipatsart, Surasak; Ali, Jalil; Yupapin, Preecha P

    2012-01-01

    Auscultation of the heart is accompanied by both electrical activity and sound. Heart auscultation provides clues to diagnose many cardiac abnormalities. Unfortunately, detection of relevant symptoms and diagnosis based on heart sound through a stethoscope is difficult. The reason GPs find this difficult is that the heart sounds are of short duration and separated from one another by less than 30 ms. In addition, the cost of false positives constitutes wasted time and emotional anxiety for both patient and GP. Many heart diseases cause changes in heart sound, waveform, and additional murmurs before other signs and symptoms appear. Heart-sound auscultation is the primary test conducted by GPs. These sounds are generated primarily by turbulent flow of blood in the heart. Analysis of heart sounds requires a quiet environment with minimum ambient noise. In order to address such issues, the technique of denoising and estimating the biomedical heart signal is proposed in this investigation. Normally, the performance of the filter naturally depends on prior information related to the statistical properties of the signal and the background noise. This paper proposes Kalman filtering for denoising statistical heart sound. The cycles of heart sounds are certain to follow first-order Gauss-Markov process. These cycles are observed with additional noise for the given measurement. The model is formulated into state-space form to enable use of a Kalman filter to estimate the clean cycles of heart sounds. The estimates obtained by Kalman filtering are optimal in mean squared sense.

  7. Ontology-based topic clustering for online discussion data

    Science.gov (United States)

    Wang, Yongheng; Cao, Kening; Zhang, Xiaoming

    2013-03-01

    With the rapid development of online communities, mining and extracting quality knowledge from online discussions becomes very important for the industrial and marketing sector, as well as for e-commerce applications and government. Most of the existing techniques model a discussion as a social network of users represented by a user-based graph without considering the content of the discussion. In this paper we propose a new multilayered mode to analysis online discussions. The user-based and message-based representation is combined in this model. A novel frequent concept sets based clustering method is used to cluster the original online discussion network into topic space. Domain ontology is used to improve the clustering accuracy. Parallel methods are also used to make the algorithms scalable to very large data sets. Our experimental study shows that the model and algorithms are effective when analyzing large scale online discussion data.

  8. Collaborative Filtering Fusing Label Features Based on SDAE

    DEFF Research Database (Denmark)

    Huo, Huan; Liu, Xiufeng; Zheng, Deyuan

    2017-01-01

    problem, auxiliary information such as labels are utilized. Another approach of recommendation system is content-based model which can’t be directly integrated with CF-based model due to its inherent characteristics. Considering that deep learning algorithms are capable of extracting deep latent features......, this paper applies Stack Denoising Auto Encoder (SDAE) to content-based model and proposes LCF(Deep Learning for Collaborative Filtering) algorithm by combing CF-based model which fuses label features. Experiments on real-world data sets show that DLCF can largely overcome the sparsity problem...

  9. Relevance Feedback Algorithm Based on Collaborative Filtering in Image Retrieval

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2010-12-01

    Full Text Available Content-based image retrieval is a very dynamic study field, and in this field, how to improve retrieval speed and retrieval accuracy is a hot issue. The retrieval performance can be improved when applying relevance feedback to image retrieval and introducing the participation of people to the retrieval process. However, as for many existing image retrieval methods, there are disadvantages of relevance feedback with information not being fully saved and used, and their accuracy and flexibility are relatively poor. Based on this, the collaborative filtering technology was combined with relevance feedback in this study, and an improved relevance feedback algorithm based on collaborative filtering was proposed. In the method, the collaborative filtering technology was used not only to predict the semantic relevance between images in database and the retrieval samples, but to analyze feedback log files in image retrieval, which can make the historical data of relevance feedback be fully used by image retrieval system, and further to improve the efficiency of feedback. The improved algorithm presented has been tested on the content-based image retrieval database, and the performance of the algorithm has been analyzed and compared with the existing algorithms. The experimental results showed that, compared with the traditional feedback algorithms, this method can obviously improve the efficiency of relevance feedback, and effectively promote the recall and precision of image retrieval.

  10. Multiway Filtering Based on Fourth-Order Cumulants

    Directory of Open Access Journals (Sweden)

    Salah Bourennane

    2005-05-01

    Full Text Available We propose a new multiway filtering based on fourth-order cumulants for the denoising of noisy data tensor with correlated Gaussian noise. The classical multiway filtering is based on the TUCKALS3 algorithm that computes a lower-rank tensor approximation. The presented method relies on the statistics of the analyzed multicomponent signal. We first recall how the well-known lower rank-(K1,…,KN tensor approximation processed by TUCKALS3 alternating least square algorithm exploits second-order statistics. Then, we propose to introduce the fourth-order statistics in the TUCKALS3-based method. Indeed, the use of fourth-order cumulants enables to remove the Gaussian components of an additive noise. In the presented method the estimation of the n-mode projector on the n-mode signal subspace are built from the eigenvectors associated with the largest eigenvalues of a fourth-order cumulant slice matrix instead of a covariance matrix. Each projector is applied by means of the n-mode product operator on the n-mode of the data tensor. The qualitative results of the improved multiway TUCKALS3-based filterings are shown for the case of noise reduction in a color image and multicomponent seismic data.

  11. Scattering angle base filtering of the inversion gradients

    KAUST Repository

    Alkhalifah, Tariq Ali

    2014-01-01

    Full waveform inversion (FWI) requires a hierarchical approach based on the availability of low frequencies to maneuver the complex nonlinearity associated with the problem of velocity inversion. I develop a model gradient filter to help us access the parts of the gradient more suitable to combat this potential nonlinearity. The filter is based on representing the gradient in the time-lag normalized domain, in which low scattering angles of the gradient update are initially muted. The result are long-wavelength updates controlled by the ray component of the wavefield. In this case, even 10 Hz data can produce near zero wavelength updates suitable for a background correction of the model. Allowing smaller scattering angle to contribute provides higher resolution information to the model.

  12. Local fingerprint image reconstruction based on gabor filtering

    Science.gov (United States)

    Bakhtiari, Somayeh; Agaian, Sos S.; Jamshidi, Mo

    2012-06-01

    In this paper, we propose two solutions for fingerprint local image reconstruction based on Gabor filtering. Gabor filtering is a popular method for fingerprint image enhancement. However, the reliability of the information in the output image suffers, when the input image has a poor quality. This is the result of the spurious estimates of frequency and orientation by classical approaches, particularly in the scratch regions. In both techniques of this paper, the scratch marks are recognized initially using reliability image which is calculated using the gradient images. The first algorithm is based on an inpainting technique and the second method employs two different kernels for the scratch and the non-scratch parts of the image to calculate the gradient images. The simulation results show that both approaches allow the actual information of the image to be preserved while connecting discontinuities correctly by approximating the orientation matrix more genuinely.

  13. Artificial Fish Swarm Algorithm-Based Particle Filter for Li-Ion Battery Life Prediction

    Directory of Open Access Journals (Sweden)

    Ye Tian

    2014-01-01

    Full Text Available An intelligent online prognostic approach is proposed for predicting the remaining useful life (RUL of lithium-ion (Li-ion batteries based on artificial fish swarm algorithm (AFSA and particle filter (PF, which is an integrated approach combining model-based method with data-driven method. The parameters, used in the empirical model which is based on the capacity fade trends of Li-ion batteries, are identified dependent on the tracking ability of PF. AFSA-PF aims to improve the performance of the basic PF. By driving the prior particles to the domain with high likelihood, AFSA-PF allows global optimization, prevents particle degeneracy, thereby improving particle distribution and increasing prediction accuracy and algorithm convergence. Data provided by NASA are used to verify this approach and compare it with basic PF and regularized PF. AFSA-PF is shown to be more accurate and precise.

  14. Improvements of Analog Neural Networks Based on Kalman Filter

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2002-04-01

    Full Text Available In the paper, original improvements of recurrent analog neuralnetworks, which are based on Kalman filter, are presented. Theseimprovements eliminate some disadvantages of the classical Kalmanneural network and enable a real time processing of quickly changingsignals, which appear in adaptive antennas and similar applications.This goal is reached using such circuit elements, which increase theconvergence rate of the network and decrease the dependence ofconvergence rate on the ratio of eigenvalues of the correlation matrixof input signals.

  15. Kalman Filter Based Tracking in an Video Surveillance System

    OpenAIRE

    SULIMAN, C.; CRUCERU, C.; Moldoveanu, F.

    2010-01-01

    In this paper we have developed a Matlab/Simulink based model for monitoring a contact in a video surveillance sequence. For the segmentation process and corect identification of a contact in a surveillance video, we have used the Horn-Schunk optical flow algorithm. The position and the behavior of the correctly detected contact were monitored with the help of the traditional Kalman filter. After that we have compared the results obtained from the optical flow method with the ones obtaine...

  16. A Context Awareness System for Online Learning: Design Based Research

    Science.gov (United States)

    Laffey, James; Amelung, Chris; Goggins, Sean

    2009-01-01

    A design based research strategy examining the impressions and behavior of members of courses taught entirely online is used for refining a context-aware activity notification system (CANS). The findings show that CANS must address substantial variety in courses and members while also fitting with multitasking between online and real world…

  17. Supervised Filter Learning for Representation Based Face Recognition.

    Directory of Open Access Journals (Sweden)

    Chao Bi

    Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

  18. Collaborative Filtering Algorithms Based on Kendall Correlation in Recommender Systems

    Institute of Scientific and Technical Information of China (English)

    YAO Yu; ZHU Shanfeng; CHEN Xinmeng

    2006-01-01

    In this work, Kendall correlation based collaborative filtering algorithms for the recommender systems are proposed. The Kendall correlation method is used to measure the correlation amongst users by means of considering the relative order of the users' ratings. Kendall based algorithm is based upon a more general model and thus could be more widely applied in e-commerce. Another discovery of this work is that the consideration of only positive correlated neighbors in prediction, in both Pearson and Kendall algorithms, achieves higher accuracy than the consideration of all neighbors, with only a small loss of coverage.

  19. A microprocessor based anti-aliasing filter for a PCM system

    Science.gov (United States)

    Morrow, D. C.; Sandlin, D. R.

    1984-01-01

    Described is the design and evaluation of a microprocessor based digital filter. The filter was made to investigate the feasibility of a digital replacement for the analog pre-sampling filters used in telemetry systems at the NASA Ames-Dryden Flight Research Facility (DFRF). The digital filter will utilize an Intel 2920 Analog Signal Processor (ASP) chip. Testing includes measurements of: (1) the filter frequency response and, (2) the filter signal resolution. The evaluation of the digital filter was made on the basis of circuit size, projected environmental stability and filter resolution. The 2920 based digital filter was found to meet or exceed the pre-sampling filter specifications for limited signal resolution applications.

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

    Directory of Open Access Journals (Sweden)

    Jinsoo Jeong

    2011-06-01

    Full Text Available 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.

  1. Information Filtering via Implicit Trust-based Network

    CERN Document Server

    Xuan, Zhao-Guo; Liu, Jian-Guo

    2011-01-01

    Based on the user-item bipartite network, collaborative filtering (CF) recommender systems predict users' interests according to their history collections, which is a promising way to solve the information exploration problem. However, CF algorithm encounters cold start and sparsity problems. The trust-based CF algorithm is implemented by collecting the users' trust statements, which is time-consuming and must use users' private friendship information. In this paper, we present a novel measurement to calculate users' implicit trust-based correlation by taking into account their average ratings, rating ranges, and the number of common rated items. By applying the similar idea to the items, a item-based CF algorithm is constructed. The simulation results on three benchmark data sets show that the performances of both user-based and item-based algorithms could be enhanced greatly. Finally, a hybrid algorithm is constructed by integrating the user-based and item-based algorithms, the simulation results indicate t...

  2. Tunnel Point Cloud Filtering Method Based on Elliptic Cylindrical Model

    Science.gov (United States)

    Zhua, Ningning; Jiaa, Yonghong; Luo, Lun

    2016-06-01

    The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points), therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.

  3. Kalman filter based algorithms for PANDA rate at FAIR

    Energy Technology Data Exchange (ETDEWEB)

    Prencipe, Elisabetta; Ritman, James [IKP, Forschungszentrum Juelich (Germany); Rauch, Johannes [E18, Technische Universitaet Muenchen (Germany); Collaboration: PANDA-Collaboration

    2015-07-01

    PANDA at the future FAIR facility in Darmstadt is an experiment with a cooled antiproton beam in a range between 1.5 and 15 GeV/c, allowing a wide physics program in nuclear and particle physics. High average reaction rates up to 2.10{sup 7} interactions/s are expected. PANDA is the only experiment worldwide, which combines a solenoid field and a dipole field in an experiment with a fixed target topology. The tracking system must be able to reconstruct high momenta in the laboratory frame. The tracking system of PANDA involves the presence of a high performance silicon vertex detector, a GEM detector, a Straw-Tubes central tracker, a forward tracking system, and a luminosity monitor. The first three of those, are inserted in a solenoid homogeneous magnetic field (B=2 T), the latter two are inside a dipole magnetic field (B=2 Tm), The offline tracking algorithm is developed within the PandaRoot framework, which is a part of the FAIRRoot project. The algorithm is based on a tool containing the Kalman Filter equations and a deterministic annealing filter (GENFIT). The Kalman-Filter-based routines can perform extrapolations of track parameters and covariance matrices. In GENFIT2, the Runge-Kutta track representation is available. First results of an implementation of GENFIT2 in PandaRoot are presented. Resolutions and efficiencies for different beam momenta and different track hypotheses are shown.

  4. TUNNEL POINT CLOUD FILTERING METHOD BASED ON ELLIPTIC CYLINDRICAL MODEL

    Directory of Open Access Journals (Sweden)

    N. Zhu

    2016-06-01

    Full Text Available The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points, therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.

  5. Online Fault Diagnosis Method Based on Nonlinear Spectral Analysis

    Institute of Scientific and Technical Information of China (English)

    WEI Rui-xuan; WU Li-xun; WANG Yong-chang; HAN Chong-zhao

    2005-01-01

    The fault diagnosis based on nonlinear spectral analysis is a new technique for the nonlinear fault diagnosis, but its online application could be limited because of the enormous compution requirements for the estimation of general frequency response functions. Based on the fully decoupled Volterra identification algorithm, a new online fault diagnosis method based on nonlinear spectral analysis is presented, which can availably reduce the online compution requirements of general frequency response functions. The composition and working principle of the method are described, the test experiments have been done for damping spring of a vehicle suspension system by utilizing the new method, and the results indicate that the method is efficient.

  6. Diffusion filtering in image processing based on wavelet transform

    Institute of Scientific and Technical Information of China (English)

    LIU Feng

    2006-01-01

    The nonlinear diffusion filtering in image processing bases on the heat diffusion equations. Its key is the control of diffusion amount. In the previous models, the diffusivity depends on the gradients of images. So it is easily affected by noises. This paper first gives a new multiscale computational technique for diffusivity. Then we proposed a class of nonlinear wavelet diffusion (NWD) models that are used to restore images. The NWD model has strong ability to resist noise.But it, like the previous models, requires higher computational effort. Thus, by simplifying the NWD, we establish linear wavelet diffusion (LWD) models that consist of advection and diffusion. Since there exists the advection, the LWD filter is anisotropic, and hence can well preserve edges although the diffusion at edges is isotropic. The advantage is that the LWD model is easy to be analyzed and has lesser computational load. Finally, a variety of numerical experiments compared with the previous model are shown.

  7. Plasmonic Colour Filters Based on Coaxial Holes in Aluminium

    Directory of Open Access Journals (Sweden)

    Ranjith Rajasekharan Unnithan

    2017-04-01

    Full Text Available Aluminum is an alternative plasmonic material in the visible regions of the spectrum due to its attractive properties such as low cost, high natural abundance, ease of processing, and complementary metal-oxide-semiconductor (CMOS and liquid crystal display (LCD compatibility. Here, we present plasmonic colour filters based on coaxial holes in aluminium that operate in the visible range. Using both computational and experimental methods, fine-tuning of resonance peaks through precise geometric control of the coaxial holes is demonstrated. These results will lay the basis for the development of filters in high-resolution liquid crystal displays, RGB-spatial light modulators, liquid crystal over silicon devices and novel displays.

  8. Microstrip Cross-coupled Interdigital SIR Based Bandpass Filter

    Directory of Open Access Journals (Sweden)

    R. K. Maharjan

    2012-09-01

    Full Text Available A simple and compact 4.9 GHz bandpass filter for C-band applications is proposed. This paper presents a novel microstrip cross-coupled interdigital half-wavelength stepped impedance resonator (SIR based bandpass filter (BPF.The designed structure is similar to that of a combination of two parallel interdigital capacitors. The scattering parameters of the structure are measured using vector network analyzer (VNA. The self generated capacitive and inductive reactances within the interdigital resonators exhibited in a resonance frequency of 4.9 GHz. The resonant frequency and bandwidth of the capacitive cross-coupled resonator is directly optimized from the physical arrangement of the resonators. The measured insertion loss (S21 and return loss (S11 were 0.3 dB and 28 dB, respectively, at resonance frequency which were almost close to the simulation results.

  9. Acceleration of Directional Medain Filter Based Deinterlacing Algorithm (DMFD

    Directory of Open Access Journals (Sweden)

    Addanki Purna Ramesh

    2011-12-01

    Full Text Available This paper presents a novel directional median filter based deinterlacing algorithm (DMFD. DMFD is a content adaptive spatial deinterlacing algorithm that finds the direction of the edge and applies the median filtering along the edge to interpolate the odd pixels from the 5 pixels from the upper and 5 pixels from the lower even lines of the field. The proposed algorithm gives a significance improvement of 3db for baboon standard test image that has high textured content compared to CADEM, DOI, and MELA and also gives improved average PSNR compared previous algorithms. The algorithm written and tested in C and ported onto Altera’s NIOS II embedded soft processor and configured in CYCLONE-II FPGA. The ISA of Nios-II processor has extended with two additional instructions for calculation of absolute difference and minimum of four numbers to accelerate the FPGA implementation of the algorithms by 3.2 times

  10. Improved Collaborative Filtering Recommendation Based on Classification and User Trust

    Institute of Scientific and Technical Information of China (English)

    Xiao-Lin Xu; Guang-Lin Xu

    2016-01-01

    When dealing with the ratings from users, traditional collaborative filtering algorithms do not consider the credibility of rating data, which affects the accuracy of similarity. To address this issue, the paper proposes an improved algorithm based on classification and user trust. It firstly classifies all the ratings by the categories of items. And then, for each category, it evaluates the trustworthy degree of each user on the category and imposes the degree on the ratings of the user. Finally, the algorithm explores the similarities between users, finds the nearest neighbors, and makes recommendations within each category. Simulations show that the improved algorithm outperforms the traditional collaborative filtering algorithms and enhances the accuracy of recommendation.

  11. Performance analysis of adjustable window based FIR filter for noisy ECG Signal Filtering

    Directory of Open Access Journals (Sweden)

    N. Mahawar

    2013-09-01

    Full Text Available Recording of the electrical activity associated to heart functioning is known as Electrocardiogram (ECG. ECG is a quasi-periodical, rhythmically signal synchronized by the function of the heart, which acts as a generator of bioelectric events. ECG signals are low level signals and sensitive to external contaminations. Electrocardiogram signals are often corrupted by noise which may have electrical or electrophysiological origin. The noise signal tends to alter the signal morphology, thereby hindering the correct diagnosis. In order to remove the unwanted noise, a digital filtering technique based on adjustable windows is proposed in this paper. Finite Impulse Response (FIR low pass is designed using windowing method for the ECG signal. The results obtained from different techniques are compared on the basis of popularly used signal error measures like SNR, PRD, PRD1, and MSE.

  12. Optical thin-film reflection filters based on the theory of photonic crystals.

    Science.gov (United States)

    Sun, Xuezheng; Shen, Weidong; Gai, Xin; Gu, Peifu; Liu, Xu; Zhang, Yueguang

    2008-05-01

    Based on the theory of photonic crystals and the framework of a single-channel reflection filter that we presented before, structures of reflection filters with multiple channels are proposed. These structures can overcome some drawbacks of conventional multichannel transmission filters and are much easier to fabricate. We have practically fabricated the reflection filters with two and three channels, and the tested results show approximate agreement with theoretical simulation. Moreover, the superprism effect is also simulated in the single-channel reflection filter, the superiorities to transmission filters are discussed, and these analyses may shed some light on new applications of reflection filters in optical communication and other systems.

  13. Adaptive Notch filter based active damping for power converters using LCL filters

    DEFF Research Database (Denmark)

    Ciobotaru, M.; Rossé, A.; Bede, L.;

    2016-01-01

    This paper proposes an active damping technique for grid-connected converters using inductor-capacitor-inductor (LCL) filters. The technique relies on a discrete-time adaptive notch filter (NF) which is able to adapt its resonance frequency and bandwidth in real-time. The tuning function of this ......This paper proposes an active damping technique for grid-connected converters using inductor-capacitor-inductor (LCL) filters. The technique relies on a discrete-time adaptive notch filter (NF) which is able to adapt its resonance frequency and bandwidth in real-time. The tuning function...

  14. Information filtering based on corrected redundancy-eliminating mass diffusion.

    Science.gov (United States)

    Zhu, Xuzhen; Yang, Yujie; Chen, Guilin; Medo, Matus; Tian, Hui; Cai, Shi-Min

    2017-01-01

    Methods used in information filtering and recommendation often rely on quantifying the similarity between objects or users. The used similarity metrics often suffer from similarity redundancies arising from correlations between objects' attributes. Based on an unweighted undirected object-user bipartite network, we propose a Corrected Redundancy-Eliminating similarity index (CRE) which is based on a spreading process on the network. Extensive experiments on three benchmark data sets-Movilens, Netflix and Amazon-show that when used in recommendation, the CRE yields significant improvements in terms of recommendation accuracy and diversity. A detailed analysis is presented to unveil the origins of the observed differences between the CRE and mainstream similarity indices.

  15. Performance-Based Technology Selection Filter description report

    Energy Technology Data Exchange (ETDEWEB)

    O' Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

    1992-05-01

    A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL).

  16. Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters.

    Science.gov (United States)

    Oster, Julien; Behar, Joachim; Sayadi, Omid; Nemati, Shamim; Johnson, Alistair E W; Clifford, Gari D

    2015-09-01

    Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need to automate ECG analysis continues to grow. In previous studies, a model-based ECG filtering approach to ECG data from healthy subjects has been applied to facilitate accurate online filtering and analysis of physiological signals. We propose an extension of this approach, which models not only normal and ventricular heartbeats, but also morphologies not previously encountered. A switching Kalman filter approach is introduced to enable the automatic selection of the most likely mode (beat type), while simultaneously filtering the signal using appropriate prior knowledge. Novelty detection is also made possible by incorporating a third mode for the detection of unknown (not previously observed) morphologies, and denoted as X-factor. This new approach is compared to state-of-the-art techniques for the ventricular heartbeat classification in the MIT-BIH arrhythmia and Incart databases. F1 scores of 98.3% and 99.5% were found on each database, respectively, which are superior to other published algorithms' results reported on the same databases. Only 3% of all the beats were discarded as X-factor, and the majority of these beats contained high levels of noise. The proposed technique demonstrates accurate beat classification in the presence of previously unseen (and unlearned) morphologies and noise, and provides an automated method for morphological analysis of arbitrary (unknown) ECG leads.

  17. A Sensor-based Long Baseline Position and Velocity Navigation Filter for Underwater Vehicles

    CERN Document Server

    Batista, Pedro; Oliveira, Paulo

    2010-01-01

    This paper presents a novel Long Baseline (LBL) position and velocity navigation filter for underwater vehicles based directly on the sensor measurements. The solution departs from previous approaches as the range measurements are explicitly embedded in the filter design, therefore avoiding inversion algorithms. Moreover, the nonlinear system dynamics are considered to their full extent and no linearizations are carried out whatsoever. The filter error dynamics are globally asymptotically stable (GAS) and it is shown, under simulation environment, that the filter achieves similar performance to the Extended Kalman Filter (EKF) and outperforms linear position and velocity filters based on algebraic estimates of the position obtained from the range measurements.

  18. Comparison of OpAmp based and comparator based switched capacitor filter

    OpenAIRE

    Sahoo, Manodipan; Amrutur, Bharadwaj

    2012-01-01

    Comparator based switched capacitor circuits provide an excellent opportunity to design sampled data systems where the virtual ground condition is detected rather than being continuously forced with negative feedback in Opamp based circuits. This work is an application of this concept to design a 1 st order 330 KHz cutoff frequency Lowpass filter operating at 10 MHz sampling frequency in 0.13μm technology and 1.2 V supply voltage. The Comparator Based Switched Capacitor (CBSC) filter is compa...

  19. Detail Enhancement for Infrared Images Based on Propagated Image Filter

    Directory of Open Access Journals (Sweden)

    Yishu Peng

    2016-01-01

    Full Text Available For displaying high-dynamic-range images acquired by thermal camera systems, 14-bit raw infrared data should map into 8-bit gray values. This paper presents a new method for detail enhancement of infrared images to display the image with a relatively satisfied contrast and brightness, rich detail information, and no artifacts caused by the image processing. We first adopt a propagated image filter to smooth the input image and separate the image into the base layer and the detail layer. Then, we refine the base layer by using modified histogram projection for compressing. Meanwhile, the adaptive weights derived from the layer decomposition processing are used as the strict gain control for the detail layer. The final display result is obtained by recombining the two modified layers. Experimental results on both cooled and uncooled infrared data verify that the proposed method outperforms the method based on log-power histogram modification and bilateral filter-based detail enhancement in both detail enhancement and visual effect.

  20. An Online Learning-based Framework for Tracking

    CERN Document Server

    Chaudhuri, Kamalika; Hsu, Daniel

    2012-01-01

    We study the tracking problem, namely, estimating the hidden state of an object over time, from unreliable and noisy measurements. The standard framework for the tracking problem is the generative framework, which is the basis of solutions such as the Bayesian algorithm and its approximation, the particle filters. However, these solutions can be very sensitive to model mismatches. In this paper, motivated by online learning, we introduce a new framework for tracking. We provide an efficient tracking algorithm for this framework. We provide experimental results comparing our algorithm to the Bayesian algorithm on simulated data. Our experiments show that when there are slight model mismatches, our algorithm outperforms the Bayesian algorithm.

  1. Fault Tolerant Parallel Filters Based On Bch Codes

    Directory of Open Access Journals (Sweden)

    K.Mohana Krishna

    2015-04-01

    Full Text Available Digital filters are used in signal processing and communication systems. In some cases, the reliability of those systems is critical, and fault tolerant filter implementations are needed. Over the years, many techniques that exploit the filters’ structure and properties to achieve fault tolerance have been proposed. As technology scales, it enables more complex systems that incorporate many filters. In those complex systems, it is common that some of the filters operate in parallel, for example, by applying the same filter to different input signals. Recently, a simple technique that exploits the presence of parallel filters to achieve multiple fault tolerance has been presented. In this brief, that idea is generalized to show that parallel filters can be protected using Bose– Chaudhuri–Hocquenghem codes (BCH in which each filter is the equivalent of a bit in a traditional ECC. This new scheme allows more efficient protection when the number of parallel filters is large.

  2. Face Recognition of Illumination Tolerance in 2D Subspace Based on the Optimum Correlation Filter

    National Research Council Canada - National Science Library

    Yi Xu

    2014-01-01

    ... subspace based on the optimal correlation filter. Firstly, through the use of a particular class 2D-PCA the face image is reconstructed and by using the optimum projecting image correlation filter (OPICF...

  3. Model-Based Hand Tracking by Chamfer Distance and Adaptive Color Learning Using Particle Filter

    Directory of Open Access Journals (Sweden)

    Kerdvibulvech Chutisant

    2009-01-01

    Full Text Available We propose a new model-based hand tracking method for recovering of three-dimensional hand motion from an image sequence. We first build a three-dimensional hand model using truncated quadrics. The degrees of freedom (DOF for each joint correspond to the DOF of a real hand. This feature extraction is performed by using the Chamfer Distance function for the edge likelihood. The silhouette likelihood is performed by using a Bayesian classifier and the online adaptation of skin color probabilities. Therefore, it is to effectively deal with any illumination changes. Particle filtering is used to track the hand by predicting the next state of three-dimensional hand model. By using these techniques, this method adds the useful ability of automatic recovery from tracking failures. This method can also be used to track the guitarist's hand.

  4. Optical fiber gas sensing system based on FBG filtering

    Science.gov (United States)

    Wang, Shutao

    2008-10-01

    An optical fiber gas sensing system based on the law of Beer-Lambert is designed to determine the concentration of gas. This technique relies on the fact that the target gas has a unique, well-defined absorption characteristic within the infrared region of electromagnetic spectrum. The narrow-band filtering characteristic of optical fiber Bragg grating is used to produce the narrow spectrum light signal. An aspheric objective optical fiber collimator is used in the system as an optical fiber gas sensing detector to improve the sensitivity and stability. Experimental results show there is a high measuring sensitivity at 0.01%, and the measuring range goes beyond 5%.

  5. Speech Emotion Recognition Based on Parametric Filter and Fractal Dimension

    Science.gov (United States)

    Mao, Xia; Chen, Lijiang

    In this paper, we propose a new method that employs two novel features, correlation density (Cd) and fractal dimension (Fd), to recognize emotional states contained in speech. The former feature obtained by a list of parametric filters reflects the broad frequency components and the fine structure of lower frequency components, contributed by unvoiced phones and voiced phones, respectively; the latter feature indicates the non-linearity and self-similarity of a speech signal. Comparative experiments based on Hidden Markov Model and K Nearest Neighbor methods are carried out. The results show that Cd and Fd are much more closely related with emotional expression than the features commonly used.

  6. Vehicle Detection Based on Probability Hypothesis Density Filter

    Directory of Open Access Journals (Sweden)

    Feihu Zhang

    2016-04-01

    Full Text Available In the past decade, the developments of vehicle detection have been significantly improved. By utilizing cameras, vehicles can be detected in the Regions of Interest (ROI in complex environments. However, vision techniques often suffer from false positives and limited field of view. In this paper, a LiDAR based vehicle detection approach is proposed by using the Probability Hypothesis Density (PHD filter. The proposed approach consists of two phases: the hypothesis generation phase to detect potential objects and the hypothesis verification phase to classify objects. The performance of the proposed approach is evaluated in complex scenarios, compared with the state-of-the-art.

  7. Scattering angle-based filtering via extension in velocity

    KAUST Repository

    Kazei, Vladimir

    2016-09-06

    The scattering angle between the source and receiver wavefields can be utilized in full-waveform inversion (FWI) and in reverse-time migration (RTM) for regularization and quality control or to remove low frequency artifacts. The access to the scattering angle information is costly as the relation between local image features and scattering angles has non-stationary nature. For the purpose of a more efficient scattering angle information extraction, we develop techniques that utilize the simplicity of the scattering angle based filters for constantvelocity background models. We split the background velocity model into several domains with different velocity ranges, generating an

  8. Hidden Markov Model Based Visual Perception Filtering in Robotic Soccer

    Directory of Open Access Journals (Sweden)

    Can Kavaklioglu

    2009-02-01

    Full Text Available Autonomous robots can initiate their mission plans only after gathering sufficient information about the environment. Therefore reliable perception information plays a major role in the overall success of an autonomous robot. The Hidden Markov Model based post-perception filtering module proposed in this paper aims to identify and remove spurious perception information in a given perception sequence using the generic metapose definition. This method allows representing uncertainty in more abstract terms compared to the common physical representations. Our experiments with the four legged AIBO robot indicated that the proposed module improved perception and localization performance significantly.

  9. Adaptive skin detection based on online training

    Science.gov (United States)

    Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

    2007-11-01

    Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

  10. ESSEA: Inquiry-Based, Online Learning Communities

    Science.gov (United States)

    Schwerin, T. G.

    2002-12-01

    The Earth System Science Education Alliance (ESSEA) is a partnership between the Institute for Global Environmental Strategies (IGES) and the Center for Educational Technologies (CET) at Wheeling Jesuit University, through funding from NASA's Earth Science Enterprise. ESSEA is supporting universities, colleges, and science education organizations in offering Earth system science online graduate courses that have been developed within the CET at Wheeling Jesuit University. ESSEA has created a national professional development program aimed at improving the knowledge, skills, and resources of Earth system science educators, offering state-of-the-art, rigorous, online courses to promote understanding of Earth system science. The three available ESS courses use an innovative instructional design model and are delivered over the Internet - they feature student-centered, knowledge-building virtual communities, the optimal method for teaching and learning. Participants in these exciting professional development courses experience online, collaborative learning, while mastering new content that addresses National Education Science Standards; develop confidence in using technology; design new classroom activities; and identify new Earth system science resources. The courses have been successfully implemented for both in-service and pre-service teacher education.

  11. RSSI based indoor tracking in sensor networks using Kalman filters

    DEFF Research Database (Denmark)

    Tøgersen, Frede Aakmann; Skjøth, Flemming; Munksgaard, Lene;

    2010-01-01

    We propose an algorithm for estimating positions of devices in a sensor network using Kalman filtering techniques. The specific area of application is monitoring the movements of cows in a barn. The algorithm consists of two filters. The first filter enhances the signal-to-noise ratio...... of the observed signal strengths and gives interpolated values at specific timestamps. Information from the first filter is transferred to the second filter which estimates the positions. Methods for estimating the parameters of the filters are given and these provide a straightforward calibration of the system...

  12. Automated Dimension Determination for NMF-based Incremental Collaborative Filtering

    Directory of Open Access Journals (Sweden)

    Xiwei Wang

    2015-12-01

    Full Text Available The nonnegative matrix factorization (NMF based collaborative filtering t e chniques h a ve a c hieved great success in product recommendations. It is well known that in NMF, the dimensions of the factor matrices have to be determined in advance. Moreover, data is growing fast; thus in some cases, the dimensions need to be changed to reduce the approximation error. The recommender systems should be capable of updating new data in a timely manner without sacrificing the prediction accuracy. In this paper, we propose an NMF based data update approach with automated dimension determination for collaborative filtering purposes. The approach can determine the dimensions of the factor matrices and update them automatically. It exploits the nearest neighborhood based clustering algorithm to cluster users and items according to their auxiliary information, and uses the clusters as the constraints in NMF. The dimensions of the factor matrices are associated with the cluster quantities. When new data becomes available, the incremental clustering algorithm determines whether to increase the number of clusters or merge the existing clusters. Experiments on three different datasets (MovieLens, Sushi, and LibimSeTi were conducted to examine the proposed approach. The results show that our approach can update the data quickly and provide encouraging prediction accuracy.

  13. Analyzing subcellular structure with optical Fourier filtering based on Gabor filters

    Science.gov (United States)

    Boustany, Nada N.; Sierra, Heidy

    2013-02-01

    Label-free measurement of subcellular morphology can be used to track dynamically cellular function under various conditions and has important applications in cellular monitoring and in vitro cell assays. We show that optical filtering of scattered light by two-dimensional Gabor filters allows for direct and highly sensitive measurement of sample structure. The Gabor filters, which are defined by their spatial frequency, orientation and Gaussian envelope, can be used to track locally and in situ the characteristic size and orientation of structures within the sample. Our method consists of sequentially implementing a set of Gabor filters via a spatial light modulator placed in a conjugate Fourier plane during optical imaging and identifying the filters that yield maximum signal. Using this setup, we show that Gabor filtering of light forward-scattered by spheres yields an optical response which varies linearly with diameter between 100nm and 2000nm. The optical filtering sensitivity to changes in diameter is on the order of 20nm and can be achieved at low image resolution. We use numerical simulations to demonstrate that this linear response can be predicted from scatter theory and does not vary significantly with changes in refractive index ratio. By applying this Fourier filtering method in samples consisting of diatoms and cells, we generate false-color images of the object that encode at each pixel the size of the local structures within the object. The resolution of these encoded size maps in on the order of 0.36μm. The pixel histograms of these encoded images directly provide 20nm resolved "size spectra", depicting the size distribution of structures within the analyzed object. We use these size spectra to differentiate the morphology of apoptosis-competent and bax/bak null apoptosis-resistant cells during cell death. We also utilize the sensitivity of the Gabor filters to object orientation to track changes in organelle morphology, and detect mitochondrial

  14. T Source Inverter Based Shunt Active Filter with LCL Passive Filter for the 415V 50 Hz Distribution systems

    Directory of Open Access Journals (Sweden)

    S. Sellakumar

    2015-06-01

    Full Text Available The inverter topology is being used as an active filter to reduce the harmonics in the power system [1]. The traditional voltage source or current source inverters are having the disadvantages of limited output voltage range hence it may not be able to supply enough compensating currents during heavy switching surges, Vulnerable to EMI noise and the devices gets damaged in either open or short circuit conditions and the main switching device of VSI and CSI are not interchangeable. The active filters are the type of DC-AC system with wide range of voltage regulation and integration of energy storages is often required. This cannot be achieved with conventional inverters and hence the impedance source inverters have been suggested. The T source inverters are basically impedance source inverters which can be used as an active filter in the power system. The MATLAB simulation is done and the results are discussed in this paper for both the types. The proposed dampening system is fully characterized by LCL based passive filters [6] and T source inverter based shunt active filter. The disturbances in the supply voltage and load current due to the non linear loads are observed in the simulation. The same is studied after connecting the designed hybrid shunt active filter in the distribution system. The simulation results obtained from the proposed method proves that it gives comparatively better THD value.

  15. Band pass filters. Citations from the NTIS data base

    Science.gov (United States)

    Reed, W. E.

    1980-04-01

    A bibliography containing 242 abstracts addressing the design, fabrication, characterization, and application of band pass filters is presented. Radiofrequency, digital, acoustic surface wave, and X-ray filters are included.

  16. POF based glucose sensor incorporating grating wavelength filters

    DEFF Research Database (Denmark)

    Hassan, Hafeez Ul; Aasmul, Søren; Bang, Ole

    2014-01-01

    AND RESEARCH IN POLYMER OPTICAL DEVICES; TRIPOD. Within the domain of TRIPOD, research is conducted on "Plastic Optical Fiber based Glucose Sensors Incorporating Grating Wavelength Filters". Research will be focused to optimized fiber tips for better coupling efficiency, reducing the response time of sensor......Medtronic has already developed a plastic fiber based optical sensor to detect the concentration of glucose both in vivo and in-vitro. The glucose sensor is based on a competitive glucose binding affinity assay consisting of a glucose receptor and glucose analog (ligand) contained in a compartment......, more donor acceptor pairs got separated resulting in high intensity and vice versa. This change in optical signal is correlated to glucose concentration. (Fig.1) Medtronic Diabetes and DTU FOTONIK has been working together under the consortium of Marie Curie Research Framework called TRAINING...

  17. Denoising in electronic speckle pattern interferometry fringes by the filtering method based on partial differential equations

    Science.gov (United States)

    Tang, Chen; Zhang, Fang; Yan, Haiqing; Chen, Zhanqing

    2006-04-01

    Denoising in electronic speckle pattern interferometry fringes is the key problem in electronic speckle pattern interferometry. We present the new filtering method based on partial differential equations (called PDE filtering method) to electronic speckle pattern interferometry fringes. The PDE filtering method transforms the image processing to solving the partial differential equations. We test the proposed method on experimentally obtained electronic speckle pattern interferometry fringes, and compare with traditional mean filtering and low-pass Fourier filtering methods. The experimental results show that the technique is capable of effectively removing noise. The PDE filtering method is flexible and has fast computational speed and stable results.

  18. High-frequency SAW filters based on diamond films.

    Science.gov (United States)

    Fujii, Satoshi; Jian, Chunyun

    2012-12-01

    We have developed a diamond SAW resonator capable of operating at frequencies over 3 GHz using a SiO(2)/ interdigital transducer (IDT)/AlN/diamond structure. This structure is expected to have a high Q value and a zero temperature coefficient of frequency (TCF) over 3 GHz, based on the high acoustic velocity of AlN. The SAW characteristics of various layered structures composed of SiO(2)/IDT/AlN/diamond substrates were studied both theoretically and experimentally. The SiO(2)/IDT/AlN/diamond substrate structure allows for a thicker IDT metal layer compared with other SAW device designs, such as the SiO(2)/IDT/ZnO/diamond structure. The thicker metal IDT in the present design leads to a lower series resistance and, in turn, a low insertion loss for SAW devices over 3 GHz. Using a second-mode (Sezawa-mode) SAW, the phase velocity and electromechanical coupling coefficient of the SiO(2)/IDT/AlN/diamond substrate reached the larger values of 11 150 m/s and 0.5%, respectively, and a zero TCF characteristic at 25°C was achieved. One-port SAW resonators fabricated from diamond substrates showed a high Q of 660 at 5.4 GHz. The frequency drift over a temperature range of -25°C to 80°C was about 90 ppm, even less than that for ST-quartz SAW substrates. A two-port resonator showed a low insertion loss of 8 dB at 5.4 GHz. Finally, we designed a 5-GHz band-stop SAW filter. A 30-MHz-wide stopband at a -6-dB rejection level was achieved while keeping the passband insertion loss to 0.76 dB. These characteristics of these filters show good potential for SHF-band filters.

  19. An active damping method based on biquad digital filter for parallel grid-interfacing inverters with LCL filters

    DEFF Research Database (Denmark)

    Lu, Xiaonan; Sun, Kai; Huang, Lipei

    2014-01-01

    to the conventional active damping approaches, the biquad filter based active damping method does not require additional sensors and control loops. Meanwhile, the multiple instable closed-loop poles of the parallel inverter system can be moved to the stable region simultaneously. Real-time simulations based on dSPACE...

  20. Scheme of adaptive polarization filtering based on Kalman model

    Institute of Scientific and Technical Information of China (English)

    Song Lizhong; Qi Haiming; Qiao Xiaolin; Meng Xiande

    2006-01-01

    A new kind of adaptive polarization filtering algorithm in order to suppress the angle cheating interference for the active guidance radar is presented. The polarization characteristic of the interference is dynamically tracked by using Kalman estimator under variable environments with time. The polarization filter parameters are designed according to the polarization characteristic of the interference, and the polarization filtering is finished in the target cell. The system scheme of adaptive polarization filter is studied and the tracking performance of polarization filter and improvement of angle measurement precision are simulated. The research results demonstrate this technology can effectively suppress the angle cheating interference in guidance radar and is feasible in engineering.

  1. An Adaptive Combinatorial Morphological Filter Based on Omnidirectional Structuring Elements

    Institute of Scientific and Technical Information of China (English)

    ZHAO Chunhui; HUI Junying; SUN Shenghe

    2001-01-01

    A new adaptive morphological filter is proposed in this paper. The filter utilizes the omnidirectional structuring elements and morphological open-closing or clos-opening operations. The outputs of the morphological operations by each structuring element are linear weighted processed by means of the adaptive method under the constrained least mean absolute (CLMA) error criterion. The new filter is applied to restore a noisy image and compared with the traditional morphological filters. The simulation results have shown that the new filter possesses effective noise suppression without blurring the geometrical features of the image.

  2. Content-Based Spam Filtering on Video Sharing Social Networks

    CERN Document Server

    da Luz, Antonio; Araujo, Arnaldo

    2011-01-01

    In this work we are concerned with the detection of spam in video sharing social networks. Specifically, we investigate how much visual content-based analysis can aid in detecting spam in videos. This is a very challenging task, because of the high-level semantic concepts involved; of the assorted nature of social networks, preventing the use of constrained a priori information; and, what is paramount, of the context dependent nature of spam. Content filtering for social networks is an increasingly demanded task: due to their popularity, the number of abuses also tends to increase, annoying the user base and disrupting their services. We systematically evaluate several approaches for processing the visual information: using static and dynamic (motionaware) features, with and without considering the context, and with or without latent semantic analysis (LSA). Our experiments show that LSA is helpful, but taking the context into consideration is paramount. The whole scheme shows good results, showing the feasib...

  3. Multimodal MRI Neuroimaging with Motion Compensation Based on Particle Filtering

    CERN Document Server

    Chen, Yu-Hui; Kim, Boklye; Meyer, Charles; Hero, Alfred

    2015-01-01

    Head movement during scanning impedes activation detection in fMRI studies. Head motion in fMRI acquired using slice-based Echo Planar Imaging (EPI) can be estimated and compensated by aligning the images onto a reference volume through image registration. However, registering EPI images volume to volume fails to consider head motion between slices, which may lead to severely biased head motion estimates. Slice-to-volume registration can be used to estimate motion parameters for each slice by more accurately representing the image acquisition sequence. However, accurate slice to volume mapping is dependent on the information content of the slices: middle slices are information rich, while edge slides are information poor and more prone to distortion. In this work, we propose a Gaussian particle filter based head motion tracking algorithm to reduce the image misregistration errors. The algorithm uses a dynamic state space model of head motion with an observation equation that models continuous slice acquisitio...

  4. urCF: An Approach to Integrating User Reviews into Memory-Based Collaborative Filtering

    Science.gov (United States)

    Zhang, Zhenxue

    2013-01-01

    Blessed by the Internet age, many online retailers (e.g., Amazon.com) have deployed recommender systems to help their customers identify products that may be of their interest in order to improve cross-selling and enhance customer loyalty. Collaborative Filtering (CF) is the most successful technique among different approaches to generating…

  5. urCF: An Approach to Integrating User Reviews into Memory-Based Collaborative Filtering

    Science.gov (United States)

    Zhang, Zhenxue

    2013-01-01

    Blessed by the Internet age, many online retailers (e.g., Amazon.com) have deployed recommender systems to help their customers identify products that may be of their interest in order to improve cross-selling and enhance customer loyalty. Collaborative Filtering (CF) is the most successful technique among different approaches to generating…

  6. Low power adder based digital filter for QRS detector.

    Science.gov (United States)

    Murali, L; Chitra, D; Manigandan, T

    2014-01-01

    Most of the Biomedical applications use dedicated processors for the implementation of complex signal processing. Among them, sensor network is also a type, which has the constraint of low power consumption. Since the processing elements are the most copiously used operations in the signal processors, the power consumption of this has the major impact on the system level application. In this paper, we introduce low power concept of transistor stacking to reduce leakage power; and new architectures based on stacking to implement the full adder and its significance at the digital filter level for QRS detector are implemented. The proposed concept has lesser leakage power at the adder as well as filter level with trade-off in other quality metrics of the design. This enabled the design to be dealt with as the low-power corner and can be made adaptable to any level of hierarchical abstractions as per the requirement of the application. The proposed architectures are designed, modeled at RTL level using the Verilog-HDL, and synthesized in Synopsys Design Compiler by mapping the design to 65 nm technology library standard cells.

  7. UNIFORM ANALYTIC CONSTRUCTION OF WAVELET ANALYSIS FILTERS BASED ON SINE AND COSINE TRIGONOMETRIC FUNCTIONS

    Institute of Scientific and Technical Information of China (English)

    李建平; 唐远炎; 严中洪; 张万萍

    2001-01-01

    Based on sine and cosine functions, the compactly supported orthogonal wavelet filter coefficients with arbitrary length are constructed for the first time. When/N = 2k- 1 and N = 2k , the unified analytic constructions of orthogonal wavelet filters are put forward,respectively. The famous Daubechies filter and some other well-known wavelet filters are tested by the proposed novel method which is very useful for wavelet theory research and many application areas such as pattern recognition.

  8. Introducing passive acoustic filter in acoustic based condition monitoring: Motor bike piston-bore fault identification

    Science.gov (United States)

    Jena, D. P.; Panigrahi, S. N.

    2016-03-01

    Requirement of designing a sophisticated digital band-pass filter in acoustic based condition monitoring has been eliminated by introducing a passive acoustic filter in the present work. So far, no one has attempted to explore the possibility of implementing passive acoustic filters in acoustic based condition monitoring as a pre-conditioner. In order to enhance the acoustic based condition monitoring, a passive acoustic band-pass filter has been designed and deployed. Towards achieving an efficient band-pass acoustic filter, a generalized design methodology has been proposed to design and optimize the desired acoustic filter using multiple filter components in series. An appropriate objective function has been identified for genetic algorithm (GA) based optimization technique with multiple design constraints. In addition, the sturdiness of the proposed method has been demonstrated in designing a band-pass filter by using an n-branch Quincke tube, a high pass filter and multiple Helmholtz resonators. The performance of the designed acoustic band-pass filter has been shown by investigating the piston-bore defect of a motor-bike using engine noise signature. On the introducing a passive acoustic filter in acoustic based condition monitoring reveals the enhancement in machine learning based fault identification practice significantly. This is also a first attempt of its own kind.

  9. Efficient Online Learning via Randomized Rounding

    CERN Document Server

    Cesa-Bianchi, Nicolò

    2011-01-01

    Most online algorithms used in machine learning today are based on variants of mirror descent or follow-the-leader. In this paper, we present an online algorithm based on a completely different approach, which combines "random playout" and randomized rounding of loss subgradients. As an application of our approach, we provide the first computationally efficient online algorithm for collaborative filtering with norm-constrained matrices. As a second application, we solve an open question linking batch learning and transductive online learning.

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

    Science.gov (United States)

    Zhang, Zhen; Ma, Yaopeng

    2016-02-06

    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.

  11. Improved DCT-based nonlocal means filter for MR images denoising.

    Science.gov (United States)

    Hu, Jinrong; Pu, Yifei; Wu, Xi; Zhang, Yi; Zhou, Jiliu

    2012-01-01

    The nonlocal means (NLM) filter has been proven to be an efficient feature-preserved denoising method and can be applied to remove noise in the magnetic resonance (MR) images. To suppress noise more efficiently, we present a novel NLM filter based on the discrete cosine transform (DCT). Instead of computing similarity weights using the gray level information directly, the proposed method calculates similarity weights in the DCT subspace of neighborhood. Due to promising characteristics of DCT, such as low data correlation and high energy compaction, the proposed filter is naturally endowed with more accurate estimation of weights thus enhances denoising effectively. The performance of the proposed filter is evaluated qualitatively and quantitatively together with two other NLM filters, namely, the original NLM filter and the unbiased NLM (UNLM) filter. Experimental results demonstrate that the proposed filter achieves better denoising performance in MRI compared to the others.

  12. Damping strapdown inertial navigation system based on a Kalman filter

    Science.gov (United States)

    Zhao, Lin; Li, Jiushun; Cheng, Jianhua; Hao, Yong

    2016-11-01

    A damping strapdown inertial navigation system (DSINS) can effectively suppress oscillation errors of strapdown inertial navigation systems (SINSs) and improve the navigation accuracy of SINSs. Aiming at overcoming the disadvantages of traditional damping methods, a DSINS, based on a Kalman filter (KF), is proposed in this paper. Using the measurement data of accelerometers and calculated navigation parameters during the navigation process, the expression of the observation equation is derived. The calculation process of the observation in both the internal damping state and the external damping state is presented. Finally, system oscillation errors are compensated by a KF. Simulation and test results show that, compared with traditional damping methods, the proposed method can reduce system overshoot errors and shorten the convergence time of oscillation errors effectively.

  13. Whitelists Based Multiple Filtering Techniques in SCADA Sensor Networks

    Directory of Open Access Journals (Sweden)

    DongHo Kang

    2014-01-01

    Full Text Available Internet of Things (IoT consists of several tiny devices connected together to form a collaborative computing environment. Recently IoT technologies begin to merge with supervisory control and data acquisition (SCADA sensor networks to more efficiently gather and analyze real-time data from sensors in industrial environments. But SCADA sensor networks are becoming more and more vulnerable to cyber-attacks due to increased connectivity. To safely adopt IoT technologies in the SCADA environments, it is important to improve the security of SCADA sensor networks. In this paper we propose a multiple filtering technique based on whitelists to detect illegitimate packets. Our proposed system detects the traffic of network and application protocol attacks with a set of whitelists collected from normal traffic.

  14. Ultra compact triplexing filters based on SOI nanowire AWGs

    Science.gov (United States)

    Jiashun, Zhang; Junming, An; Lei, Zhao; Shijiao, Song; Liangliang, Wang; Jianguang, Li; Hongjie, Wang; Yuanda, Wu; Xiongwei, Hu

    2011-04-01

    An ultra compact triplexing filter was designed based on a silicon on insulator (SOI) nanowire arrayed waveguide grating (AWG) for fiber-to-the-home FTTH. The simulation results revealed that the design performed well in the sense of having a good triplexing function. The designed SOI nanowire AWGs were fabricated using ultraviolet lithography and induced coupler plasma etching. The experimental results showed that the crosstalk was less than -15 dB, and the 3 dB-bandwidth was 11.04 nm. The peak wavelength output from ports a, c, and b were 1455, 1510 and 1300 nm, respectively, which deviated from our original expectations. The deviation of the wavelength is mainly caused by 45 nm width deviation of the arrayed waveguides during the course of the fabrication process and partly caused by material dispersion.

  15. Ultra compact triplexing filters based on SOI nanowire AWGs

    Energy Technology Data Exchange (ETDEWEB)

    Zhang Jiashun; An Junming; Zhao Lei; Song Shijiao; Wang Liangliang; Li Jianguang; Wang Hongjie; Wu Yuanda; Hu Xiongwei, E-mail: junming@red.semi.ac.cn [State Key Laboratory on Integrated Optoelectronics, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083 (China)

    2011-04-15

    An ultra compact triplexing filter was designed based on a silicon on insulator (SOI) nanowire arrayed waveguide grating (AWG) for fiber-to-the-home FTTH. The simulation results revealed that the design performed well in the sense of having a good triplexing function. The designed SOI nanowire AWGs were fabricated using ultraviolet lithography and induced coupler plasma etching. The experimental results showed that the crosstalk was less than -15 dB, and the 3 dB-bandwidth was 11.04 nm. The peak wavelength output from ports a, c, and b were 1455, 1510 and 1300 nm, respectively, which deviated from our original expectations. The deviation of the wavelength is mainly caused by 45 nm width deviation of the arrayed waveguides during the course of the fabrication process and partly caused by material dispersion. (semiconductor devices)

  16. Removing Impulse Bursts from Images by Training-Based Filtering

    Directory of Open Access Journals (Sweden)

    Pertti Koivisto

    2003-03-01

    Full Text Available The characteristics of impulse bursts in remote sensing images are analyzed and a model for this noise is proposed. The model also takes into consideration other noise types, for example, the multiplicative noise present in radar images. As a case study, soft morphological filters utilizing a training-based optimization scheme are used for the noise removal. Different approaches for the training are discussed. It is shown that these techniques can provide an effective removal of impulse bursts. At the same time, other noise types in images, for example, the multiplicative noise, can be suppressed without compromising good edge and detail preservation. Numerical simulation results, as well as examples of real remote sensing images, are presented.

  17. Entropy-based straight kernel filter for echocardiography image denoising.

    Science.gov (United States)

    Rajalaxmi, S; Nirmala, S

    2014-10-01

    A new filter has been proposed with the aim of eliminating speckle noise from 2D echocardiography images. This speckle noise has to be eliminated to avoid the pseudo prediction of the underlying anatomical facts. The proposed filter uses entropy parameter to measure the disorganized occurrence of noise pixel in each row and column and to increase the image visibility. Straight kernels with 3 pixels each are chosen for the filtering process, and the filter is slided over the image to eliminate speckle. The peak signal-to-noise ratio (PSNR) is obtained in the range of 147 dB, and the root mean square error (RMSE) is very low of approximately 0.15. The proposed filter is implemented on 36 echocardiography images, and the filter has the competence to illuminate the actual anatomical facts without degrading the edges.

  18. Star-sensor-based predictive Kalman filter for satelliteattitude estimation

    Institute of Scientific and Technical Information of China (English)

    林玉荣; 邓正隆

    2002-01-01

    A real-time attitude estimation algorithm, namely the predictive Kalman filter, is presented. This algorithm can accurately estimate the three-axis attitude of a satellite using only star sensor measurements. The implementation of the filter includes two steps: first, predicting the torque modeling error, and then estimating the attitude. Simulation results indicate that the predictive Kalman filter provides robust performance in the presence of both significant errors in the assumed model and in the initial conditions.

  19. Novel optical filters based on curved grating structure

    Science.gov (United States)

    Wang, Jia-Xian; Zhao, Jing; Qiu, Weibin; Lin, Zhili; Huang, Yixin; Chen, Houbo; Qiu, Pingping

    2017-03-01

    A novel modified Rowland grating structure is proposed in this paper. Optical filters with the proposed structure are designed and fabricated with both high input and output angles. The passband width, coupling loss of the filters are investigated as a function of the output waveguide width. Nearly aberration free diffraction filters with an ultracompact footprint less than 0.5 mm2 were obtained with the proposed structure.

  20. 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.

  1. An estimation model of time-varying origin-destination flows in expressway corridors based on unscented Kalman filter

    Institute of Scientific and Technical Information of China (English)

    LI JunWei; LIN BoLiang; SUN ZhiHui; GENG XueFei

    2009-01-01

    On the basis of measurable time series of mainline and ramp flows from traffic counts and the assumption of travel time distributions, this research presents a dynamic system model and its on-line estimation algorithm for recursive estimation of Ume-varying origin-destination (OD) matrices in expressway corridors. The proposed model employs a macro-traffic flow model to estimate travel times of OD flows and uses parameters of the traffic model as state variables, which are added to the constrained function of the system. To improve the model efficiency, we revise the travel time distribution based on the feature of normal distribution. The research employs a newly developed filtering technique, called unscented Kalman filter. The proposed model is evaluated with simulation experiments.Numerical analyses with respect to the sensitivity of the selection of initial parameters on the estimation results indicate that the proposed model is sufficiently reasonable and stable for real-world applications.

  2. An estimation model of time-varying origin-destination flows in expressway corridors based on unscented Kalman filter

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    On the basis of measurable time series of mainline and ramp flows from traffic counts and the assumption of travel time distributions, this research presents a dynamic system model and its on-line estimation algorithm for recursive estimation of time-varying origin-destination (OD) matrices in expressway corridors. The proposed model employs a macro-traffic flow model to estimate travel times of OD flows and uses parameters of the traffic model as state variables, which are added to the constrained function of the system. To improve the model efficiency, we revise the travel time distribution based on the feature of normal distribution. The research employs a newly developed filtering technique, called unscented Kalman filter. The proposed model is evaluated with simulation experiments. Numerical analyses with respect to the sensitivity of the selection of initial parameters on the estimation results indicate that the proposed model is sufficiently reasonable and stable for real-world appli-cations.

  3. Dichroic rugate filters based on birefringent porous silicon.

    Science.gov (United States)

    Ishikura, Nobuyuki; Fujii, Minoru; Nishida, Kohei; Hayashi, Shinji; Diener, Joachim

    2008-09-29

    Rugate filters made of anisotropically nanostructured birefringent silicon have been fabricated and studied by polarization-resolved transmission measurements. Electrochemical etching of a (110) oriented Si wafer results in porous silicon layers which exhibit a strong in-plane birefringence. We demonstrate that a sinusoidal refractive index variation of birefringent porous silicon combined with index-matching layers and apodization results in a dichroic rugate filter having a stop-band dependent on the polarization direction of the incident light without higher-order harmonics and sidelobes. We also demonstrate that the combination of different dichroic rugate filters allow us to realize filters with more complex properties in a single preparation step.

  4. ONLINE GRINDING WHEEL WEAR COMPENSATION BY IMAGE BASED MEASURING TECHNIQUES

    Institute of Scientific and Technical Information of China (English)

    WAN Daping; HU Dejin; WU Qi; ZHANG Yonghong

    2006-01-01

    Automatic compensation of grinding wheel wear in dry grinding is accomplished by an image based online measurement method. A kind of PC-based charge-coupled device image recognition system is schemed out, which detects the topography changes of the grinding wheel surface. Profile data, which corresponds to the wear and the topography, is measured by using a digital image processing method. The grinding wheel wear is evaluated by analyzing the position deviation of the grinding wheel edge. The online wear compensation is achieved according to the measure results. The precise detection and automatic compensation system is integrated into an open structure CNC curve grinding machine. A practical application is carried out to fulfil the precision curve grinding. The experimental results confirm the benefits of the proposed techniques, and the online detection accuracy is less than 5 μm. The grinding machine provides higher precision according to the in-process grinding wheel error compensation.

  5. On-Line Voltage Stability Assessment based on PMU Measurements

    DEFF Research Database (Denmark)

    Garcia-Valle, Rodrigo; P. Da Silva, Luiz C.; Nielsen, Arne Hejde

    2009-01-01

    through statistic analysis. During the off-line analysis, a memory of high-risk situations following a pre-defined voltage stability criterion is obtained. Thereafter, basic statistics analyses are applied resulting in the definition of voltage regions. During on-line operation, voltage magnitudes......This paper presents a method for on-line monitoring of risk voltage collapse based on synchronised phasor measurement. As there is no room for intensive computation and analysis in real-time, the method is based on the combination of off-line computation and on-line monitoring, which are correlated...... of critical buses obtained by phasor measurements are monitored in relation to the risk regions. Comprehensive studies demonstrate that the proposed method could assist operators to avoid voltage collapse events, by taking preventive or emergency actions....

  6. Transistor-based filter for inhibiting load noise from entering a power supply

    Science.gov (United States)

    Taubman, Matthew S

    2013-07-02

    A transistor-based filter for inhibiting load noise from entering a power supply is disclosed. The filter includes a first transistor having an emitter coupled to a power supply, a collector coupled to a load, and a base. The filter also includes a first capacitor coupled between the base of the first transistor and a ground terminal. The filter further includes an impedance coupled between the base and a node between the collector and the load, or a second transistor and second capacitor. The impedance can be a resistor or an inductor.

  7. An online hybrid BCI system based on SSVEP and EMG

    Science.gov (United States)

    Lin, Ke; Cinetto, Andrea; Wang, Yijun; Chen, Xiaogang; Gao, Shangkai; Gao, Xiaorong

    2016-04-01

    Objective. A hybrid brain-computer interface (BCI) is a device combined with at least one other communication system that takes advantage of both parts to build a link between humans and machines. To increase the number of targets and the information transfer rate (ITR), electromyogram (EMG) and steady-state visual evoked potential (SSVEP) were combined to implement a hybrid BCI. A multi-choice selection method based on EMG was developed to enhance the system performance. Approach. A 60-target hybrid BCI speller was built in this study. A single trial was divided into two stages: a stimulation stage and an output selection stage. In the stimulation stage, SSVEP and EMG were used together. Every stimulus flickered at its given frequency to elicit SSVEP. All of the stimuli were divided equally into four sections with the same frequency set. The frequency of each stimulus in a section was different. SSVEPs were used to discriminate targets in the same section. Different sections were classified using EMG signals from the forearm. Subjects were asked to make different number of fists according to the target section. Canonical Correlation Analysis (CCA) and mean filtering was used to classify SSVEP and EMG separately. In the output selection stage, the top two optimal choices were given. The first choice with the highest probability of an accurate classification was the default output of the system. Subjects were required to make a fist to select the second choice only if the second choice was correct. Main results. The online results obtained from ten subjects showed that the mean accurate classification rate and ITR were 81.0% and 83.6 bits min-1 respectively only using the first choice selection. The ITR of the hybrid system was significantly higher than the ITR of any of the two single modalities (EMG: 30.7 bits min-1, SSVEP: 60.2 bits min-1). After the addition of the second choice selection and the correction task, the accurate classification rate and ITR was

  8. Classification of Textures Using Filter Based Local Feature Extraction

    Directory of Open Access Journals (Sweden)

    Bocekci Veysel Gokhan

    2016-01-01

    Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

  9. Damage Detection for Continuous Bridge Based on Static-Dynamic Condensation and Extended Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Haoxiang He

    2014-01-01

    Full Text Available As an effective and classical method about physical parameter identification, extended Kalman filtering (EKF algorithm is widely used in structural damage identification, but the equations and solutions for the structure with bending deformation are not established based on EKF. The degrees of freedom about rotation can be eliminated by the static condensation method, and the dynamic condensation method considering Rayleigh damping is proposed in order to establish the equivalent and simplified modal based on complex finite element model such as continuous girder bridge. According to the requirement of bridge inspection and health monitoring, the online and convenient damage detection method based on EKF is presented. The impact excitation can be generated only on one location by one hammer actuator, and the signal in free vibration is analyzed. The deficiency that the complex excitation information is needed based on the traditional method is overcome. As a numerical example, a three-span continuous girder bridge is simulated, and the corresponding stiffness, the damage location and degree, and the damping parameter are identified accurately. It is verified that the method is suitable for the dynamic signal with high noise-signal ratio; the convergence speed is fast and this method is feasible for application.

  10. A Statistical Investigation of the Sensitivity of Ensemble-Based Kalman Filters to Covariance Filtering

    Science.gov (United States)

    2011-09-01

    several in- dependent, locally stationary processes with simple parametric stationary (or isotropic) covariance func- tions ( Fuentes 2001). Parametric...230, 99–111. ——, and S. L. Anderson, 1999: A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimi- lations and...Q. Yao, 2003: Nonlinear Time Series: Nonparametric and Parametric Methods. Springer-Verlag, 552 pp. Fuentes , M., 2001: A high frequency kriging

  11. Single-Phase LLCL-Filter-based Grid-Tied Inverter with Low-Pass Filter Based Capacitor Current Feedback Active damper

    DEFF Research Database (Denmark)

    Liu, Yuan; Wu, Weimin; Li, Yun

    2016-01-01

    The capacitor-current-feedback active damping method is attractive for high-order-filter-based high power grid-tied inverter when the grid impedance varies within a wide range. In order to improve the system control bandwidth and attenuate the high order grid background harmonics by using the quasi....... In this paper, a low pass filter is proposed to be inserted in the capacitor current feedback loop op LLCL-filter based grid-tied inverter together with a digital proportional and differential compensator. The detailed theoretical analysis is given. For verification, simulations on a 2kW/220V/10kHz LLCL...

  12. A Series-LC-Filtered Active Damper for AC Power Electronics Based Power Systems

    DEFF Research Database (Denmark)

    Wang, Xiongfei; Blaabjerg, Frede; Loh, Poh Chiang

    2015-01-01

    This paper proposes an active damper with a series LC-filter for suppressing resonances in an ac power electronics based power system. The added filter capacitor helps to lower the voltage stress of the converter to be used for implementing the damper. Unlike active filters for the compensation...... is built, where the damper is integrated into a grid-connected converter. The results obtained from the experiments demonstrate the stability enhancement of ac power electronics based power systems by the active damper....

  13. Filter-radiometer-based realization of candela and establishment of photometric scale at UME

    Science.gov (United States)

    Samedov, Farhad; Durak, Murat; Bazkır, Özcan

    2005-11-01

    The luminous intensity unit of candela was realized based on filter-radiometer, which is traceable to detector-based primary standard electrical substitution cryogenic radiometer (ESCR). In that realization the traditional Osram Wi41/G-type incandescent lamp and filter-radiometer consisting of an aperture, a V(λ) filter and a silicon photodiode based trap detector were used as light source and detection element, respectively. Measurement techniques of effective aperture area, spectral transmittance of V(λ) filter and absolute responsivity of trap detector are also presented.

  14. An Agent-Based Approach to Modeling Online Social Influence

    NARCIS (Netherlands)

    Maanen, P.P. van; Vecht, B. van der

    2013-01-01

    The aim of this study is to better understand social influence in online social media. Therefore, we propose a method in which we implement, validate and improve an individual behavior model. The behavior model is based on three fundamental behavioral principles of social influence from the literatu

  15. An Agent-Based Approach to Modeling Online Social Influence

    NARCIS (Netherlands)

    Maanen, P.P. van; Vecht, B. van der

    2013-01-01

    The aim of this study is to better understand social influence in online social media. Therefore, we propose a method in which we implement, validate and improve an individual behavior model. The behavior model is based on three fundamental behavioral principles of social influence from the literatu

  16. Genetic Algorithm-Based Design of the Active Damping for an LCL-Filter Three-Phase Active Rectifier

    DEFF Research Database (Denmark)

    Liserre, Marco; Aquila, Antonio Dell; Blaabjerg, Frede

    2004-01-01

    of this filter is easily done, for a wide range of sampling frequencies, with the use of genetic algorithms. This method is used only for the optimum choice of the parameters in the filter, and an on-line implementation is not needed. Thus the resulting active damping solution does not need new sensors...

  17. Web-based kinetic modelling using JWS Online.

    Science.gov (United States)

    Olivier, Brett G; Snoep, Jacky L

    2004-09-01

    JWS Online is a repository of kinetic models, describing biological systems, which can be interactively run and interrogated over the Internet. It is implemented using a client-server strategy where the clients, in the form of web browser based Java applets, act as a graphical interface to the model servers, which perform the required numerical computations. The JWS Online website is publicly accessible at http://jjj.biochem.sun.ac.za/ with mirrors at http://www.jjj.bio.vu.nl/ and http://jjj.vbi.vt.edu/

  18. ROBOT'S MOTION ERROR AND ONLINE COMPENSATION BASED ON FORCE SENSOR

    Institute of Scientific and Technical Information of China (English)

    GAN Fangjian; LIU Zhengshi; REN Chuansheng; ZHANG Ping

    2007-01-01

    Robot's dynamic motion error and on-line compensation based on multi-axis force sensor are dealt with. It is revealed that the reasons of the error are formed and the relations of the error are delivered. A motion equation of robot's termination with the error is established, and then, an error matrix and an error compensation matrix of the motion equation are also defined. An on-line error's compensation method is put forward to decrease the displacement error, which is a degree of millimeter, shown by the result of Simulation of PUMA562 robot.

  19. Modeling online social networks based on preferential linking

    Institute of Scientific and Technical Information of China (English)

    Hu Hai-Bo; Guo Jin-Li; Chen Jun

    2012-01-01

    We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation,preferential acceptance,and preferential attachment.Based on the linear preference,we propose an analyzable model,which illustrates the mechanism of network growth and reproduces the process of network evolution.Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network.This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks.

  20. Hollow cathode lamp based Faraday anomalous dispersion optical filter.

    Science.gov (United States)

    Pan, Duo; Xue, Xiaobo; Shang, Haosen; Luo, Bin; Chen, Jingbiao; Guo, Hong

    2016-07-15

    The Faraday anomalous dispersion optical filter (FADOF), which has acquired wide applications, is mainly limited to some gaseous elements and low melting-point metals before, for the restriction of the attainable atomic density. In conventional FADOF systems a high atomic density is usually achieved by thermal equilibrium at the saturated vapor pressure, hence for elements with high melting-points a high temperature is required. To avoid this restriction, we propose a scheme of FADOF based on the hollow cathode lamp (HCL), instead of atomic vapor cells. Experimental results in strontium atoms verified this scheme, where a transmission peak corresponding to the (88)Sr (5s(2))(1)S0 - (5s5p)(1)P1 transition (461 nm) is obtained, with a maximum transmittance of 62.5% and a bandwith of 1.19 GHz. The dependence of transmission on magnetic field and HCL discharge current is also studied. Since the state-of-art commercial HCLs cover about 70 elements, this scheme can greatly expand the applications of FADOFs, and the abundant atomic transitions they provide bring the HCL based FADOFs potential applications for frequency stabilization.

  1. PSO Algorithm based Adaptive Median Filter for Noise Removal in Image Processing Application

    Directory of Open Access Journals (Sweden)

    Ruby Verma

    2016-07-01

    Full Text Available A adaptive Switching median filter for salt and pepper noise removal based on genetic algorithm is presented. Proposed filter consist of two stages, a noise detector stage and a noise filtering stage. Particle swarm optimization seems to be effective for single objective problem. Noise Dictation stage works on it. In contrast to the standard median filter, the proposed algorithm generates the noise map of corrupted Image. Noise map gives information about the corrupted and non-corrupted pixels of Image. In filtering, filter calculates the median of uncorrupted neighbouring pixels and replaces the corrupted pixels. Extensive simulations are performed to validate the proposed filter. Simulated results show refinement both in Peak signal to noise ratio (PSNR and Image Quality Index value (IQI. Experimental results shown that proposed method is more effective than existing methods.

  2. An online doctoral education course using problem-based learning.

    Science.gov (United States)

    Candela, Lori; Carver, Lara; Diaz, Anne; Edmunds, Johnna; Talusan, Richard; Tarrant, Theresa A

    2009-02-01

    The number of doctoral nursing programs has greatly increased over the past several years. There has also been a shift toward delivering programs either partially or fully online. The literature lacks discussions about doctoral-level teaching methods in the online environment. This article describes the use of a semester-long problem-based learning activity in an online doctoral course focusing on nurse educator leadership. The Students-As-Faculty Experience created for this course features the use of a virtual nursing program in which students are cast as faculty members confronting issues via faculty meetings and sharing rotating roles as chairperson. Students were vested in the process by co-designing the course in terms of developing agenda items for the meetings and evaluation rubrics. Through playing the roles of faculty and chairperson, the students reported a distinct improvement in their leadership abilities and confidence at the end of the course.

  3. Electron-Spin Filters Based on the Rashba Effect

    Science.gov (United States)

    Ting, David Z.-Y.; Cartoixa, Xavier; McGill, Thomas C.; Moon, Jeong S.; Chow, David H.; Schulman, Joel N.; Smith, Darryl L.

    2004-01-01

    Semiconductor electron-spin filters of a proposed type would be based on the Rashba effect, which is described briefly below. Electron-spin filters more precisely, sources of spin-polarized electron currents have been sought for research on, and development of, the emerging technological discipline of spintronics (spin-based electronics). There have been a number of successful demonstrations of injection of spin-polarized electrons from diluted magnetic semiconductors and from ferromagnetic metals into nonmagnetic semiconductors. In contrast, a device according to the proposal would be made from nonmagnetic semiconductor materials and would function without an applied magnetic field. The Rashba effect, named after one of its discoverers, is an energy splitting, of what would otherwise be degenerate quantum states, caused by a spin-orbit interaction in conjunction with a structural-inversion asymmetry in the presence of interfacial electric fields in a semiconductor heterostructure. The magnitude of the energy split is proportional to the electron wave number. The present proposal evolved from recent theoretical studies that suggested the possibility of devices in which electron energy states would be split by the Rashba effect and spin-polarized currents would be extracted by resonant quantum-mechanical tunneling. Accordingly, a device according to the proposal would be denoted an asymmetric resonant interband tunneling diode [a-RITD]. An a-RITD could be implemented in a variety of forms, the form favored in the proposal being a double-barrier heterostructure containing an asymmetric quantum well. It is envisioned that a-RITDs would be designed and fabricated in the InAs/GaSb/AlSb material system for several reasons: Heterostructures in this material system are strong candidates for pronounced Rashba spin splitting because InAs and GaSb exhibit large spin-orbit interactions and because both InAs and GaSb would be available for the construction of highly asymmetric

  4. DIGITAL FILTERS IMPLEMENTATION IN MICROPROCESSOR-BASED RELAY PROTECTION

    Directory of Open Access Journals (Sweden)

    Yu. V. Rumiantsev

    2016-01-01

    Full Text Available This article presents the implementation of digital filters used in digital relay protection current measuring elements. Mathematical descriptions of the considered digital filters as well as the computer programs for their coefficients calculation are described. It has been shown that in order to reliable estimate the digital filter performance its input signals waveforms must be close to the actual secondary current waveform of the current transformer to which the digital protection with the estimated digital filter is connected. For these purposes in MatLab–Simulink dynamic simulation environment the power system and the current measuring element models were developed. Performed calculations allowed to reveal that the exponentially decaying DC component which in some cases contains in primary fault current drives the current transformer core into saturation even when its nominal parameters are not exceeded. This results in distortion of the current transformer secondary current which in this case contains higher and inter-harmonics. Moreover, such harmonic content is not completely taking into account during coefficients calculation of the considered digital filters what results in signal magnitude estimation inaccuracy. Comparison of the digital filters response to the above-mentioned input signals allowed to find out such digital filter implementations which enable signal magnitude estimation with a minimum error. Ways of filtering quality improvement concerned with the window functions are proposed. Thus, the joint usage of digital filter and Hamming window allows to achieve the zero value of the signal magnitude gain factor in high-frequency range and substantially suppress all spectral components above 100 Hz. The increasing of the signal magnitude settling time in this case can be reduced by choosing the most optimal parameters of the all components of the current measuring element.

  5. Optical antialiasing filters based on complementary Golay codes.

    Science.gov (United States)

    Leger, J R; Schuler, J; Morphis, N; Knowlden, R

    1997-07-10

    An optical filter that has an ideal response for removing aliasing noise from a sampled imaging system is described. The all-phase filter uses complementary Golay codes to achieve an optimum low-pass transfer function with no sidelobes. A computer model shows that the optical system has the expected performance in the ideal case, but degrades somewhat with wavelength variations and image aberrations. An experimental demonstration of the filter shows the optical transfer function performance and the response to imagery with a sampled detector.

  6. Tunable metamaterial bandstop filter based on ferromagnetic resonance

    Directory of Open Access Journals (Sweden)

    Qingmin Wang

    2015-07-01

    Full Text Available Tunable wideband microwave bandstop filters have been investigated by experiments and simulations. The negative permeability is realized around the ferromagnetic resonance frequency which can be influenced by the demagnetization factor of the ferrite rods. For the filter composed of two ferrite rods with different size, it exhibits a -3 db stop bandwidth as large as 500 MHz, peak absorption of -40 db and an out-of-stopband insertion loss of -1.5 db. This work provides a new way to fabricate the microwave bandstop filters.

  7. FPGA-Based Efficient Programmable Polyphase FIR Filter

    Institute of Scientific and Technical Information of China (English)

    CHEN He; XIONG Cheng-huan; ZHONG Shu-nan; WANG Hua

    2005-01-01

    The modelling, design and implementation of a high-speed programmable polyphase finite impulse response (FIR) filter with field programmable gate array (FPGA) technology are described. This FIR filter can run automatically according to the programmable configuration word including symmetry/asymmetry, odd/even taps, from 32 taps up to 256 taps. The filter with 12 bit signal and 12 bit coefficient word-length has been realized on a Xilinx VirtexⅡ-v1500 device and operates at the maximum sampling frequency of 160 MHz.

  8. The behaviours of optical novelty filter based on bacteriorhodopsin film

    Institute of Scientific and Technical Information of China (English)

    Chen Gui-Ying; Yuan Yi-Zhe; Liang Xin; Xu Tang; Zhang Chun-Ping; Song Qi-Wang

    2006-01-01

    The quality of the novelty filter image is investigated at different intensities of the incident blue and yellow beams irradiating a bacteriorhodopsin (bR) film. The relationship between the transmitted blue beams and the incident yellow beams is established. The results show that the contrast of the novelty filter image depends on the lifetime of longest lived photochemical state (M state). These results enable one to identify the direction of a moving object and to improve the quality of the novel filter image by prolonging the lifetime of M state.

  9. Online Problem-Based and Enquiry-Based Learning in the Training of Educational Psychologists

    Science.gov (United States)

    Bozic, Nick; Williams, Huw

    2011-01-01

    Over the past 40 years, problem-based learning (PBL) and enquiry-based learning (EBL) approaches have been used in a variety of professional training courses. More recently online versions of these pedagogies have been developed. This paper explains how online PBL and EBL activities have been incorporated into the professional training of…

  10. MULTILEVEL INDEX STRUCTURE FOR INFORMATION FILTERING BASED ON USER CHARACTERISTIC

    Institute of Scientific and Technical Information of China (English)

    He jun; Zhou Mingtian

    2001-01-01

    Aimed at information overload and personalized characteristic of user information requirement, this letter presents a type of multilevel index structure and algorithm which is applied to large scale information filtering system and has better performance and stronger scalability.

  11. Realization of IIR Decimation Filters Based on Merged Delay Transformation

    Directory of Open Access Journals (Sweden)

    Umar Farooq

    2007-01-01

    The transformation is derived analytically and can be applied directly to first- and second-order IIR filters. Computational efficiency is enhanced because the current output can be directly computed from Mth old output. The output data rate is decreased by M by merging M number of delay elements in the recursive path. The proposed transformation is applied to higher-order IIR filter by decomposing it into parallel first-order and second-order sections. This transformation not only gives better stability for coefficient quantization but also reduces the requirement on processing clock, for sample, rate reduction. Filtering and down sampling are performed in the same stage. Number of multiplications is reduced by 45% as compared to the conventional IIR filters where all output samples are computed.

  12. Fuzzy Logic Based Autonomous Parallel Parking System with Kalman Filtering

    Science.gov (United States)

    Panomruttanarug, Benjamas; Higuchi, Kohji

    This paper presents an emulation of fuzzy logic control schemes for an autonomous parallel parking system in a backward maneuver. There are four infrared sensors sending the distance data to a microcontroller for generating an obstacle-free parking path. Two of them mounted on the front and rear wheels on the parking side are used as the inputs to the fuzzy rules to calculate a proper steering angle while backing. The other two attached to the front and rear ends serve for avoiding collision with other cars along the parking space. At the end of parking processes, the vehicle will be in line with other parked cars and positioned in the middle of the free space. Fuzzy rules are designed based upon a wall following process. Performance of the infrared sensors is improved using Kalman filtering. The design method needs extra information from ultrasonic sensors. Starting from modeling the ultrasonic sensor in 1-D state space forms, one makes use of the infrared sensor as a measurement to update the predicted values. Experimental results demonstrate the effectiveness of sensor improvement.

  13. Link performance model for filter bank based multicarrier systems

    Science.gov (United States)

    Petrov, Dmitry; Oborina, Alexandra; Giupponi, Lorenza; Stitz, Tobias Hidalgo

    2014-12-01

    This paper presents a complete link level abstraction model for link quality estimation on the system level of filter bank multicarrier (FBMC)-based networks. The application of mean mutual information per coded bit (MMIB) approach is validated for the FBMC systems. The considered quality measure of the resource element for the FBMC transmission is the received signal-to-noise-plus-distortion ratio (SNDR). Simulation results of the proposed link abstraction model show that the proposed approach is capable of estimating the block error rate (BLER) accurately, even when the signal is propagated through the channels with deep and frequent fades, as it is the case for the 3GPP Hilly Terrain (3GPP-HT) and Enhanced Typical Urban (ETU) models. The FBMC-related results of link level simulations are compared with cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) analogs. Simulation results are also validated through the comparison to reference publicly available results. Finally, the steps of link level abstraction algorithm for FBMC are formulated and its application for system level simulation of a professional mobile radio (PMR) network is discussed.

  14. Paris law parameter identification based on the Extended Kalman Filter

    Directory of Open Access Journals (Sweden)

    Melgar M.

    2016-01-01

    Full Text Available Aircraft structures are commonly subjected to repeated loading cycles leading to fatigue damage. Fatigue data can be extrapolated by fatigue models which are adopted to describe the fatigue damage behaviour. Such models depend on their parameters for accurate prediction of the fatigue life. Therefore, several methods have been developed for estimating the model parameters for both linear and nonlinear systems. It is useful for a broad class of parameter identification problems when the dynamic model is not known. In this paper, the Paris law is used as fatigue-crack-length growth model on a metallic component under loading cycles. The Extended Kalman Filter (EKF is proposed as estimation method. Simulated crack length data is used to validate the estimation method. Based on experimental data obtained from fatigue experiment, the crack length and model parameters are estimated. Accurate model parameters allow a more realistic prediction of the fatigue life, consequently, the remaining useful life (RUL of component can be accurately computed. In this sense, maintenance performance could be improved.

  15. A Particle Filter for Smartphone-Based Indoor Pedestrian Navigation

    Directory of Open Access Journals (Sweden)

    Andrea Masiero

    2014-11-01

    Full Text Available This paper considers the problem of indoor navigation by means of low-cost mobile devices. The required accuracy, the low reliability of low-cost sensor measurements and the typical unavailability of the GPS signal make indoor navigation a challenging problem. In this paper, a particle filtering approach is presented in order to obtain good navigation performance in an indoor environment: the proposed method is based on the integration of information provided by the inertial navigation system measurements, the radio signal strength of a standard wireless network and of the geometrical information of the building. In order to make the system as simple as possible from the user’s point of view, sensors are assumed to be uncalibrated at the beginning of the navigation, and an auto-calibration procedure of the magnetic sensor is performed to improve the system performance: the proposed calibration procedure is performed during regular user’s motion (no specific work is required. The navigation accuracy achievable with the proposed method and the results of the auto-calibration procedure are evaluated by means of a set of tests carried out in a university building.

  16. Emotion Recognition of Speech Signals Based on Filter Methods

    Directory of Open Access Journals (Sweden)

    Narjes Yazdanian

    2016-10-01

    Full Text Available Speech is the basic mean of communication among human beings.With the increase of transaction between human and machine, necessity of automatic dialogue and removing human factor has been considered. The aim of this study was to determine a set of affective features the speech signal is based on emotions. In this study system was designs that include three mains sections, features extraction, features selection and classification. After extraction of useful features such as, mel frequency cepstral coefficient (MFCC, linear prediction cepstral coefficients (LPC, perceptive linear prediction coefficients (PLP, ferment frequency, zero crossing rate, cepstral coefficients and pitch frequency, Mean, Jitter, Shimmer, Energy, Minimum, Maximum, Amplitude, Standard Deviation, at a later stage with filter methods such as Pearson Correlation Coefficient, t-test, relief and information gain, we came up with a method to rank and select effective features in emotion recognition. Then Result, are given to the classification system as a subset of input. In this classification stage, multi support vector machine are used to classify seven type of emotion. According to the results, that method of relief, together with multi support vector machine, has the most classification accuracy with emotion recognition rate of 93.94%.

  17. Stable and efficient cubature-based filtering in dynamical systems

    CERN Document Server

    Ballreich, Dominik

    2017-01-01

    The book addresses the problem of calculation of d-dimensional integrals (conditional expectations) in filter problems. It develops new methods of deterministic numerical integration, which can be used to speed up and stabilize filter algorithms. With the help of these methods, better estimates and predictions of latent variables are made possible in the fields of economics, engineering and physics. The resulting procedures are tested within four detailed simulation studies.

  18. Dynamic stimulus enhancement with Gabor-based filtered images

    Science.gov (United States)

    Pinkus, Alan R.; Poteet, Miriam J.; Pantle, Allan J.

    2008-04-01

    In an empirical study, observers gave ratings of their ability to detect a military target in filtered images of natural scenes. The purpose of the study was twofold. First, the absolute value of the convolution images generated with oriented Gabor filters of different scales and orientations, and pairs of filters (corner filters), provided brightness images which were evaluated as saliency maps of potential target locations. The generation of the saliency maps with oriented Gabor filters was modeled after the second-order processing of texture in the visual system. Second, two methods of presentation of the saliency maps were compared. With the flicker presentation method, a saliency map was flickered on and off at a 2-Hz rate and superimposed upon the image of the original scene. The flicker presentation method was designed to take advantage of the known properties of the magnocellular pathway of the visual system. A second method (toggle presentation) used simply for comparison, required observers to switch back and forth between the saliency image and the image of the original scene. Primary results were that (1) saliency images produced with corner filters were rated higher than those produced with simple Gabor filters, and (2) ratings obtained with the flicker method were higher than those obtained with the toggle method, with the greatest advantage for filters tuned to lower spatial frequencies. The second result suggests that the flicker presentation method holds considerable promise as a new technique for combining information (dynamic image fusion) from two or more independently obtained (e.g., multi-spectral) or processed images.

  19. Neuro-fuzzy based Controller for Solving Active Power Filter

    Directory of Open Access Journals (Sweden)

    Homayoun Ebrahimian

    2016-03-01

    Full Text Available In this paper, two soft computing techniques by fuzzy logic, neural network are used to design alternative control schemes for switching the APF active power filter (APF. The control of a shunt active power filter designed for harmonic and reactive current mitigation. Application of the mentioned model has been combined by an intelligent algorithm for improving the efficiency of proposed controller. Effectiveness of the proposed method has been applied over test case and shows the validity of proposed model.

  20. Filtering and Estimation of Vehicular Dead Reckoning System Based on Hopfield Neural Network

    Institute of Scientific and Technical Information of China (English)

    毕军; 付梦印; 张启鸿

    2003-01-01

    The algorithm of Hopfield neural network filtering and estimation is studied. The model of vehicular dead reckoning system fitting for the algorithm is constructed, and the design scheme of system filtering and estimation based on Hopfield network is proposed. Compared with Kalman filter, the algorithm does not require very precise system model and the prior knowledge of noise statistics and does not diverge easily. The simulation results show that the vehicular dead reckoning system based on Hopfield network filtering and estimation has the good position precision, and needn't require the inertial sensors with high precision. Therefore, the algorithm has the good practicability.

  1. Reduction of nonlinear patterning effects in SOA-based All-optical Switches using Optical filtering

    DEFF Research Database (Denmark)

    Nielsen, Mads Lønstrup; Mørk, Jesper; Skaguchi, J.

    2005-01-01

    We explain theoretically, and demonstrate and quantify experimentally, how appropriate filtering can reduce the dominant nonlinear patterning effect, which limits the performance of differential-mode SOA-based switches.......We explain theoretically, and demonstrate and quantify experimentally, how appropriate filtering can reduce the dominant nonlinear patterning effect, which limits the performance of differential-mode SOA-based switches....

  2. LC Filter Design for Wide Band Gap Device Based Adjustable Speed Drives

    DEFF Research Database (Denmark)

    Vadstrup, Casper; Wang, Xiongfei; Blaabjerg, Frede

    2014-01-01

    the LC filter with a higher cut off frequency and without damping resistors. The selection of inductance and capacitance is chosen based on capacitor voltage ripple and current ripple. The filter adds a base load to the inverter, which increases the inverter losses. It is shown how the modulation index...

  3. A Quantitative Analysis on Two RFS-Based Filtering Methods for Multicell Tracking

    Directory of Open Access Journals (Sweden)

    Yayun Ren

    2014-01-01

    Full Text Available Multiobject filters developed from the theory of random finite sets (RFS have recently become well-known methods for solving multiobject tracking problem. In this paper, we present two RFS-based filtering methods, Gaussian mixture probability hypothesis density (GM-PHD filter and multi-Bernoulli filter, to quantitatively analyze their performance on tracking multiple cells in a series of low-contrast image sequences. The GM-PHD filter, under linear Gaussian assumptions on the cell dynamics and birth process, applies the PHD recursion to propagate the posterior intensity in an analytic form, while the multi-Bernoulli filter estimates the multitarget posterior density through propagating the parameters of a multi-Bernoulli RFS that approximates the posterior density of multitarget RFS. Numerous performance comparisons between the two RFS-based methods are carried out on two real cell images sequences and demonstrate that both yield satisfactory results that are in good agreement with manual tracking method.

  4. Optofluidic-Tunable Color Filters And Spectroscopy Based On Liquid-Crystal Microflows

    Energy Technology Data Exchange (ETDEWEB)

    Cuennet, J. G. [Swiss Federal Institute of Technology in Lausanne (EPFL) (Switzerland); Vasdekis, Andreas E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Psaltis, D. [Swiss Federal Institute of Technology in Lausanne (EPFL) (Switzerland)

    2013-05-24

    The integration of color filters with microfluidics has attracted substantial attention in recent years, for on-chip absorption, fluorescence, or Raman analysis. We describe such tunable filters based on the micro-flow of liquid crystals. The filter operation is based on the wavelength dependent liquid crystal birefringence that can be tuned by modifying the flow velocity field in the microchannel. The latter is possible both temporally and spatially by varying the inlet pressure and the channel geometry respectively. We explored the use of these optofluidic filters for on-chip absorption spectroscopy; by integrating the distance dependent color filter with a dye-filled micro-channel, the absorption spectrum of a dye could be measured. Liquid crystal microflows simplify substantially the optofluidic integration, actuation and tuning of color filters for lab-on-a-chip spectroscopic applications.

  5. Design of reconfigurable low-complexity digital hearing aid using Farrow structure based variable bandwidth filters

    Directory of Open Access Journals (Sweden)

    Nisha Haridas

    2016-04-01

    Full Text Available A low complexity digital hearing aid is designed using a set of subband filters, for various audiograms. It is important for the device to be made of simple hardware, so that the device becomes less bulky. Hence, a low complexity design of reconfigurable filter is proposed in this paper. The tunable filter structure is designed using Farrow based variable bandwidth filter. The coefficients of the filter are expressed in canonic signed digit format. The performance can be enhanced using optimization algorithm. Here, we have explored the strength of hybrid evolutionary algorithms and compared their various combinations to select a proper coefficient representation for the Farrow based filter, which results in low complexity implementation.

  6. Measurement-based local quantum filters and their ability to transform quantum entanglement

    Indian Academy of Sciences (India)

    DEBMALYA DAS; RITABRATA SENGUPTA; ARVIND

    2017-06-01

    We introduce local filters as a means to detect the entanglement of bound entangled states which do not yield to detection by witnesses based on positive maps which are not completely positive.We demonstrate how suchnon-detectable bound entangled states can be locally filtered into detectable bound entangled states. Specifically, we show that a bound entangled state in the orthogonal complement of the unextendible product bases (UPB), canbe locally filtered into another bound entangled state that is detectable by the Choi map. We reinterpret these filters as local measurements on locally extended Hilbert spaces. We give explicit constructions of a measurement-basedimplementation of these filters for 2$\\otimes$2 and 3$\\otimes$3 systems. This provides us with a physical mechanism to implement such local filters.

  7. Eigen-based clutter filter design for ultrasound color flow imaging: a review.

    Science.gov (United States)

    Yu, Alfred; Lovstakken, Lasse

    2010-05-01

    Proper suppression of tissue clutter is a prerequisite for visualizing flow accurately in ultrasound color flow imaging. Among various clutter suppression methods, the eigen-based filter has shown potential because it can theoretically adapt its stopband to the actual clutter characteristics even when tissue motion is present. This paper presents a formative review on how eigen-based filters should be designed to improve their practical efficacy in adaptively suppressing clutter without affecting the blood flow echoes. Our review is centered around a comparative assessment of two eigen-filter design considerations: 1) eigen-component estimation approach (single-ensemble vs. multi-ensemble formulations), and 2) filter order selection mechanism (eigenvalue-based vs. frequencybased algorithms). To evaluate the practical efficacy of existing eigen-filter designs, we analyzed their clutter suppression level in two in vivo scenarios with substantial tissue motion (intra-operative coronary imaging and thyroid imaging). Our analysis shows that, as compared with polynomial regression filters (with or without instantaneous clutter downmixing), eigen-filters that use a frequency-based algorithm for filter order selection generally give Doppler power images with better contrast between blood and tissue regions. Results also suggest that both multi-ensemble and single-ensemble eigen-estimation approaches have their own advantages and weaknesses in different imaging scenarios. It may be beneficial to develop an algorithmic way of defining the eigen-filter formulation so that its performance advantages can be better realized.

  8. An object tracking method based on guided filter for night fusion image

    Science.gov (United States)

    Qian, Xiaoyan; Wang, Yuedong; Han, Lei

    2016-01-01

    Online object tracking is a challenging problem as it entails learning an effective model to account for appearance change caused by intrinsic and extrinsic factors. In this paper, we propose a novel online object tracking with guided image filter for accurate and robust night fusion image tracking. Firstly, frame difference is applied to produce the coarse target, which helps to generate observation models. Under the restriction of these models and local source image, guided filter generates sufficient and accurate foreground target. Then accurate boundaries of the target can be extracted from detection results. Finally timely updating for observation models help to avoid tracking shift. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm performs favorably against several state-of-art methods.

  9. Online Levenberg-Marquardt algorithm for digital predistortion based on direct learning and indirect learning architectures

    Science.gov (United States)

    Chen, Limin; Liang, Yin; Wan, Guojin

    2012-04-01

    An regularization approach is introduced into the online identification of inverse model for predistortion. It is based on a modified backpropagation Levenberg-Marquardt algorithm with sliding window. Adaptive predistorter with feedback was identified respectively based on direct learning and indirect learning architectures. Length of the sliding window was discussed. Compared with the Recursive Prediction Error Method (RPEM) algorithm and Nonlinear Filtered Least-Mean-Square (NFxLMS) algorithm, the algorithm is tested by identification of infinite impulse response Wiener predistorter. It is found that the proposed algorithm is much more efficient than either of the other techniques. The values of the parameters are also smaller than those extracted by the ordinary least-squares algorithm since the proposed algorithm constrains the L2-norm of the parameters.

  10. Hardware-based high-performance string lookup with value retrieval using extended Bloom filter

    Institute of Scientific and Technical Information of China (English)

    LI Qi-yue; QU Yu-gui; ZHAO Bao-hua

    2008-01-01

    In network packet processing, high-performance string lookup systems are very important. In this article, an extended Bloom filter data structure is introduced to support value retrieval string lookup, and to improve its performance, a weighted extended Bloom filter (WEBF) structure is generalized. The optimal configuration of the WEBF is then derived, and it is shown that it outperforms the traditional Bloom filter. Finally, an application-specific integrated circuit (ASIC)-based technique using WEBF is outlined.

  11. EVD Dualdating Based Online Subspace Learning

    Directory of Open Access Journals (Sweden)

    Bo Jin

    2014-01-01

    Full Text Available Conventional incremental PCA methods usually only discuss the situation of adding samples. In this paper, we consider two different cases: deleting samples and simultaneously adding and deleting samples. To avoid the NP-hard problem of downdating SVD without right singular vectors and specific position information, we choose to use EVD instead of SVD, which is used by most IPCA methods. First, we propose an EVD updating and downdating algorithm, called EVD dualdating, which permits simultaneous arbitrary adding and deleting operation, via transforming the EVD of the covariance matrix into a SVD updating problem plus an EVD of a small autocorrelation matrix. A comprehensive analysis is delivered to express the essence, expansibility, and computation complexity of EVD dualdating. A mathematical theorem proves that if the whole data matrix satisfies the low-rank-plus-shift structure, EVD dualdating is an optimal rank-k estimator under the sequential environment. A selection method based on eigenvalues is presented to determine the optimal rank k of the subspace. Then, we propose three incremental/decremental PCA methods: EVDD-IPCA, EVDD-DPCA, and EVDD-IDPCA, which are adaptive to the varying mean. Finally, plenty of comparative experiments demonstrate that EVDD-based methods outperform conventional incremental/decremental PCA methods in both efficiency and accuracy.

  12. Wellbore Surveying While Drilling Based on Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Mahmoud ElGizawy

    2010-01-01

    by designing a reliable real-time low cost MWD surveying system based on MEMS inertial sensors miniaturized inside the RSS housing installed directly behind the drill bit. A continuous borehole surveying module based on MEMS inertial sensors integrated with other drilling measurements was developed using Kalman filtering.

  13. Online Database Editor Design for Web Based Distance Education

    Directory of Open Access Journals (Sweden)

    Mustafa Ali Akça

    2015-10-01

    Full Text Available Web-Based Distance Education every day continues to increase its influence in all areas. Informatics, especially in software training is widely used in web-based distance education. However, based on coding in a course with topics of mutual teacher / student interaction, also known to increase the success of the individual is a fact. In this study, software engineering, computer engineering, computer teacher and information technology departments, such as computer programming course to be used in the online database to MSSQL editor is designed as an employee. In this study, students entering the system assigned to them can create tables in the database online, it can add data to the tables and SQL queries can be run. Students in all of these studies, despite all the distance education classroom environment facility engages in close communication facilities.

  14. Learning Vocabulary through Paper and Online-Based Glossary

    Directory of Open Access Journals (Sweden)

    Ratih Novita Sari

    2017-08-01

    Full Text Available This study examined the effect of teaching glossary and personality traits on vocabulary learning. Two groups of students who had different personality (extroverted and introverted were exposed to two types of glosses: paper and online-based glossary. The two groups underwent two-month treatment. Prior to and after the treatment, each group was given pre and posttest. In calculating the data, two-way ANOVA was used. The results of the study showed that extroverted students learned vocabulary better through paper-based glossary, while introverted students learned vocabulary better through online-based. Further research needs to be conducted to determine whether age influences the use of teaching glossary or not

  15. Turbulent-PSO-Based Fuzzy Image Filter With No-Reference Measures for High-Density Impulse Noise.

    Science.gov (United States)

    Chou, Hsien-Hsin; Hsu, Ling-Yuan; Hu, Hwai-Tsu

    2013-02-01

    Digital images are often corrupted by impulsive noise during data acquisition, transmission, and processing. This paper presents a turbulent particle swarm optimization (PSO) (TPSO)-based fuzzy filtering (or TPFF for short) approach to remove impulse noise from highly corrupted images. The proposed fuzzy filter contains a parallel fuzzy inference mechanism, a fuzzy mean process, and a fuzzy composition process. To a certain extent, the TPFF is an improved and online version of those genetic-based algorithms which had attracted a number of works during the past years. As the PSO is renowned for its ability of achieving success rate and solution quality, the superiority of the TPFF is almost for sure. In particular, by using a no-reference Q metric, the TPSO learning is sufficient to optimize the parameters necessitated by the TPFF. Therefore, the proposed fuzzy filter can cope with practical situations where the assumption of the existence of the "ground-truth" reference does not hold. The experimental results confirm that the TPFF attains an excellent quality of restored images in terms of peak signal-to-noise ratio, mean square error, and mean absolute error even when the noise rate is above 0.5 and without the aid of noise-free images.

  16. FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

    Science.gov (United States)

    Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

    2016-07-12

    In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.

  17. Comparison of sand-based water filters for point-of-use arsenic removal in China.

    Science.gov (United States)

    Smith, Kate; Li, Zhenyu; Chen, Bohan; Liang, Honggang; Zhang, Xinyi; Xu, Ruifei; Li, Zhilin; Dai, Huanfang; Wei, Caijie; Liu, Shuming

    2017-02-01

    Contamination of groundwater wells by arsenic is a major problem in China. This study compared arsenic removal efficiency of five sand-based point-of-use filters with the aim of selecting the most effective filter for use in a village in Shanxi province, where the main groundwater source had arsenic concentration >200 μg/L. A biosand filter, two arsenic biosand filters, a SONO-style filter and a version of the biosand filter with nails embedded in the sand were tested. The biosand filter with embedded nails was the most consistent and effective under the study conditions, likely due to increased contact time between water and nails and sustained corrosion. Effluent arsenic was below China's standard of 50 μg/L for more than six months after construction. The removal rate averaged 92% and was never below 86%. In comparison, arsenic removal for the nail-free biosand filter was never higher than 53% and declined with time. The arsenic biosand filter, in which nails sit in a diffuser basin above the sand, performed better but effluent arsenic almost always exceeded the standard. This highlights the positive impact on arsenic removal of embedding nails within the top layer of biosand filter sand and the promise of this low-cost filtration method for rural areas affected by arsenic contamination. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Silicon cross-connect filters using microring resonator coupled multimode-interference-based waveguide crossings.

    Science.gov (United States)

    Xu, Fang; Poon, Andrew W

    2008-06-09

    We report silicon cross-connect filters using microring resonator coupled multimode-interference (MMI) based waveguide crossings. Our experiments reveal that the MMI-based cross-connect filters impose lower crosstalk at the crossing than the conventional cross-connect filters using plain crossings, while offering a nearly symmetric resonance line shape in the drop-port transmission. As a proof-of-concept for cross-connection applications, we demonstrate on a silicon-on-insulator substrate (i) a 4-channel 1 x 4 linear-cascaded MMI-based cross-connect filter, and (ii) a 2-channel 2 x 2 array-cascaded MMI-based cross-connect filter.

  19. Reflective Pedagogy: Making Meaning in Experiential Based Online Courses

    Directory of Open Access Journals (Sweden)

    Kathy L. Guthrie

    2010-07-01

    Full Text Available The use of reflective pedagogies has long been considered critical to facilitating meaningful learning through experientially based curricula; however, the use of such methods has not been extensively explored as implemented in virtual environments. The study reviewed utilizes a combination of survey research and individual interviews to examine student perceptions of the meaningful learning which occurred as a result of their participation in two Web-based courses that utilized reflective pedagogies. One course focuses on topics related to service-learning and the second on placement-based internships. Both were instructed using online coursework based in reflective pedagogies to compliment on-site placements within local communities.

  20. Kalman Filter-based Single-baseline GNSS Data Processing without Pivot Satellite Changing

    Directory of Open Access Journals (Sweden)

    ZHANG Baocheng

    2015-09-01

    Full Text Available Single-baseline global navigation satellite system (GNSS data are able to be processed into a batch of parameters such as positions, timing information as well as atmospheric delays. The applications of relevance, therefore, consist of relative positioning, time and frequency transfer and so forth. To achieve real-time capability, these parameters are usually estimated by means of Kalman-filter. Moreover, the reliability of these parameters can be further strengthened by forming and then successfully fixing a set of independent double-differenced (DD integer ambiguities. For this purpose, the filter function model is commonly set up based on the DD observation equations (DD filter model. In order to preserve the continuity of the filter, DD filter model needs to explicitly refer to another pivot satellite once the previous one becomes invisible. This thereby implies that, before being predicted to the next epoch, the former filtered DD ambiguity vector has to be “mapped” with respect to the newly-defined pivot satellite. In addition to that, the estimated receiver phase clocks using DD filter model may soak up distinct between-receiver single-differenced (SD ambiguities belonging to different pivot satellites and would thereby be subject to apparent “integer jumps”. In this contribution, SD observation equations involving estimable DD ambiguity parameters are alternatively selected as the filter function model (SD filter model. Our analyses suggest that, both DD and SD filter models are equivalent in theory, but differ from each other as far as their implementations are concerned. Typically, for SD filter model, no effort should be made to map DD ambiguities, thus implying less intensive computational burden and better flexibility than DD filter model. At the same time, receiver phase clocks determined by SD filter model are free from “integer jumps” and thus are particularly beneficial for frequency transfer.

  1. Design and control of an LCL-filter-based three-phase active rectifier

    DEFF Research Database (Denmark)

    Liserre, Marco; Blaabjerg, Frede; Hansen, Steffan

    2005-01-01

    This paper proposes a step-by-step procedure for designing the LCL filter of a front-end three-phase active rectifier. The primary goal is to reduce the switching frequency ripple at a reasonable cost, while at the same time achieving a high-performance front-end rectifier (as characterized...... by a rapid dynamic response and good stability margin). An example LCL filter design is reported and a filter has been built and tested using the values obtained from this design. The experimental results demonstrate the performance of the design procedure both for the LCL filter and for the rectifier...... a powerful tool to design an LCL-filter-based active rectifier while avoiding trial-and-error procedures that can result in having to build several filter prototypes....

  2. LLSURE: local linear SURE-based edge-preserving image filtering.

    Science.gov (United States)

    Qiu, Tianshuang; Wang, Aiqi; Yu, Nannan; Song, Aimin

    2013-01-01

    In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.

  3. A chaotic communication system of improved performance based on the Derivative-free nonlinear Kalman filter

    Science.gov (United States)

    Rigatos, Gerasimos

    2016-07-01

    The Derivative-free nonlinear Kalman Filter is used for developing a communication system that is based on a chaotic modulator such as the Duffing system. In the transmitter's side, the source of information undergoes modulation (encryption) in which a chaotic signal generated by the Duffing system is the carrier. The modulated signal is transmitted through a communication channel and at the receiver's side demodulation takes place, after exploiting the estimation provided about the state vector of the chaotic oscillator by the Derivative-free nonlinear Kalman Filter. Evaluation tests confirm that the proposed filtering method has improved performance over the Extended Kalman Filter and reduces significantly the rate of transmission errors. Moreover, it is shown that the proposed Derivative-free nonlinear Kalman Filter can work within a dual Kalman Filtering scheme, for performing simultaneously transmitter-receiver synchronisation and estimation of unknown coefficients of the communication channel.

  4. Applications of Kalman filters based on non-linear functions to numerical weather predictions

    Directory of Open Access Journals (Sweden)

    G. Galanis

    2006-10-01

    Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.

  5. Microwave photonic notch filter with complex coefficient based on four wave mixing

    Science.gov (United States)

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

    2016-11-01

    A microwave photonic notch filter with a complex coefficient is proposed and demonstrated based on four wave mixing (FWM). FWM effect of two single-frequency laser beams occurs in a highly nonlinear fiber (HNLF), and multi-wavelength optical signals are generated and used to generate the multi-tap of microwave photonic filter (MPF). The complex coefficient is generated by using a Fourier-domain optical processor (FD-OP) to control the amplitude and phase of the optical carrier and phase modulation sidebands. The results show that this filter can be changed from bandpass filter to notch filter by controlling the FD-OP. The center frequency of the notch filter can be continuously tuned from 5.853 GHz to 29.311 GHz with free spectral range ( FSR) of 11.729 GHz. The shape of the frequency response keeps unchanged when the phase is tuned.

  6. Filter-Bank-Based Narrowband Interference Detection and Suppression in Spread Spectrum Systems

    Directory of Open Access Journals (Sweden)

    Tobias Hidalgo Stitz

    2004-07-01

    Full Text Available A filter-bank-based narrowband interference detection and suppression method is developed and its performance is studied in a spread spectrum system. The use of an efficient, complex, critically decimated perfect reconstruction filter bank with a highly selective subband filter prototype, in combination with a newly developed excision algorithm, offers a solution with efficient implementation and performance close to the theoretical limit derived as a function of the filter bank stopband attenuation. Also methods to cope with the transient effects in case of frequency hopping interference are developed and the resulting performance shows only minor degradation in comparison to the stationary case.

  7. Homomorphic partial differential equation filtering method for electronic speckle pattern interferometry fringes based on fringe density

    Institute of Scientific and Technical Information of China (English)

    Fang Zhang; Wenyao Liu; Lin Xia; Jinjiang Wang; Yue Zhu

    2009-01-01

    Noise reduction is one of the most exciting problems in electronic speckle pattern interferometry. We present a homomorphic partial differential equation filtering method for interferometry fringe patterns. The diffusion speed of the equation is determined based on the fringe density. We test the new method on the computer-simulated fringe pattern and experimentally obtain the fringe pattern, and evaluate its filtering performance. The qualitative and quantitative analysis shows that this technique can filter off the additive and multiplicative noise of the fringe patterns effectively, and avoid blurring high-density fringe. It is more capable of improving the quality of fringe patterns than the classical filtering methods.

  8. Tunable Microwave Photonic Notch Filter Based on a high-birefringence linearly chirped fiber Bragg grating

    Energy Technology Data Exchange (ETDEWEB)

    Jin Yongxing; Dong Xinyong; Wang Jianfeng [Institute of Optoelectronic Technology, China Jiliang University, Hangzhou (China); Zhou Junqiang, E-mail: phyjyxin@gmail.com [Network Technology Research Centre, Nanyang Technological University (Singapore)

    2011-02-01

    In this paper, a continuously tunable microwave photonic notch filter is proposed and experimentally demonstrated. This filter is based on the differential group delay generated by a high-birefringence linearly chirped fiber Bragg grating. This microwave photonic filter belongs to the orthogonal polarization approach, polarization maintaining structure ensures the filter free from the random optical interference problem. Its response is induced by the differential group delay (DGD) of the Hi-Bi LCFBG and it can be varied by tuning the grating through adding gradient strength to the grating. Free spectral range tuning by 9.27 GHz with more than 35 dB notch rejection is achieved.

  9. Design of optical notch filter based on Michelson Gires-Tournois interferometer

    Science.gov (United States)

    Guo, Sen; Zhang, Juan; Li, Xue

    2011-01-01

    Based on digital signal processing theory, a novel method of designing optical notch filter is presented for Michelson interferometer with Gires-Tournois Etalon. The method is not only effective and simple, but also can be used to implement the designing of the optical notch filter which has arbitrary numbers of notch points in one free spectrum range. As a designing example, the optical notch filter with one notch point is given in the paper. The change of output intensity spectrum is also investigated for the reflection coefficient of the mirror and the distance between the mirrors deviating from the ideal value, finally the tuning characteristics of the notch filter is discussed.

  10. FIR Filter Implementation Based on the RNS with Diminished-1 Encoded Channel

    Directory of Open Access Journals (Sweden)

    Dragana Uros Zivaljevic

    2013-03-01

    Full Text Available A technique, based on the residue number system (RNS with diminished-1 encoded channel, has being used for implementing a finite impulse response (FIR digital filter. The proposed RNS architecture of the filter consists of three main blocks: forward and reverse converter and arithmetic processor for each channel. Architecture for residue to binary (reverse convertor with diminished-1 encoded channel has been proposed. Besides, for all RNS channels, the systolic design is used for the efficient  realization of FIR filter. A numerical example illustrates the principles of diminished-1 residue arithmetic, signal processing, and decoding for FIR filters.

  11. 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.

  12. 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.

  13. A Speckle Reduction Filter Using Wavelet-Based Methods for Medical Imaging Application

    Science.gov (United States)

    2001-10-25

    A Speckle Reduction Filter using Wavelet-Based Methods for Medical Imaging Application Su...Wavelet-Based Methods for Medical Imaging Application Contract Number Grant Number Program Element Number Author(s) Project Number Task Number Work

  14. Fast GPU based adaptive filtering of 4D echocardiography.

    Science.gov (United States)

    Broxvall, Mathias; Emilsson, Kent; Thunberg, Per

    2012-06-01

    Time resolved three-dimensional (3D) echocardiography generates four-dimensional (3D+time) data sets that bring new possibilities in clinical practice. Image quality of four-dimensional (4D) echocardiography is however regarded as poorer compared to conventional echocardiography where time-resolved 2D imaging is used. Advanced image processing filtering methods can be used to achieve image improvements but to the cost of heavy data processing. The recent development of graphics processing unit (GPUs) enables highly parallel general purpose computations, that considerably reduces the computational time of advanced image filtering methods. In this study multidimensional adaptive filtering of 4D echocardiography was performed using GPUs. Filtering was done using multiple kernels implemented in OpenCL (open computing language) working on multiple subsets of the data. Our results show a substantial speed increase of up to 74 times, resulting in a total filtering time less than 30 s on a common desktop. This implies that advanced adaptive image processing can be accomplished in conjunction with a clinical examination. Since the presented GPU processor method scales linearly with the number of processing elements, we expect it to continue scaling with the expected future increases in number of processing elements. This should be contrasted with the increases in data set sizes in the near future following the further improvements in ultrasound probes and measuring devices. It is concluded that GPUs facilitate the use of demanding adaptive image filtering techniques that in turn enhance 4D echocardiographic data sets. The presented general methodology of implementing parallelism using GPUs is also applicable for other medical modalities that generate multidimensional data.

  15. Development of active porous medium filters based on plasma textiles

    Science.gov (United States)

    Kuznetsov, Ivan A.; Saveliev, Alexei V.; Rasipuram, Srinivasan; Kuznetsov, Andrey V.; Brown, Alan; Jasper, Warren

    2012-05-01

    Inexpensive, flexible, washable, and durable materials that serve as antimicrobial filters and self-decontaminating fabrics are needed to provide active protection to people in areas regularly exposed to various biohazards, such as hospitals and bio research labs working with pathogens. Airlines and cruise lines need such material to combat the spread of infections. In households these materials can be used in HVAC filters to fight indoor pollution, which is especially dangerous to people suffering from asthma. Efficient filtering materials are also required in areas contaminated by other types of hazardous dust particulates, such as nuclear dust. The primary idea that guided the undertaken study is that a microplasma-generating structure can be embedded in a textile fabric to generate a plasma sheath ("plasma shield") that kills bacterial agents coming in contact with the fabric. The research resulted in the development of a plasma textile that can be used for producing new types of self-decontaminating garments, fabrics, and filter materials, capable of activating a plasma sheath that would filter, capture, and destroy any bacteriological agent deposited on its surface. This new material relies on the unique antimicrobial and catalytic properties of cold (room temperature) plasma that is benign to people and does not cause thermal damage to many polymer textiles, such as Nomex and polypropylene. The uniqueness of cold plasma as a disinfecting agent lies in the inability of bacteria to develop resistance to plasma exposure, as they can for antibiotics. Plasma textiles could thus be utilized for microbial destruction in active antimicrobial filters (for continuous decontamination and disinfection of large amounts of air) as well as in self-decontaminating surfaces and antibacterial barriers (for example, for creating local antiseptic or sterile environments around wounds and burns).

  16. Development of active porous medium filters based on plasma textiles

    Energy Technology Data Exchange (ETDEWEB)

    Kuznetsov, Ivan A.; Saveliev, Alexei V.; Rasipuram, Srinivasan; Kuznetsov, Andrey V.; Brown, Alan; Jasper, Warren [Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695 (United States); Textile Engineering Chemistry and Science, North Carolina State University, Raleigh, NC 27695 (United States)

    2012-05-15

    Inexpensive, flexible, washable, and durable materials that serve as antimicrobial filters and self-decontaminating fabrics are needed to provide active protection to people in areas regularly exposed to various biohazards, such as hospitals and bio research labs working with pathogens. Airlines and cruise lines need such material to combat the spread of infections. In households these materials can be used in HVAC filters to fight indoor pollution, which is especially dangerous to people suffering from asthma. Efficient filtering materials are also required in areas contaminated by other types of hazardous dust particulates, such as nuclear dust. The primary idea that guided the undertaken study is that a microplasma-generating structure can be embedded in a textile fabric to generate a plasma sheath (''plasma shield'') that kills bacterial agents coming in contact with the fabric. The research resulted in the development of a plasma textile that can be used for producing new types of self-decontaminating garments, fabrics, and filter materials, capable of activating a plasma sheath that would filter, capture, and destroy any bacteriological agent deposited on its surface. This new material relies on the unique antimicrobial and catalytic properties of cold (room temperature) plasma that is benign to people and does not cause thermal damage to many polymer textiles, such as Nomex and polypropylene. The uniqueness of cold plasma as a disinfecting agent lies in the inability of bacteria to develop resistance to plasma exposure, as they can for antibiotics. Plasma textiles could thus be utilized for microbial destruction in active antimicrobial filters (for continuous decontamination and disinfection of large amounts of air) as well as in self-decontaminating surfaces and antibacterial barriers (for example, for creating local antiseptic or sterile environments around wounds and burns).

  17. Identifying online traffic based on property of TCP flow

    Institute of Scientific and Technical Information of China (English)

    HONG Min-huo; GU Ren-tao; WANG Hong-xiang; SUN Yong-mei; JI Yue-feng

    2009-01-01

    Classification of network traffic using port-based or payload-based analysis is becoming increasingly difficult when many applications use dynamic port numbers, masquerading techniques, and encryption to avoid detection. In this article, an approach is presented for online traffic classification relying on the observation of the first n packets of a transmission control protocol (TCP) connection. Its key idea is to utilize the properties of the observed first ten packets of a TCP connection and Bayesian network method to build a classifier. This classifier can classify TCP flows dynamically as packets pass through it by deciding whether a TCP flow belongs to a given application. The experimental results show that the proposed approach performs well in online Internet traffic classification and that it is superior to naive Bayesian method.

  18. 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...... the need for complex scaling circuits in RNS. The advantages in terms of area and speed of the presented filter, with respect to its two's complement counterpart, are evaluated for implementations in standard cells....

  19. Advanced Impulse Detection & Reduction Based on Multimodal Filter

    Directory of Open Access Journals (Sweden)

    P. Thirumurugan

    2014-07-01

    Full Text Available Impulse noises are occurred in the images during image signal acquisition and processing from one location to another location. In this paper, the optimal detector noise filtering algorithm and its efficient hardware architecture is presented. The proposed architecture comprises of orthogonal direction pattern generation, sorter, thresholder, local binary converter, multimodal filter and pixel converter units respectively. The local binary converter unit detects and corrects the noise pixel efficiently using a simple logic circuit. The design possesses only two line memory buffers with very low computational complexity, thereby reducing the hardware cost and appropriate for several real-time applications.

  20. Optical filters with fractal transmission spectra based on diffractive optics.

    Science.gov (United States)

    Mendoza-Yero, Omel; Mínguez-Vega, Gladys; Fernández-Alonso, Mercedes; Lancis, Jesús; Tajahuerce, Enrique; Climent, Vicent; Monsoriu, Juan A

    2009-03-01

    The duality between the axial irradiance distribution originated by any circularly symmetric diffracting aperture under monochromatic illumination and its diffracted spectral intensity at a fixed on-axis point under broadband illumination is highlighted and experimentally investigated. Two applications are derived from this basic result. On the one hand, we suggest the use of a broadband source and a spectrometer for a single-shot measurement of the axial response of pupil filters. Second, we implement a spectral filter having a transmission spectrum with a fractal structure of frequencies. Experimental results and potential applications in synthetic spectra designs are provided.

  1. An E-Commerce Recommender System Based on Content-Based Filtering

    Institute of Scientific and Technical Information of China (English)

    HE Weihong; CAO Yi

    2006-01-01

    Content-based filtering E-commerce recommender system was discussed fully in this paper. Users' unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products information, the recommender lists were obtained. Since the system can adapt to the users' feedback automatically, its performance were enhanced comprehensively. Finally the evaluation of the system and the experimental results were presented.

  2. Learning Vocabulary through Paper and Online-Based Glossary

    OpenAIRE

    Ratih Novita Sari

    2017-01-01

    This study examined the effect of teaching glossary and personality traits on vocabulary learning. Two groups of students who had different personality (extroverted and introverted) were exposed to two types of glosses: paper and online-based glossary. The two groups underwent two-month treatment. Prior to and after the treatment, each group was given pre and posttest. In calculating the data, two-way ANOVA was used. The results of the study showed that extroverted students learned vocabulary...

  3. A Novel Chip-based Spectrophotometer for Online Detection

    Institute of Scientific and Technical Information of China (English)

    Haoyuan Cai; Min-Hsien Wu; Zheng Cui

    2006-01-01

    A chip-based spectrophotometer integrated with optical fiber is successfully demonstrated. Grade concentration of lactate solution flowed through the chip to perform an online detection. The response time (100s) and Limit of Detection (LOD,50mg/L) of the device were measured. This device shows comparable performance with traditional commercial instrument,while greatly decreases the sample requirement per detection and reduces the size of total system, introducing a novel method for real-time detection.

  4. An optimized item-based collaborative filtering recommendation algorithm based on item genre prediction

    Science.gov (United States)

    Zhang, De-Jia

    2009-07-01

    With the fast development of Internet, many systems have emerged in e-commerce applications to support the product recommendation. Collaborative filtering is one of the most promising techniques in recommender systems, providing personalized recommendations to users based on their previously expressed preferences in the form of ratings and those of other similar users. In practice, with the adding of user and item scales, user-item ratings are becoming extremely sparsity and recommender systems utilizing traditional collaborative filtering are facing serious challenges. To address the issue, this paper presents an approach to compute item genre similarity, through mapping each item with a corresponding descriptive genre, and computing similarity between genres as similarity, then make basic predictions according to those similarities to lower sparsity of the user-item ratings. After that, item-based collaborative filtering steps are taken to generate predictions. Compared with previous methods, the presented collaborative filtering employs the item genre similarity can alleviate the sparsity issue in the recommender systems, and can improve accuracy of recommendation.

  5. Energy efficiency through model based control and online optimisation; Energieffektivisering gennem modelbaseret regulering og online optimering

    Energy Technology Data Exchange (ETDEWEB)

    Sandvig, J.

    2009-11-15

    The project's overall objective has been to use methods in model-based control and online optimization to increase industrial energy efficiency. Model-based regulation is a relatively new technology that combines knowledge of processes and systems, theoretical methods and computer processing power in intelligent, advanced control solutions and methods. The methods have so far been successfully applied in some of the largest process industries, but virtually not in small and medium-sized industries. A major reason for this is that no standard solutions have existed, and therefore it has required significant resources to develop and implement. The goal of this project is to contribute to model-based control being disseminated among the SMEs. This can be done by finding out whether it is possible to adjust and standardize the methods so that they are suitable for deployment in these segments. (ln)

  6. Evaluation of a Filter-Based Model for Computations of Cavitating Flows

    Institute of Scientific and Technical Information of China (English)

    HUANG Biao; WANG Guo-Yu

    2011-01-01

    To identify ways to improve the predictive capability of the current RANS-based cavitating turbulent closure,a filter-based model (FBM) is introduced by considering sub-filter stresses. The sub-filter stress is constructed directly by using the filter size and the conventional turbulence closure. The model is evaluated in steady cavitating flow over a blunt body revolution and unsteady cavitating flow around a Clark-Y hydrofoil respectively.Compared with the experimental data, those results indicate that FBM can be used to improve the predictive capability considerably.%@@ To identify ways to improve the predictive capability of the current RANS-based cavitating turbulent closure, a filter-based model (FBM) is introduced by considering sub-filter stresses.The sub-filter stress is constructed directly by using the filter size and the conventional turbulence closure.The model is evaluated in steady cavitating flow over a blunt body revolution and unsteady cavitating flow around a Clark-Y hydrofoil respectively.Compared with the experimental data, those results indicate that FBM can be used to improve the predictive capability considerably.

  7. A complementary least-mean-square algorithm of adaptive filtering for SQUID based magnetocardiography

    Institute of Scientific and Technical Information of China (English)

    Li Zhuo; Chen Geng-Hua; Zhang Li-Hua; Yang Qian-Sheng; Feng Ji

    2005-01-01

    We present acomplementary least-mean-square algorithm of adaptive filtering for SQUID-based magnetocardiography, in which both rapid convergence and fine tracking are realized by switching the weight parameters back and forth between two filters according to the least mean square principle.

  8. 640 Gbit/s RZ-to-NRZ format conversion based on optical phase filtering

    DEFF Research Database (Denmark)

    Maram, Reza; Kong, Deming; Galili, Michael;

    2014-01-01

    We propose a novel approach for all optical RZ-to-NRZ conversion based on optical phase filtering. The proposed concept is experimentally validated through format conversion of a 640 Gbit/s coherent RZ signal to NRZ signal using a simple phase filter implemented by a commercial optical waveshaper....

  9. Liquid crystal TV-based white light optical tracking novelty filter.

    Science.gov (United States)

    Li, Y; Kostrzewski, A; Kim, D H; Eichmann, G

    1989-11-15

    A compact white light optical tracking novelty filter is demonstrated. Based on the use of two inexpensive liquid crystal televisions, a filtered and collimated white light source, digital delay, and video recorder, this portable white light device performs two major image comparison operations, a real time image subtraction and novelty tracking operations. Some preliminary experimental results are presented.

  10. Low-cost domestic water filter: The case for a process-based ...

    African Journals Online (AJOL)

    Low-cost domestic water filter: The case for a process-based approach for the development of a rural technology product. ... The product is a low- cost water filter for which there is a definite need in rural India. The case brings ... Article Metrics.

  11. Miniature wideband filter based on coupled-line sections and quasi-lumped element resonator

    DEFF Research Database (Denmark)

    Zhurbenko, Vitaliy; Krozer, Viktor; Meincke, Peter

    2007-01-01

    A new design of a wideband bandpass filter is proposed, based on coupled-line sections and quasi-lumped element resonator, taking advantage of the last one to introduce two transmission zeros and suppress a spurious response. The proposed filter demonstrates significantly improved characteristics...

  12. Cantilever-based micro-particle filter with simultaneous single particle detection

    DEFF Research Database (Denmark)

    Noeth, Nadine-Nicole; Keller, Stephan Sylvest; Boisen, Anja

    2011-01-01

    Currently, separation of whole blood samples on lab-on-a-chip systems is achieved via filters followed by analysis of the filtered matter such as counting of blood cells. Here, a micro-chip based on cantilever technology is developed, which enables simultaneous filtration and counting of micro...

  13. Properties of predictor based on relative neighborhood graph localized FIR filters

    DEFF Research Database (Denmark)

    Sørensen, John Aasted

    1995-01-01

    A time signal prediction algorithm based on relative neighborhood graph (RNG) localized FIR filters is defined. The RNG connects two nodes, of input space dimension D, if their lune does not contain any other node. The FIR filters associated with the nodes, are used for local approximation...

  14. Adaptive Robust Tracking Control of Pressure Trajectory Based on Kalman Filter

    Institute of Scientific and Technical Information of China (English)

    CAO Jian; ZHU Xiaocong; TAO Guoliang; YAO Bin

    2009-01-01

    When adaptive robust control(ARC) strategy based on backstepping design is applied in pneumatic servo control, accurate pressure tracking in motion is especially necessary for both force and position trajectories tracking of rodless pneumatic cylinders, and therefore an adaptive robust pressure controller is developed in this paper to improve the tracking accuracy of pressure trajectory in the chamber when the pneumatic cylinder is moving. In the proposed adaptive robust pressure controller, off-line fitting of the orifice area and on-line parameter estimation of the flow coefficient are utilized to have improved model compensation, and meanwhile robust feedback and Kalman filter are used to have strong robustness against uncertain nonlinearities, parameter fluctuations and noise. Research results demonstrate that the adaptive robust pressure controller could not only track various pressure trajectories accurately even when the pneumatic cylinder is moving, but also obtain very smooth control input, which indicates the effectiveness of adaptive model compensation. Especially when a step pressure trajectory is tracked under the condition of the movement of a rodless pneumatic cylinder, maximum tracking error of ARC is 4.46 kPa and average tracking error is 0.99 kPa, and steady-state error of ARC could achieve 0.84 kPa, which is very close to the measurement accuracy of pressure transducer.

  15. Proposing Wavelet-Based Low-Pass Filter and Input Filter to Improve Transient Response of Grid-Connected Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Bijan Rahmani

    2016-08-01

    Full Text Available Available photovoltaic (PV systems show a prolonged transient response, when integrated into the power grid via active filters. On one hand, the conventional low-pass filter, employed within the integrated PV system, works with a large delay, particularly in the presence of system’s low-order harmonics. On the other hand, the switching of the DC (direct current–DC converters within PV units also prolongs the transient response of an integrated system, injecting harmonics and distortion through the PV-end current. This paper initially develops a wavelet-based low-pass filter to improve the transient response of the interconnected PV systems to grid lines. Further, a damped input filter is proposed within the PV system to address the raised converter’s switching issue. Finally, Matlab/Simulink simulations validate the effectiveness of the proposed wavelet-based low-pass filter and damped input filter within an integrated PV system.

  16. Pleasant/Unpleasant Filtering for Affective Image Retrieval Based on Cross-Correlation of EEG Features

    Directory of Open Access Journals (Sweden)

    Keranmu Xielifuguli

    2014-01-01

    Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.

  17. Path Renewal Method in Filtering Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Tae Ho Cho

    2011-01-01

    Full Text Available In applications of wireless sensor networks, there are many security issues. Attackers can create false reports and transmit the reports to the networks. These false reports can lead not only false alarms, but also the depletion of limited energy resources. In order to filter out such false reports during the forwarding process, Ye et al. proposed the statistical en-route filtering (SEF. Several research efforts to enhance the efficiency of SEF have been made. Especially, the path selection method proposed by Sun et al. can improve the detection power of SEF by considering the information on the filtering keys of and distances of upstream paths. However, such selection mechanism could lead to favored paths in heavy traffic, which would result in unbalanced energy consumption. In this paper, we propose a path renewal method to provide load balancing for sensor networks in terms of energy consumption. In our method, a node renews its upstream path to save energy resources if the remaining energy of and the communication traffic of the node exceed some threshold values. We show the effectiveness of the proposed method in terms of balanced energy consumption and filtering power by providing simulation results.

  18. Utilizing Time Redundancy for Particle Filter-Based Transfer Alignment

    Science.gov (United States)

    Chattaraj, Suvendu; Mukherjee, Abhik

    2016-07-01

    Signal detection in the presence of high noise is a challenge in natural sciences. From understanding signals emanating out of deep space probes to signals in protein interactions for systems biology, domain specific innovations are needed. The present work is in the domain of transfer alignment (TA), which deals with estimation of the misalignment of deliverable daughter munitions with respect to that of the delivering mother platform. In this domain, the design of noise filtering scheme has to consider a time varying and nonlinear system dynamics at play. The accuracy of conventional particle filter formulation suffers due to deviations from modeled system dynamics. An evolutionary particle filter can overcome this problem by evolving multiple system models through few support points per particle. However, this variant has even higher time complexity for real-time execution. As a result, measurement update gets deferred and the estimation accuracy is compromised. By running these filter algorithms on multiple processors, the execution time can be reduced, to allow frequent measurement updates. Such scheme ensures better system identification so that performance improves in case of simultaneous ejection of multiple daughters and also results in better convergence of TA algorithms for single daughter.

  19. Multi-tap complex-coefficient incoherent microwave photonic filters based on optical single-sideband modulation and narrow band optical filtering.

    Science.gov (United States)

    Sagues, Mikel; García Olcina, Raimundo; Loayssa, Alayn; Sales, Salvador; Capmany, José

    2008-01-07

    We propose a novel scheme to implement tunable multi-tap complex coefficient filters based on optical single sideband modulation and narrow band optical filtering. A four tap filter is experimentally demonstrated to highlight the enhanced tuning performance provided by complex coefficients. Optical processing is performed by the use of a cascade of four phase-shifted fiber Bragg gratings specifically fabricated for this purpose.

  20. Design and fabrication of multiple airgap-based visible filters

    Science.gov (United States)

    Ghaderi, M.; Wolffenbuttel, R. F.

    2014-05-01

    The efficiency of a Bragg reflector design for implementation in optical resonators is highly dependent on the ratio between the high-index material and the low-index material used for the quarter-wavelength (QWOT) layers. A higher contrast implies that fewer layers are required to achieve a specified spectral selectivity over a wider spectral band. In turn, the reduced total thickness of the filter stack reduces the effect of optical absorption in the layers. The research presented here focuses on implementation of filters on top of silicon detectors that are already fabricated in a CMOS process. This implies that the constraints of process compatibility, such as the materials to be used, process temperature and cleanroom reentrance related to contamination, need to be considered. Silicon-dioxide is often used in CMOS-compatible designs, which has an index of refraction n~1.5, thus limiting nHi/nLo to about 2. This value can be improved by 50% when using air-films as the low-n material. Surface micromachining is used for the fabrication of such mirrors. Multiple layers of Si and SiO2 were alternatingly deposited, and subsequently the Si layers are selectively removed in a sacrificial etch. The width of the λ/4 air-gaps is about 100 nm, which is narrower as compared to the typical layer thickness that is used in surface micromachining for conventional MEMS applications. Moreover, a demanding optical design requires more layers than typically used in a conventional MEMS device. Since the number of stacked layers is significantly higher as compared to the conventional MEMS, fabricating such filters is a challenge. However, unlike a conventional MEMS, electrical contacting to the structural layers is not required in optical filter application, which, eases the fabrication of such filters. This paper presents the design of several 4-layer structures for use in the visible spectral range, along with the fabrication sequence and preliminary measurement results.

  1. Design and analysis of a photonic crystal fiber based polarization filter using surface plasmon resonance

    Science.gov (United States)

    Yogalakshmi, S.; Selvendran, S.; Sivanantha Raja, A.

    2016-05-01

    A photonic crystal fiber with an active metal nanowire is proposed to act as a polarization filter based on the principle of plasmonic resonance. The light launched into the silica core gets coupled to gold wire inducing surface plasmon resonance, filtering one of the two orthogonally polarized light waves in the third optical communication window. This polarization filtering characteristic is analyzed using the finite element method. The change in the performance behaviour of the proposed filter is investigated by increasing the number of embedded gold wires, altering their positions and varying the diameter of gold wire. It is found that enhanced absorption of the core guided mode is achieved by replacing the filled metal nanowire with a metal coating around the air hole. Filtering of any or both polarizations can be attained by suitably positioning the metal wires. Confinement loss as high as 348.55 and 302 dB cm-1 for y-polarized and x-polarized lights respectively are attained at 1.52 and 1.56 μm respectively for single gold wire. The filter acts as a single polarization filter filtering x-polarized light with a confinement loss value of 187.67 dB cm-1 when two gold nanowires are placed adjacently. The same structure acts as the filter for y-polarized light by employing gold coating exhibiting an increased confinement loss of 406.34 dB cm-1 at 1.64 μm.

  2. Vision-Based Position Estimation Utilizing an Extended Kalman Filter

    Science.gov (United States)

    2016-12-01

    orders of magnitude less expensive than a Navy helicopter. One disadvantage that a UAV has compared to a manned helicopter is the UAV’s reliance on... segmentation ,” [Online]. Available: https://www.mathworks.com/help/images/examples/detecting-a-cell-using-image- segmentation.html. [Accessed 29 November 2016

  3. Genetic-based fuzzy image filter and its application to image processing.

    Science.gov (United States)

    Lee, Chang-Shing; Guo, Shu-Mei; Hsu, Chin-Yuan

    2005-08-01

    In this paper, we propose a Genetic-based Fuzzy Image Filter (GFIF) to remove additive identical independent distribution (i.i.d.) impulse noise from highly corrupted images. The proposed filter consists of a fuzzy number construction process, a fuzz filtering process, a genetic learning process, and an image knowledge base. First, the fuzzy number construction process receives sample images or the noise-free image and then constructs an image knowledge base for the fuzzy filtering process. Second, the fuzzy filtering process contains a parallel fuzzy inference mechanism, a fuzzy mean process, and a fuzzy decision process to perform the task of noise removal. Finally, based on the genetic algorithm, the genetic learning process adjusts the parameters of the image knowledge base. By the experimental results, GFIF achieves a better performance than the state-of-the-art filters based on the criteria of Peak-Signal-to-Noise-Ratio (PSNR), Mean-Square-Error (MSE), and Mean-Absolute-Error (MAE). On the subjective evaluation of those filtered images, GFIF also results in a higher quality of global restoration.

  4. Neural network-based H∞ filtering for nonlinear systems with time-delays

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A novel H∞ design methodology for a neural network-based nonlinear filtering scheme is addressed.Firstly,neural networks are employed to approximate the nonlinearities.Next,the nonlinear dynamic system is represented by the mode-dependent linear difference inclusion (LDI).Finally,based on the LDI model,a neural network-based nonlinear filter (NNBNF) is developed to minimize the upper bound of H∞ gain index of the estimation error under some linear matrix inequality (LMI) constraints.Compared with the existing nonlinear filters,NNBNF is time-invariant and numerically tractable.The validity and applicability of the proposed approach are successfully demonstrated in an illustrative example.

  5. 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.

  6. Active Damping Techniques for LCL-Filtered Inverters-Based Microgrids

    DEFF Research Database (Denmark)

    Lorzadeh, Iman; Firoozabadi, Mehdi Savaghebi; Askarian Abyaneh, Hossein

    2015-01-01

    LCL-type filters are widely used in gridconnected voltage source inverters, since it provides switching ripples reduction with lower cost and weight than the L-type counterpart. However, the inclusion of LCL-filters in voltage source inverters complicates the current control design regarding system...... the different active damping approaches for grid-connected inverters with LCL filters, which are based on high-order filters and additional feedbacks methods. These techniques are analyzed and discussed in detail....... stability issues; because an inherent resonance peak appears due to zero impedance at that resonance frequency. Moreover, in grid-interactive low-voltage microgrids, the interactions among the LCL-filtered-based parallel inverters may result in a more complex multiresonance issue which may compromise...

  7. Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

    Science.gov (United States)

    Singh, R.; Verma, H. K.

    2013-12-01

    This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

  8. ANN BASED ONLINE ESTIMATION OF VOLTAGE COLLAPSE PROXIMITY INDICATOR

    Directory of Open Access Journals (Sweden)

    G. Balamurugan

    2010-07-01

    Full Text Available Voltage stability has recently become a challenging issue in many power systems. There are different methods used to study the voltage collapse phenomenon but most of them take significant computation time and are not suitable for on-line applications. Fast voltage stability assessment tools are required in order to ensure the secureoperation of the present day power systems, as voltage collapse can occur quite abruptly in systems. Therefore a new ANN based on-line approach that requires minimum input for estimation of voltage collapse proximity indicator for each critical bus under normal and contingent conditions is developed in this paper. Test results onIEEE-14 bus system are presented to show its computational accuracy.

  9. Non-orthogonal optical multicarrier access based on filter bank and SCMA.

    Science.gov (United States)

    Liu, Bo; Zhang, Lijia; Xin, Xiangjun

    2015-10-19

    This paper proposes a novel non-orthogonal optical multicarrier access system based on filter bank and sparse code multiple access (SCMA). It offers released frequency offset and better spectral efficiency for multicarrier access. An experiment of 73.68 Gb/s filter bank-based multicarrier (FBMC) SCMA system with 60 km single mode fiber link is performed to demonstrate the feasibility. The comparison between fast Fourier transform (FFT) based multicarrier and the proposed scheme is also investigated in the experiment.

  10. Do Online Comments Influence the Public's Attitudes Toward an Organization? Effects of Online Comments Based on Individuals' Prior Attitudes.

    Science.gov (United States)

    Sung, Kang Hoon; Lee, Moon J

    2015-01-01

    The authors investigated the effects of reading different types of online comments about a company on people's attitude change based on individual's prior attitude toward the company. Based on Social Judgment Theory, several hypotheses were tested. The results showed that the effects of online comments interact with individuals' prior attitudes toward a corporation. People with a strong negative attitude toward a corporation were less influenced by other's online comments than people with a neutral attitude in general. However, people with a prior negative attitude were more affected by refutational two-sided comments than one-sided comments. The results suggest that the effects of user generated content should be studied in a holistic manner, not only by investigating the effects of online content itself, but also by examining how others' responses to the content shape or change individuals' attitudes based on their prior attitudes.

  11. Online Knowledge-Based Model for Big Data Topic Extraction.

    Science.gov (United States)

    Khan, Muhammad Taimoor; Durrani, Mehr; Khalid, Shehzad; Aziz, Furqan

    2016-01-01

    Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC) to support streaming data with reduced data dependency. With engineering the knowledge-base and introducing new knowledge features the learning pattern of the model is improved for data arriving in pieces. OAMC improves accuracy as topic coherence by 7% for streaming data while reducing the processing cost to half.

  12. Online Knowledge-Based Model for Big Data Topic Extraction

    Science.gov (United States)

    Khan, Muhammad Taimoor; Durrani, Mehr; Khalid, Shehzad; Aziz, Furqan

    2016-01-01

    Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain models they can easily scale up to explore big data. The existing LML models have high data dependency, consume more resources, and do not support streaming data. This paper proposes online LML model (OAMC) to support streaming data with reduced data dependency. With engineering the knowledge-base and introducing new knowledge features the learning pattern of the model is improved for data arriving in pieces. OAMC improves accuracy as topic coherence by 7% for streaming data while reducing the processing cost to half. PMID:27195004

  13. A vacuum ultraviolet filtering monochromator for synchrotron-based spectroscopy

    Science.gov (United States)

    Janik, Ireneusz; Marin, Timothy W.

    2013-01-01

    We describe the design, characterization, and implementation of a vacuum ultraviolet (VUV) monochromator for use in filtering stray and scattered light from the principal monochromator output of the Stainless Steel Seya VUV synchrotron beam line at the Synchrotron Radiation Center, University of Wisconsin-Madison. We demonstrate a reduction of three orders of magnitude of stray and scattered light over the wavelength range 1400-2000 Å with minimal loss of light intensity, allowing for over six orders of magnitude of dynamic range in light detection. We suggest that a similar filtering scheme can be utilized in any variety of spectroscopic applications where a large dynamic range and low amount of background signal are of import, such as in transmittance experiments with very high optical density.

  14. Fractional Resonance-Based RLβCα Filters

    Directory of Open Access Journals (Sweden)

    Todd J. Freeborn

    2013-01-01

    Full Text Available We propose the use of a fractional order capacitor and fractional order inductor with orders 0≤α,  β≤1, respectively, in a fractional RLβCα series circuit to realize fractional-step lowpass, highpass, bandpass, and bandreject filters. MATLAB simulations of lowpass and highpass responses having orders of (α+β=1.1, 1.5, and 1.9 and bandpass and bandreject responses having orders of 1.5 and 1.9 are given as examples. PSPICE simulations of 1.1, 1.5, and 1.9 order lowpass and 1.0 and 1.4 order bandreject filters using approximated fractional order capacitors and fractional order inductors verify the implementations.

  15. Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering

    Directory of Open Access Journals (Sweden)

    Li Guangxu

    2015-01-01

    Full Text Available A mobile robot localization method which combines relative positioning with absolute orientation is presented. The code salver and gyroscope are used for relative positioning, and the laser radar is used to detect absolute orientation. In this paper, we established environmental map, multi-sensor information fusion model, sensors and robot motion model. The Extended Kalman Filtering (EKF is adopted as multi-sensor data fusion technology to realize the precise localization of wheeled mobile robot.

  16. Coevolution-Based Adaptive Particle Filters for Global Localization

    Institute of Scientific and Technical Information of China (English)

    LUORonghua; HONGBingrong; PIAOSonghao; DAIHuming

    2005-01-01

    A coevolution mechanism derived from competition relationships between ecological species is merged into Particle filters (PF). The new version of particle filters is termed Coevolutionbased adaptive particle filters (CEAPF). In CEAPF, samples are clustered into species, each of which represents a hypothesis of state of the system in a higher level than a single sample. Since the coevolution between the species ensures that the multiple distinct hypotheses can be tracked stably, the problem of premature convergence of PF can be solved. And the number of samples can be adjusted adaptively over time according to the uncertainty of the state of the system by using the population growth model. In addition, by using the crossover and mutation operators in evolutionary computation, intra-species evolution can drive the samples move towards the regions where the desired posterior density is large. So a small number of samples can represent the desired density well enough. And CEAPF is applied to robot localization in highly symmetric environments. Experiments prove that CEAPF can considerably improve the success rate and precision of localization.

  17. Improved hybrid information filtering based on limited time window

    Science.gov (United States)

    Song, Wen-Jun; Guo, Qiang; Liu, Jian-Guo

    2014-12-01

    Adopting the entire collecting information of users, the hybrid information filtering of heat conduction and mass diffusion (HHM) (Zhou et al., 2010) was successfully proposed to solve the apparent diversity-accuracy dilemma. Since the recent behaviors are more effective to capture the users' potential interests, we present an improved hybrid information filtering of adopting the partial recent information. We expand the time window to generate a series of training sets, each of which is treated as known information to predict the future links proven by the testing set. The experimental results on one benchmark dataset Netflix indicate that by only using approximately 31% recent rating records, the accuracy could be improved by an average of 4.22% and the diversity could be improved by 13.74%. In addition, the performance on the dataset MovieLens could be preserved by considering approximately 60% recent records. Furthermore, we find that the improved algorithm is effective to solve the cold-start problem. This work could improve the information filtering performance and shorten the computational time.

  18. Improvement of QR Code Recognition Based on Pillbox Filter Analysis

    Directory of Open Access Journals (Sweden)

    Jia-Shing Sheu

    2013-04-01

    Full Text Available The objective of this paper is to perform the innovation design for improving the recognition of a captured QR code image with blur through the Pillbox filter analysis. QR code images can be captured by digital video cameras. Many factors contribute to QR code decoding failure, such as the low quality of the image. Focus is an important factor that affects the quality of the image. This study discusses the out-of-focus QR code image and aims to improve the recognition of the contents in the QR code image. Many studies have used the pillbox filter (circular averaging filter method to simulate an out-of-focus image. This method is also used in this investigation to improve the recognition of a captured QR code image. A blurred QR code image is separated into nine levels. In the experiment, four different quantitative approaches are used to reconstruct and decode an out-of-focus QR code image. These nine reconstructed QR code images using methods are then compared. The final experimental results indicate improvements in identification.

  19. A personalized web page content filtering model based on segmentation

    CERN Document Server

    Kuppusamy, K S; 10.5121/ijist.2012.2104

    2012-01-01

    In the view of massive content explosion in World Wide Web through diverse sources, it has become mandatory to have content filtering tools. The filtering of contents of the web pages holds greater significance in cases of access by minor-age people. The traditional web page blocking systems goes by the Boolean methodology of either displaying the full page or blocking it completely. With the increased dynamism in the web pages, it has become a common phenomenon that different portions of the web page holds different types of content at different time instances. This paper proposes a model to block the contents at a fine-grained level i.e. instead of completely blocking the page it would be efficient to block only those segments which holds the contents to be blocked. The advantages of this method over the traditional methods are fine-graining level of blocking and automatic identification of portions of the page to be blocked. The experiments conducted on the proposed model indicate 88% of accuracy in filter...

  20. 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.

  1. Online Signature Verification Based on DCT and Sparse Representation.

    Science.gov (United States)

    Liu, Yishu; Yang, Zhihua; Yang, Lihua

    2015-11-01

    In this paper, a novel online signature verification technique based on discrete cosine transform (DCT) and sparse representation is proposed. We find a new property of DCT, which can be used to obtain a compact representation of an online signature using a fixed number of coefficients, leading to simple matching procedures and providing an effective alternative to deal with time series of different lengths. The property is also used to extract energy features. Furthermore, a new attempt to apply sparse representation to online signature verification is made, and a novel task-specific method for building overcomplete dictionaries is proposed, then sparsity features are extracted. Finally, energy features and sparsity features are concatenated to form a feature vector. Experiments are conducted on the Sabancı University's Signature Database (SUSIG)-Visual and SVC2004 databases, and the results show that our proposed method authenticates persons very reliably with a verification performance which is better than those of state-of-the-art methods on the same databases.

  2. Marker-based filtering of bilingual phrase pairs for SMT

    OpenAIRE

    Sánchez-Martínez, Felipe; Way, Andy

    2009-01-01

    State-of-the-art statistical machine translation systems make use of a large translation table obtained after scoring a set of bilingual phrase pairs automatically extracted from a parallel corpus. The number of bilingual phrase pairs extracted from a pair of aligned sentences grows exponentially as the length of the sentences increases; therefore, the number of entries in the phrase table used to carry out the translation may become unmanageable, especially when online, ‘on demand’ translati...

  3. Overview of anisotropic filtering methods based on partial differential equations for electronic speckle pattern interferometry.

    Science.gov (United States)

    Tang, Chen; Wang, Linlin; Yan, Haiqing

    2012-07-10

    In this paper, we first present the general description for partial differential equations (PDEs) based image processing methods, including the basic idea, the main advantages and disadvantages, a few representative PDE models, and the derivation of PDE models. Then we review our contributions on PDE-based anisotropic filtering methods for electronic speckle pattern interferometry, including the second-order, fourth-order, and coupled nonoriented PDE filtering models and the second-order and coupled nonlinear oriented PDE filtering models. We have summarized the features of each model.

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

    OpenAIRE

    Zhen Zhang; Yaopeng Ma

    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) al...

  5. Random Finite Set Based Bayesian Filtering with OpenCL in a Heterogeneous Platform

    National Research Council Canada - National Science Library

    Biao Hu; Uzair Sharif; Rajat Koner; Guang Chen; Kai Huang; Feihu Zhang; Walter Stechele; Alois Knoll

    2017-01-01

    ... applications such as pedestrian detection. Towards this goal, this paper investigates the use of OpenCL to accelerate the computation of random finite set-based Bayesian filtering in a heterogeneous system...

  6. A curvature filter and PDE based non-uniformity correction algorithm

    Science.gov (United States)

    Cheng, Kuanhong; Zhou, Huixin; Qin, Hanlin; Zhao, Dong; Qian, Kun; Rong, Shenghui; Yin, Shimin

    2016-10-01

    In this paper, a curvature filter and PDE based non-uniformity correction algorithm is proposed, the key point of this algorithm is the way to estimate FPN. We use anisotropic diffusion to smooth noise and Gaussian curvature filter to extract the details of original image. Then combine these two parts together by guided image filter and subtract the result from original image to get the crude approximation of FPN. After that, a Temporal Low Pass Filter (TLPF) is utilized to filter out random noise and get the accurate FPN. Finally, subtract the FPN from original image to achieve non-uniformity correction. The performance of this algorithm is tested with two infrared image sequences, and the experimental results show that the proposed method achieves a better non-uniformity correction performance.

  7. Infrared dim target tracking based on guide filter and Bayes classification

    Science.gov (United States)

    Qian, Kun; Zhou, Hui-xin; Qin, Han-lin; Song, Shang-zhen; Zhao, Dong; Wang, Bing-jian

    2016-10-01

    An infrared dim and small tracking is proposed based on an explicit image filter - guided filter. The guided filter utilizes the structure in the guidance image and performs as an edge-preserving smoothing operator. The superior performance depending on the guidance image is critical advantage for target tracking. First, the guided filter can help to preserve the detail of the valuable templates and make the inaccurate ones blurry so that the tracker can distinguish the target from numerous bad templates easily. Besides, the filter can recover the content of the small target being influenced according to the guidance image, helping to alleviate the drifting problem effectively. Finally, the candidate samples are utilized to train an effective Bayes classifier to generate a robust tracker, which is easy to be implemented. Experimental results demonstrate that the presented method can track the target effectively, compared with several classical methods. Experimental results show that the proposed algorithm outperforms relative trackers in the accuracy and the robustness.

  8. Position USBL/DVL Sensor-based Navigation Filter in the presence of Unknown Ocean Currents

    CERN Document Server

    Morgado, M; Oliveira, P; Silvestre, C

    2010-01-01

    This paper presents a novel approach to the design of globally asymptotically stable (GAS) position filters for Autonomous Underwater Vehicles (AUVs) based directly on the nonlinear sensor readings of an Ultra-short Baseline (USBL) and a Doppler Velocity Log (DVL). Central to the proposed solution is the derivation of a linear time-varying (LTV) system that fully captures the dynamics of the nonlinear system, allowing for the use of powerful linear system analysis and filtering design tools that yield GAS filter error dynamics. Simulation results reveal that the proposed filter is able to achieve the same level of performance of more traditional solutions, such as the Extended Kalman Filter (EKF), while providing, at the same time, GAS guarantees, which are absent for the EKF.

  9. Method for signal decomposition and denoising based on nonuniform cosine-modulated filter banks

    Institute of Scientific and Technical Information of China (English)

    Xuemei Xie; Li Li; Guangming Shi; Bin Peng

    2008-01-01

    In this paper,a novel method for signal decomposition and denoising is proposed based on a nonuniform filter bank (NUFB),which is derived from a uniform filter bank.With this method,the signal is firstly decomposed into M subbands using a uniform filter bank.Then according to their energy distribution,the corresponding consecutive filters are merged to compose the nonuniform filters.With the resulting NUFB,the signal can be readily matched and flexibly decomposed according to its power spectrum distribution.As another advantage,this method can be used to detect and remove the narrow-band noise from the corrupted signal.To verify the proposed method,a simulation of extracting the main information of an audio signal and removing its glitch is given.

  10. Hypersonic entry vehicle state estimation using nonlinearity-based adaptive cubature Kalman filters

    Science.gov (United States)

    Sun, Tao; Xin, Ming

    2017-05-01

    Guidance, navigation, and control of a hypersonic vehicle landing on the Mars rely on precise state feedback information, which is obtained from state estimation. The high uncertainty and nonlinearity of the entry dynamics make the estimation a very challenging problem. In this paper, a new adaptive cubature Kalman filter is proposed for state trajectory estimation of a hypersonic entry vehicle. This new adaptive estimation strategy is based on the measure of nonlinearity of the stochastic system. According to the severity of nonlinearity along the trajectory, the high degree cubature rule or the conventional third degree cubature rule is adaptively used in the cubature Kalman filter. This strategy has the benefit of attaining higher estimation accuracy only when necessary without causing excessive computation load. The simulation results demonstrate that the proposed adaptive filter exhibits better performance than the conventional third-degree cubature Kalman filter while maintaining the same performance as the uniform high degree cubature Kalman filter but with lower computation complexity.

  11. Multiwavelength erbium-doped fiber laser based on an all-fiber polarization interference filter

    Science.gov (United States)

    Wang, Hushan; Yan, Zhijun; Zhou, Kaiming; Song, Jiazheng; Feng, Ye; Wang, Yishan

    2017-04-01

    We demonstrated a compact stable room-temperature multiwavelength erbium doped fiber laser by employing a 45° tilted fiber gratings (TFGs) based all-fiber polarization interference filter. Benefiting from the filter, the channel number, the linewidth, the uniformity and stabilization of the multiwavelength laser were greatly improved. The filter also worked as a polarizing functional device in nonlinear polarization rotation leading to multiwavelength operation. More than 60 wavelengths (within 3dB bandwidth) lasing with a linewidth of 0.03nm and a signal-to-noise ratio of 31dB were obtained. The wavelength spacing was 0.164nm agreeing with the value of the filter and it can be flexibly controlled by adjusting the length of the filter.

  12. Mecoprop (MCPP) removal in full-scale rapid sand filters at a groundwater-based waterworks

    Energy Technology Data Exchange (ETDEWEB)

    Hedegaard, Mathilde J., E-mail: mjhe@env.dtu.dk; Arvin, Erik; Corfitzen, Charlotte B.; Albrechtsen, Hans-Jørgen

    2014-11-15

    Contamination by the herbicide mecoprop (MCPP) was detected in groundwater abstraction wells at Kerteminde Waterworks in concentrations up to 0.08 μg/L. MCPP was removed to below detection limit in a simple treatment line where anaerobic groundwater was aerated and subsequently filtered by primary and secondary rapid sand filters. Water quality parameters were measured throughout the waterworks, and they behaved as designed for. MCPP was removed in secondary rapid sand filters — removal was the greatest in the sand filters in the filter line with the highest contact time (63 min). In these secondary sand filters, MCPP concentration decreased from 0.037 μg/L to below the detection limit of 0.01 μg/L. MCPP was removed continuously at different filter depths (0.80 m). Additionally, biodegradation, mineralisation and adsorption were investigated in the laboratory in order to elucidate removal mechanisms in the full-scale system. Therefore, microcosms were set up with filter sand, water and {sup 14}C-labelled MCPP at an initial concentration of 0.2 μg/L. After 24 h, 79–86% of the initial concentration of MCPP was removed. Sorption removed 11–15%, while the remaining part was removed by microbial processes, leading to a complete mineralisation of 13–18%. Microbial removal in the filter sand was similar at different depths of the rapid sand filter, while the amount of MCPP which adsorbed to the filter sand after 48 h decreased with depth from 21% of the initial MCPP in the top layer to 7% in the bottom layer. It was concluded that MCPP was removed in secondary rapid sand filters at Kerteminde Waterworks, to which both adsorption and microbial degradation contributed. - Highlights: • A full-scale groundwater based waterworks was able to remove MCPP. • In the secondary rapid sand filters, MCPP decreased from 0.037 μg/L to < 0.010 μg/L. • The filter sand removed MCPP both by sorption and by microbial degradation. • Microbial removal was unchanged while

  13. Improvement for Speech Signal based on Post Wiener Filter and Adjustable Beam-Former

    Directory of Open Access Journals (Sweden)

    Xiaorong Tong

    2013-06-01

    Full Text Available In this study, a two-stage filter structure is introduced for speech enhancement. The first stage is an adjustable filter and sum beam-former with four-microphone array. The control of beam-forming filter is realized by adjusting only a single control variable. Different from the adaptive beam-forming filter, the proposed filter structure does not bring to any adaptive error noise, thus, it also does not bring the trouble to the second stage of the speech signal processing. The second stage of the proposed filter is a Wiener filter. The estimation of signal’s power spectrum for Wiener filter is realized by cross-correlation between primary outputs of two adjacent directional beams. This estimation is based on the assumption that the noise outputs of the two adjacent directional beams come from two independent noise source but the speech outputs come from the same speech source. The simulation results shown that the proposed algorithm can improve the Signal-Noise-Ratio (SNR about 6 dB.

  14. Investigation of New Microstrip Bandpass Filter Based on Patch Resonator with Geometrical Fractal Slot.

    Science.gov (United States)

    Mezaal, Yaqeen S; Eyyuboglu, Halil T

    2016-01-01

    A compact dual-mode microstrip bandpass filter using geometrical slot is presented in this paper. The adopted geometrical slot is based on first iteration of Cantor square fractal curve. This filter has the benefits of possessing narrower and sharper frequency responses as compared to microstrip filters that use single mode resonators and traditional dual-mode square patch resonators. The filter has been modeled and demonstrated by Microwave Office EM simulator designed at a resonant frequency of 2 GHz using a substrate of εr = 10.8 and thickness of h = 1.27 mm. The output simulated results of the proposed filter exhibit 22 dB return loss, 0.1678 dB insertion loss and 12 MHz bandwidth in the passband region. In addition to the narrow band gained, miniaturization properties as well as weakened spurious frequency responses and blocked second harmonic frequency in out of band regions have been acquired. Filter parameters including insertion loss, return loss, bandwidth, coupling coefficient and external quality factor have been compared with different values of perturbation dimension (d). Also, a full comparative study of this filter as compared with traditional square patch filter has been considered.

  15. A new Recommender system based on target tracking: a Kalman Filter approach

    CERN Document Server

    Nowakowski, Samuel; Boyer, Anne

    2010-01-01

    In this paper, we propose a new approach for recommender systems based on target tracking by Kalman filtering. We assume that users and their seen resources are vectors in the multidimensional space of the categories of the resources. Knowing this space, we propose an algorithm based on a Kalman filter to track users and to predict the best prediction of their future position in the recommendation space.

  16. Target tracking in the recommender space: Toward a new recommender system based on Kalman filtering

    CERN Document Server

    Nowakowski, Samuel; Boyer, Anne

    2010-01-01

    In this paper, we propose a new approach for recommender systems based on target tracking by Kalman filtering. We assume that users and their seen resources are vectors in the multidimensional space of the categories of the resources. Knowing this space, we propose an algorithm based on a Kalman filter to track users and to predict the best prediction of their future position in the recommendation space.

  17. Modeling of porous filter penneability via image-based stochastic reconstruction of spatial porosity correlations.

    Science.gov (United States)

    Zhao, Fu; Landis, Heather R; Skerlos, Steven J

    2005-01-01

    A methodology for producing a pore-scale, 3D computational model of porous filter permeability is developed that is based on the analysis of 2D images of the filter matrix and first principles. The computationally reconstructed porous filter model retains statistical details of porosity and the spatial correlations of porosity within the filter and can be used to calculate permeability for either isotropic or 1D anisotropic porous filters. In the isotropic case, validation of the methodology was conducted using 0.2 and 0.8 microm ceramic membrane filters,forwhich it is shown that the image-based computational models provide a viable statistical reproduction of actual porosity characteristics. It is also shown that these models can predict water flux directly from first principles with deviations from experimental measurements in the range of experimental error. In the anisotropic case, validation of the methodology was conducted using a natural river sand filter. For this case, it is shown that the methodology yields predictions of filtration velocity that are similar or better than predictions offered by existing filtration models. It was found for the sand filter that the deviation between observation and prediction was mostly due to swelling during the preparation of the sand filter for imaging and can be reduced significantly using alternative methods reported in the literature. On the basis of these results, it is concluded that the computational reconstruction methodology is valid for porous filter modeling, and given that it captures pore-scale details, it has potential application to the investigation of permeability decline underthe influence of pore-scale fouling mechanisms.

  18. 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.

  19. Metamaterial based embedded acoustic filters for structural applications

    Directory of Open Access Journals (Sweden)

    Hongfei Zhu

    2013-09-01

    Full Text Available We investigate the use of acoustic metamaterials to design structural materials with frequency selective characteristics. By exploiting the properties of acoustic metamaterials, we tailor the propagation characteristics of the host structure to effectively filter the constitutive harmonics of an incoming broadband excitation. The design approach exploits the characteristics of acoustic waveguides coupled by cavity modes. By properly designing the cavity we can tune the corresponding resonant mode and, therefore, coupling the waveguide at a prescribed frequency. This structural design can open new directions to develop broadband passive vibrations and noise control systems fully integrated in structural components.

  20. Improvement of QR Code Recognition Based on Pillbox Filter Analysis

    OpenAIRE

    Jia-Shing Sheu; Kai-Chung Teng

    2013-01-01

    The objective of this paper is to perform the innovation design for improving the recognition of a captured QR code image with blur through the Pillbox filter analysis. QR code images can be captured by digital video cameras. Many factors contribute to QR code decoding failure, such as the low quality of the image. Focus is an important factor that affects the quality of the image. This study discusses the out-of-focus QR code image and aims to improve the recognition of the conte...

  1. Chaotic Synchronization with Filter Based on Wavelet Transformation

    Institute of Scientific and Technical Information of China (English)

    XiaoanZHOU; JunfengLAN; 等

    1999-01-01

    A kind of chaotic synchronization method is presented in the paper,In the transmitter,part signals are transformed by wavelet and the detail information is removed.In the receiver.the component with low frequency is reconstructed and discrete feedback is used,we show that synchronization of two identical structure chaotic systems is attained.The effect of feedback on chaotic synchronization is discussed.Using the synchronous method,the transmitting signal is transported in compressible way system resource is saved,the component with high frequency is filtered and the effect of disturbance on synchronization is reduced.The synchronization method is illustrated by numerical simulation experiment.

  2. An Online Banking System Based on Quantum Cryptography Communication

    Science.gov (United States)

    Zhou, Ri-gui; Li, Wei; Huan, Tian-tian; Shen, Chen-yi; Li, Hai-sheng

    2014-07-01

    In this paper, an online banking system has been built. Based on quantum cryptography communication, this system is proved unconditional secure. Two sets of GHZ states are applied, which can ensure the safety of purchase and payment, respectively. In another word, three trading participants in each triplet state group form an interdependent and interactive relationship. In the meantime, trading authorization and blind signature is introduced by means of controllable quantum teleportation. Thus, an effective monitor is practiced on the premise that the privacy of trading partners is guaranteed. If there is a dispute or deceptive behavior, the system will find out the deceiver immediately according to the relationship mentioned above.

  3. A online credit evaluation method based on AHP and SPA

    Science.gov (United States)

    Xu, Yingtao; Zhang, Ying

    2009-07-01

    Online credit evaluation is the foundation for the establishment of trust and for the management of risk between buyers and sellers in e-commerce. In this paper, a new credit evaluation method based on the analytic hierarchy process (AHP) and the set pair analysis (SPA) is presented to determine the credibility of the electronic commerce participants. It solves some of the drawbacks found in classical credit evaluation methods and broadens the scope of current approaches. Both qualitative and quantitative indicators are considered in the proposed method, then a overall credit score is achieved from the optimal perspective. In the end, a case analysis of China Garment Network is provided for illustrative purposes.

  4. Network-based approach to online cursive script recognition.

    Science.gov (United States)

    Sin, B K; Ha, J Y; Oh, S C; Kim, J H

    1999-01-01

    The idea of combining the network of HMMs and the dynamic programming-based search is highly relevant to online handwriting recognition. The word model of HMM network can be systematically constructed by concatenating letter and ligature HMM's while sharing common ones. Character recognition in such a network can be defined as the task of best aligning a given input sequence to the best path in the network. One distinguishing feature of the approach is that letter segmentation is obtained simultaneously with recognition but no extra computation is required.

  5. Stability Analysis and Active Damping for LLCL-filter-Based Grid-Connected Inverters

    DEFF Research Database (Denmark)

    Huang, Min; Wang, Xiongfei; Loh, Poh Chiang

    2015-01-01

    to use either passive or active damping methods. This paper analyzes the stability of the LLCL-filter based grid-connected inverter and identifies a critical resonant frequency for the LLCL-filter when sampling and transport delays are considered. In a high resonant frequency region the active damping...... is not required but in a low resonant frequency region the active damping is necessary. The basic LLCL resonance damping properties of different feedback states based on a notch filter concept are also studied. Then an active damping method which is using the capacitor current feedback for LLCL......-filter is introduced. Based on this active damping method, a design procedure for the controller is given. Last, both simulation and experimental results are provided to validate the theoretical analysis of this paper....

  6. Design Intelligent Model base Online Tuning Methodology for Nonlinear System

    Directory of Open Access Journals (Sweden)

    Ali Roshanzamir

    2014-04-01

    Full Text Available In various dynamic parameters systems that need to be training on-line adaptive control methodology is used. In this paper fuzzy model-base adaptive methodology is used to tune the linear Proportional Integral Derivative (PID controller. The main objectives in any systems are; stability, robust and reliability. However PID controller is used in many applications but it has many challenges to control of continuum robot. To solve these problems nonlinear adaptive methodology based on model base fuzzy logic is used. This research is used to reduce or eliminate the PID controller problems based on model reference fuzzy logic theory to control of flexible robot manipulator system and testing of the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.

  7. Architecture for knowledge-based and federated search of online clinical evidence.

    Science.gov (United States)

    Coiera, Enrico; Walther, Martin; Nguyen, Ken; Lovell, Nigel H

    2005-10-24

    It is increasingly difficult for clinicians to keep up-to-date with the rapidly growing biomedical literature. Online evidence retrieval methods are now seen as a core tool to support evidence-based health practice. However, standard search engine technology is not designed to manage the many different types of evidence sources that are available or to handle the very different information needs of various clinical groups, who often work in widely different settings. The objectives of this paper are (1) to describe the design considerations and system architecture of a wrapper-mediator approach to federate search system design, including the use of knowledge-based, meta-search filters, and (2) to analyze the implications of system design choices on performance measurements. A trial was performed to evaluate the technical performance of a federated evidence retrieval system, which provided access to eight distinct online resources, including e-journals, PubMed, and electronic guidelines. The Quick Clinical system architecture utilized a universal query language to reformulate queries internally and utilized meta-search filters to optimize search strategies across resources. We recruited 227 family physicians from across Australia who used the system to retrieve evidence in a routine clinical setting over a 4-week period. The total search time for a query was recorded, along with the duration of individual queries sent to different online resources. Clinicians performed 1662 searches over the trial. The average search duration was 4.9 +/- 3.2 s (N = 1662 searches). Mean search duration to the individual sources was between 0.05 s and 4.55 s. Average system time (ie, system overhead) was 0.12 s. The relatively small system overhead compared to the average time it takes to perform a search for an individual source shows that the system achieves a good trade-off between performance and reliability. Furthermore, despite the additional effort required to incorporate the

  8. Online approach to feature interaction problems in middleware based system

    Institute of Scientific and Technical Information of China (English)

    HUANG Gang; LIU XuanZhe; MEI Hong

    2008-01-01

    As a popular infrastructure for distributed systems running on the Internet, middle-ware has to support much more diverse and complex interactions for coping with the drastically increasing demand on information technology and the extremely open and dynamic nature of the Internet. These supporting mechanisms facilitate the development, deployment, and integration of distributed systems, as well as increase the occasions for distributed systems to interact in an undesired way. The undesired interactions may cause serious problems, such as quality violation, function loss, and even system crash. In this paper, the problem is studied from the perspective of the feature interaction problem (FIP) in telecom, and an online ap-proach to the detection and solution on runtime systems is proposed. Based on a classification of middleware enabled interactions, the existence of FIP in middle-ware based systems is illustrated by four real cases and a conceptual comparison between middleware based systems and telecom systems. After that, runtime soft-ware architecture is employed to facilitate the online detection and solution of FIP. The approach is demonstrated on J2EE (Java 2 Platform Enterprise Edition) and applied to detect and resolve all of the four real cases.

  9. Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

    Science.gov (United States)

    Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

    2012-01-01

    This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

  10. Analysis and implementation of a structural vibration control algorithm based on an IIR adaptive filter

    Science.gov (United States)

    Huang, Quanzhen; Luo, Jun; Li, Hengyu; Wang, Xiaohua

    2013-08-01

    With the wide application of large-scale flexible structures in spacecraft, vibration control problems in these structures have become important design issues. The filtered-X least mean square (FXLMS) algorithm is the most popular one in current active vibration control using adaptive filtering. It assumes that the source of interference can be measured and the interference source is considered as the reference signal input to the controller. However, in the actual control system, this assumption is not accurate, because it does not consider the impact of the reference signal on the output feedback signal. In this paper, an adaptive vibration active control algorithm based on an infinite impulse response (IIR) filter structure (FULMS, filtered-U least mean square) is proposed. The algorithm is based on an FXLMS algorithm framework, which replaces the finite impulse response (FIR) filter with an IIR filter. This paper focuses on the structural design of the controller, the process of the FULMS filtering control method, the design of the experimental model object, and the experimental platform construction for the entire control system. The comparison of the FXLMS algorithm with FULMS is theoretically analyzed and experimentally validated. The results show that the FULMS algorithm converges faster and controls better. The design of the FULMS controller is feasible and effective and has greater value in practical applications of aerospace engineering.

  11. New Collaborative Filtering Algorithms Based on SVD++ and Differential Privacy

    Directory of Open Access Journals (Sweden)

    Zhengzheng Xian

    2017-01-01

    Full Text Available Collaborative filtering technology has been widely used in the recommender system, and its implementation is supported by the large amount of real and reliable user data from the big-data era. However, with the increase of the users’ information-security awareness, these data are reduced or the quality of the data becomes worse. Singular Value Decomposition (SVD is one of the common matrix factorization methods used in collaborative filtering, which introduces the bias information of users and items and is realized by using algebraic feature extraction. The derivative model SVD++ of SVD achieves better predictive accuracy due to the addition of implicit feedback information. Differential privacy is defined very strictly and can be proved, which has become an effective measure to solve the problem of attackers indirectly deducing the personal privacy information by using background knowledge. In this paper, differential privacy is applied to the SVD++ model through three approaches: gradient perturbation, objective-function perturbation, and output perturbation. Through theoretical derivation and experimental verification, the new algorithms proposed can better protect the privacy of the original data on the basis of ensuring the predictive accuracy. In addition, an effective scheme is given that can measure the privacy protection strength and predictive accuracy, and a reasonable range for selection of the differential privacy parameter is provided.

  12. Filter Based Interference Mitigation in Multi Band-OFDM

    Directory of Open Access Journals (Sweden)

    Avila J.

    2014-02-01

    Full Text Available This study aims at to mitigate the interference between the primary user and secondary user in the wireless environment. This becomes necessary task because with the growing demand for bandwidth for wireless connectivity, it has become essential to come up with innovative solutions to tackle the demand. Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM offers a compelling answer for higher bandwidth and data rate requirements. The performance of multi band OFDM has been tarnished by narrow band interference due to the existence of primary users in the UWB spectrum. This occurs due to the leakage of spectral interference power. Despite the fact that Multiband OFDM has the inherent capability to mitigate the interference, independent mitigation techniques become necessary when the interference level is too high. In this study, interference mitigation is carried out by filtering action at the receiver. Results of simulation are compared to analyze the performance of the filters. Further steps have been taken out to enhance the performance of multiband OFDM system which in turn will be helpful in mitigating the interference.

  13. Multimodal Degradation Prognostics Based on Switching Kalman Filter Ensemble.

    Science.gov (United States)

    Lim, Pin; Goh, Chi Keong; Tan, Kay Chen; Dutta, Partha

    2017-01-01

    For accurate prognostics, users have to determine the current health of the system and predict future degradation pattern of the system. An increasingly popular approach toward tackling prognostic problems involves the use of switching models to represent various degradation phases, which the system undergoes. Such approaches have the advantage of determining the exact degradation phase of the system and being able to handle nonlinear degradation models through piecewise linear approximation. However, limitations of such existing methods include, limited applicability due to the discretization of predicted remaining useful life, insufficient robustness due to the use of single models and others. This paper circumvents these limitations by proposing a hybrid of ensemble methods with switching methods. The proposed method first implements a switching Kalman filter (SKF) to classify between various linear degradation phases, then predict the future propagation of fault dimension using appropriate Kalman filters for each phase. This proposed method achieves both continuous and discrete prediction values representing the remaining life and degradation phase of the system, respectively. The proposed framework is shown via a case study on benchmark simulated aeroengine data sets. The evaluation of the proposed framework shows that the proposed method achieves better accuracy and robustness against noise compared with other methods reported in the literature. The results also indicate the effectiveness of the SKF in detecting the switching point between various degradation modes.

  14. Design Considerations for Today's Online Learners: A Study of Personalized, Relationship-Based Social Awareness Information

    Science.gov (United States)

    Heo, Misook

    2009-01-01

    This article examined online learners' preferences in personalized, relationship-based social awareness information sharing in course management systems. Three hundred seventy-seven online learners' willingness to share social awareness information was measured through a national survey. Results indicated that today's online learners are open…

  15. Creating Fee-Based Online Services: A New Role for Academic Librarians.

    Science.gov (United States)

    Trehub, Aaron

    1999-01-01

    Discussion of the impact of the Internet on libraries focuses on librarians as creators and marketers of new online services. Describes two fee-based online services at the University of Illinois at Urbana-Champaign and concludes that academic libraries have the ability to create new online services, especially reference services. (Author/LRW)

  16. Student Satisfaction with Blended and Online Courses Based on Personality Type

    Science.gov (United States)

    Bolliger, Doris U.; Erichsen, Elizabeth Anne

    2013-01-01

    The purpose of the study was to investigate differences in perceived student satisfaction in blended and online learning environments based on personality type. A total of 72 graduate students enrolled in blended and online courses at two research universities in the United States completed an abbreviated online version of the Myers-Briggs Type…

  17. LLCL-Filter Based Single-Phase Grid-Tied Aalborg Inverter

    DEFF Research Database (Denmark)

    Wu, Weimin; Feng, Shuangshuang; Ji, Junhao

    2014-01-01

    The Aalborg Inverter is a new type of high efficient DC/AC grid-tied inverter, where the input DC voltage can vary in a wide range. Compared with the LCL-filter, the LLCL-filter can save the total inductance for the conventional voltage source inverter. In this paper, an LLCL-filter based Aalborg...... Inverter is proposed and its character is illustrated through the small signal analysis in both “Buck” and “Buck-Boost” mode. From the modeling, it can be seen that the resonant inductor in the capacitor loop has not brought extra control difficulties, whereas more inductance in the power loop can be saved...

  18. Graphene-based tunable terahertz filter with rectangular ring resonator containing double narrow gaps

    Science.gov (United States)

    Su, Wei; Chen, Bingyan

    2017-09-01

    A plasmonic band-pass filter based on graphene rectangular ring resonator with double narrow gaps is proposed and numerically investigated by finite-difference time-domain (FDTD) simulations. For the filter with or without gaps, the resonant frequencies can be effectively adjusted by changing the width of the graphene nanoribbon, the coupling distance and chemical potential of graphene. In addition, by introducing narrow gaps in the rectangular ring resonators, it shows the single frequency filtering effect. Moreover, the structure also shows high sensitivity for different surrounding mediums. This work provides a novel method for designing all-optical integrated components in optical communication.

  19. Tunable orbital angular momentum mode filter based on optical geometric transformation.

    Science.gov (United States)

    Huang, Hao; Ren, Yongxiong; Xie, Guodong; Yan, Yan; Yue, Yang; Ahmed, Nisar; Lavery, Martin P J; Padgett, Miles J; Dolinar, Sam; Tur, Moshe; Willner, Alan E

    2014-03-15

    We present a tunable mode filter for spatially multiplexed laser beams carrying orbital angular momentum (OAM). The filter comprises an optical geometric transformation-based OAM mode sorter and a spatial light modulator (SLM). The programmable SLM can selectively control the passing/blocking of each input OAM beam. We experimentally demonstrate tunable filtering of one or multiple OAM modes from four multiplexed input OAM modes with vortex charge of ℓ=-9, -4, +4, and +9. The measured output power suppression ratio of the propagated modes to the blocked modes exceeds 14.5 dB.

  20. Bandwidth and wavelength-tunable optical bandpass filter based on silicon microring-MZI structure

    DEFF Research Database (Denmark)

    Ding, Yunhong; Pu, Minhao; Liu, Liu

    2011-01-01

    A novel and simple bandwidth and wavelength-tunable optical bandpass filter based on silicon microrings in a Mach-Zehnder interferometer (MZI) structure is proposed and demonstrated. In this filter design, the drop transmissions of two microring resonators are combined to provide the desired...... tunability. A detailed analysis and the design of the device are presented. The shape factor and extinction ratio of the filter are optimized by thermally controlling the phase difference between the two arms of the MZI. Simultaneous bandwidth and wavelength tunability with in-band ripple control...

  1. Ultrafast all-optical clock recovery based on phase-only linear optical filtering

    DEFF Research Database (Denmark)

    Maram, Reza; Kong, Deming; Galili, Michael

    2014-01-01

    We report on a novel, efficient technique for all-optical clock recovery from RZ-OOK data signals based on spectral phase-only (all-pass) optical filtering. This technique significantly enhances both the recovered optical clock quality and energy efficiency in comparison with conventional amplitude...... optical filtering approaches using a Fabry-Perot filter. The proposed concept is validated through recovery of the optical clock from a 640 Gbit/s RZ-OOK data signal using a commercial linear optical waveshaper. (C) 2014 Optical Society of America...

  2. Graphene-based tunable terahertz filter with rectangular ring resonator containing double narrow gaps

    Indian Academy of Sciences (India)

    WEI SU; BINGYAN CHEN

    2017-09-01

    A plasmonic band-pass filter based on graphene rectangular ring resonator with double narrow gaps is proposed and numerically investigated by finite-difference time-domain (FDTD) simulations. For the filter with or without gaps, the resonant frequencies can be effectively adjusted by changing the width of the graphene nanoribbon, the coupling distance and chemical potential of graphene. In addition, by introducing narrow gaps in the rectangular ring resonators, it shows the single frequency filtering effect. Moreover, the structure also shows high sensitivity fordifferent surrounding mediums. This work provides a novel method for designing all-optical integrated components in optical communication.

  3. Design of the annular binary filters with super-resolution based on the genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    YU Qi-lei; LE Zi-chun; ZHU Hong-ying

    2006-01-01

    To improve the density of information storage,this paper introduces a kind of annular binary filters with super-resolution,Several of these filters have been designed based on the genetic algorithm,the simulations demonstrate that the transverse gain of the filters can reach the value of 1.37.Thus they can remarkably decrease the recording spot size,which is helpful to improve the density of information storage and to make the depth of focus longer,and therefore they can avoid the mistake caused by the small undulation of the optical disk in the process of recording/reading the information.

  4. A novel 3D wavelet based filter for visualizing features in noisy biological data

    Energy Technology Data Exchange (ETDEWEB)

    Moss, W C; Haase, S; Lyle, J M; Agard, D A; Sedat, J W

    2005-01-05

    We have developed a 3D wavelet-based filter for visualizing structural features in volumetric data. The only variable parameter is a characteristic linear size of the feature of interest. The filtered output contains only those regions that are correlated with the characteristic size, thus denoising the image. We demonstrate the use of the filter by applying it to 3D data from a variety of electron microscopy samples including low contrast vitreous ice cryogenic preparations, as well as 3D optical microscopy specimens.

  5. 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

    challenge the LCL-filter stability. Active damping by using a notch filter on the reference voltage for the modulator is simple to implement and does not require additional sensors. With the notch frequency tuned for the resonant frequency the voltage reference does not contain any component susceptible...... 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...... inductance variations it is proposed to estimate the resonance frequency by means of Fourier analysis. The Goertzel algorithm, instead of the FFT, is used to reduce the calculation and memory requirements. Thus, the proposed self-commissioning notch filter results robust and consumes little computational...

  6. Online traffic state estimation based on floating car data

    CERN Document Server

    Kesting, Arne

    2010-01-01

    Besides the traditional data collection by stationary detectors, recent advances in wireless and sensor technologies have promoted new potentials for a vehicle-based data collection and local dissemination of information. By means of microscopic traffic simulations we study the problem of online estimation of the current traffic situation based on floating car data. Our focus is on the estimation on the up- and downstream jam fronts determining the extension of traffic congestion. We study the impact of delayed information transmission by short-range communication via wireless LAN in contrast to instantaneous information transmission to the roadside units by means of mobile radio. The delayed information transmission leads to systematic estimation errors which cannot be compensated for by a higher percentage of probe vehicles. Additional flow measurements from stationary detectors allow for a model-based prediction which is effective for much lower floating car percentages than 1%.

  7. A Vondrak low pass filter for IMU sensor initial alignment on a disturbed base.

    Science.gov (United States)

    Li, Zengke; Wang, Jian; Gao, Jingxiang; Li, Binghao; Zhou, Feng

    2014-12-10

    The initial alignment of the Inertial Measurement Unit (IMU) is an important process of INS to determine the coordinate transformation matrix which is used in the integration of Global Positioning Systems (GPS) with Inertial Navigation Systems (INS). In this paper a novel alignment method for a disturbed base, such as a vehicle disturbed by wind outdoors, implemented with the aid of a Vondrak low pass filter, is proposed. The basic principle of initial alignment including coarse alignment and fine alignment is introduced first. The spectral analysis is processed to compare the differences between the characteristic error of INS force observation on a stationary base and on disturbed bases. In order to reduce the high frequency noise in the force observation more accurately and more easily, a Vondrak low pass filter is constructed based on the spectral analysis result. The genetic algorithms method is introduced to choose the smoothing factor in the Vondrak filter and the corresponding objective condition is built. The architecture of the proposed alignment method with the Vondrak low pass filter is shown. Furthermore, simulated experiments and actual experiments were performed to validate the new algorithm. The results indicate that, compared with the conventional alignment method, the Vondrak filter could eliminate the high frequency noise in the force observation and the proposed alignment method could improve the attitude accuracy. At the same time, only one parameter needs to be set, which makes the proposed method easier to implement than other low-pass filter methods.

  8. A Vondrak Low Pass Filter for IMU Sensor Initial Alignment on a Disturbed Base

    Directory of Open Access Journals (Sweden)

    Zengke Li

    2014-12-01

    Full Text Available The initial alignment of the Inertial Measurement Unit (IMU is an important process of INS to determine the coordinate transformation matrix which is used in the integration of Global Positioning Systems (GPS with Inertial Navigation Systems (INS. In this paper a novel alignment method for a disturbed base, such as a vehicle disturbed by wind outdoors, implemented with the aid of a Vondrak low pass filter, is proposed. The basic principle of initial alignment including coarse alignment and fine alignment is introduced first. The spectral analysis is processed to compare the differences between the characteristic error of INS force observation on a stationary base and on disturbed bases. In order to reduce the high frequency noise in the force observation more accurately and more easily, a Vondrak low pass filter is constructed based on the spectral analysis result. The genetic algorithms method is introduced to choose the smoothing factor in the Vondrak filter and the corresponding objective condition is built. The architecture of the proposed alignment method with the Vondrak low pass filter is shown. Furthermore, simulated experiments and actual experiments were performed to validate the new algorithm. The results indicate that, compared with the conventional alignment method, the Vondrak filter could eliminate the high frequency noise in the force observation and the proposed alignment method could improve the attitude accuracy. At the same time, only one parameter needs to be set, which makes the proposed method easier to implement than other low-pass filter methods.

  9. Effect of particle-fiber friction coefficient on ultrafine aerosol particles clogging in nanofiber based filter

    Science.gov (United States)

    Sambaer, Wannes; Zatloukal, Martin; Kimmer, Dusan

    2013-04-01

    Realistic SEM image based 3D filter model considering transition/free molecular flow regime, Brownian diffusion, aerodynamic slip, particle-fiber and particle-particle interactions together with a novel Euclidian distance map based methodology for the pressure drop calculation has been utilized for a polyurethane nanofiber based filter prepared via electrospinning process in order to more deeply understand the effect of particle-fiber friction coefficient on filter clogging and basic filter characteristics. Based on the performed theoretical analysis, it has been revealed that the increase in the fiber-particle friction coefficient causes, firstly, more weaker particle penetration in the filter, creation of dense top layers and generation of higher pressure drop (surface filtration) in comparison with lower particle-fiber friction coefficient filter for which deeper particle penetration takes place (depth filtration), secondly, higher filtration efficiency, thirdly, higher quality factor and finally, higher quality factor sensitivity to the increased collected particle mass. Moreover, it has been revealed that even if the particle-fiber friction coefficient is different, the cake morphology is very similar.

  10. Optimization of spectrally selective Si/SiO2 based filters for thermophotovoltaic devices

    Science.gov (United States)

    Khosroshahi, Farhad Kazemi; Ertürk, Hakan; Pınar Mengüç, M.

    2017-08-01

    Design of a spectrally selective filter based on one-dimensional Si/SiO2 layers is considered for improved performance of thermo-photovoltaic devices. Spectrally selective filters transmit only the convertible radiation from the emitter as non-convertible radiation leads to a reduction in cell efficiency due to heating. The presented Si/SiO2 based filter concept reflects the major part of the undesired range back to the emitter to minimize energy required for the process and it is adaptable to different types of cells and emitters with different temperatures since its cut-off wavelength can be tuned. While this study mainly focuses on InGaSb based thermo-photovoltaic cell, Si, GaSb, and Ga0.78In0.22As0.19Sb0.81 based cells are also examined. Transmittance of the structure is predicted by rigorous coupled wave approach. Genetic algorithm, which is a global optimization method, is used to find the best possible filter structure by considering the overall efficiency as an objective function that is maximized. The simulations show that significant enhancement in the overall system and device efficiency is possible by using such filters with TPV devices. The methodology described in this paper allows for an improved filter design procedure for selected applications.

  11. Bloom Filter-Based Secure Data Forwarding in Large-Scale Cyber-Physical Systems

    Directory of Open Access Journals (Sweden)

    Siyu Lin

    2015-01-01

    Full Text Available Cyber-physical systems (CPSs connect with the physical world via communication networks, which significantly increases security risks of CPSs. To secure the sensitive data, secure forwarding is an essential component of CPSs. However, CPSs require high dimensional multiattribute and multilevel security requirements due to the significantly increased system scale and diversity, and hence impose high demand on the secure forwarding information query and storage. To tackle these challenges, we propose a practical secure data forwarding scheme for CPSs. Considering the limited storage capability and computational power of entities, we adopt bloom filter to store the secure forwarding information for each entity, which can achieve well balance between the storage consumption and query delay. Furthermore, a novel link-based bloom filter construction method is designed to reduce false positive rate during bloom filter construction. Finally, the effects of false positive rate on the performance of bloom filter-based secure forwarding with different routing policies are discussed.

  12. Moving Average Filter-Based Phase-Locked Loops: Performance Analysis and Design Guidelines

    DEFF Research Database (Denmark)

    Golestan, Saeed; Ramezani, Malek; Guerrero, Josep M.

    2014-01-01

    The phase locked-loops (PLLs) are probably the most widely used synchronization technique in grid-connected applications. The main challenge associated with the PLLs is how to precisely and fast estimate the phase and frequency when the grid voltage is unbalanced and/or distorted. To overcome...... this challenge, incorporating moving average filter(s) (MAF) into the PLL structure has been proposed in some recent literature. A MAF is a linear-phase finite impulse response filter which can act as an ideal low-pass filter, if certain conditions hold. The main aim of this paper is to present the control...... design guidelines for a typical MAF-based PLL. The paper starts with the general description of MAFs. The main challenge associated with using the MAFs is then explained, and its possible solutions are discussed. The paper then proceeds with a brief overview of the different MAF-based PLLs. In each case...

  13. Noise Reduction in Breath Sound Files Using Wavelet Transform Based Filter

    Science.gov (United States)

    Syahputra, M. F.; Situmeang, S. I. G.; Rahmat, R. F.; Budiarto, R.

    2017-04-01

    The development of science and technology in the field of healthcare increasingly provides convenience in diagnosing respiratory system problem. Recording the breath sounds is one example of these developments. Breath sounds are recorded using a digital stethoscope, and then stored in a file with sound format. This breath sounds will be analyzed by health practitioners to diagnose the symptoms of disease or illness. However, the breath sounds is not free from interference signals. Therefore, noise filter or signal interference reduction system is required so that breath sounds component which contains information signal can be clarified. In this study, we designed a filter called a wavelet transform based filter. The filter that is designed in this study is using Daubechies wavelet with four wavelet transform coefficients. Based on the testing of the ten types of breath sounds data, the data is obtained in the largest SNRdB bronchial for 74.3685 decibels.

  14. Research on the method of information system risk state estimation based on clustering particle filter

    Directory of Open Access Journals (Sweden)

    Cui Jia

    2017-05-01

    Full Text Available With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  15. Application of Wavelet-based Active Power Filter in Accelerator Magnet Power Supply

    CERN Document Server

    Xiaoling, Guo

    2013-01-01

    As modern accelerators demand excellent stability to magnet power supply (PS), it is necessary to decrease harmonic currents passing magnets. Aim at depressing rappel current from PS in Beijing electron-positron collider II, a wavelet-based active power filter (APF) is proposed in this paper. APF is an effective device to improve the quality of currents. As a countermeasure to these harmonic currents, the APF circuit generates a harmonic current, countervailing harmonic current from PS. An active power filter based on wavelet transform is proposed in this paper. Discrete wavelet transform is used to analyze the harmonic components in supply current, and active power filter circuit works according to the analysis results. At end of this paper, the simulation and experiment results are given to prove the effect of the mentioned Active power filter.

  16. Nonlinear Diffusion Filtering of the GOCE-Based Satellite-Only Mean Dynamic Topography

    Science.gov (United States)

    Cunderlik, Robert; Mikula, Karol

    2015-03-01

    The paper presents nonlinear diffusion filtering of the GOCE-based satellite-only mean dynamic topography (MDT). Our approach is based on a numerical solution to the nonlinear diffusion equation defined on the discretized Earth’s surface using the regularized surface Perona-Malik Model. For its numerical discretization we use a surface finite volume method. A key idea is that the diffusivity coefficient depends on the edge detector. It allows effectively reduce the stripping noise while preserve important gradients in filtered data. Numerical experiments present nonlinear filtering of the geopotential evaluated from the GO_CONS_GCF_2_ DIR_R5 model on the DTU13 mean sea surface. After filtering the geopotential is transformed into the MDT.

  17. Passive Target Tracking in Non-cooperative Radar System Based on Particle Filtering

    Institute of Scientific and Technical Information of China (English)

    LI Shuo; TAO Ran

    2006-01-01

    We propose a target tracking method based on particle filtering(PF) to solve the nonlinear non-Gaussian target-tracking problem in the bistatic radar systems using external radiation sources. Traditional nonlinear state estimation method is extended Kalman filtering (EKF), which is to do the first level Taylor series extension. It will cause an inaccuracy or even a scatter estimation result on condition that there is either a highly nonlinear target or a large noise square-error. Besides, Kalman filtering is the optimal resolution under a Gaussian noise assumption, and is not suitable to the non-Gaussian condition. PF is a sort of statistic filtering based on Monte Carlo simulation that is using some random samples (particles) to simulate the posterior probability density of system random variables. This method can be used in any nonlinear random system. It can be concluded through simulation that PF can achieve higher accuracy than the traditional EKF.

  18. Research on the method of information system risk state estimation based on clustering particle filter

    Science.gov (United States)

    Cui, Jia; Hong, Bei; Jiang, Xuepeng; Chen, Qinghua

    2017-05-01

    With the purpose of reinforcing correlation analysis of risk assessment threat factors, a dynamic assessment method of safety risks based on particle filtering is proposed, which takes threat analysis as the core. Based on the risk assessment standards, the method selects threat indicates, applies a particle filtering algorithm to calculate influencing weight of threat indications, and confirms information system risk levels by combining with state estimation theory. In order to improve the calculating efficiency of the particle filtering algorithm, the k-means cluster algorithm is introduced to the particle filtering algorithm. By clustering all particles, the author regards centroid as the representative to operate, so as to reduce calculated amount. The empirical experience indicates that the method can embody the relation of mutual dependence and influence in risk elements reasonably. Under the circumstance of limited information, it provides the scientific basis on fabricating a risk management control strategy.

  19. Study on microwave photonic filters based on lasers and dispersive fiber

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A general theoretical model for microwave photonic filters based on multi-wavelength light source and dispersive media is summarized and presented, and is applied to the analysis of double-laser-based microwave photonic notch filters' performance.The different influences of the double-sideband(DSB) modulation and the single-sideband(SSB) modulation are demonstrated and explained theoretically. Furthermore, the impact of different factors, such as frequency spacing, 3dB bandwidth and the spectrum amplitude mismatch on the performance of the microwave photonic notch filters are also studied. The numerical simulation results are in good agreement with predictions, and could be beneficial for future optimization of microwave photonic filters.

  20. A Comparative Study of Empirical Mode Decomposition-Based Filtering for Impact Signal

    Directory of Open Access Journals (Sweden)

    Liwei Zhan

    2016-12-01

    Full Text Available The Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN has been used to propose a new method for filtering time series originating from nonlinear systems. The filtering method is based on fuzzy entropy and a new waveform. A new waveform is defined wherein Intrinsic Mode Functions (IMFs—which are obtained by CEEMDAN algorithm—are firstly sorted in ascending order (the sorted IMFs is symmetric about center point, because at any point, the mean value of the envelope line defined by the local maxima and the local minima is zero, and the energy of the sorted IMFs are calculated, respectively. Finally, the new waveform with axial symmetry can be obtained. The complexity of the new waveform can be quantified by fuzzy entropy. The relevant modes (noisy signal modes and useful signal modes can be identified by the difference between the fuzzy entropy of the new waveform and the next adjacent new waveform. To evaluate the filter performance, CEEMDAN and sample entropy, Ensemble Empirical Mode Decomposition (EEMD and fuzzy entropy, and EEMD and sample entropy were used to filter the synthesizing signals with various levels of input signal-to-noise ratio (SNRin. In particular, this approach is successful in filtering impact signal. The results of the filtering are evaluated by a de-trended fluctuation analysis (DFA algorithm, revised mean square error (RMSE, and revised signal-to-noise ratio (RSNR, respectively. The filtering results of simulated and impact signal show that the filtering method based on CEEMDAN and fuzzy entropy outperforms other signal filtering methods.

  1. Prediction of Lumen Output and Chromaticity Shift in LEDs Using Kalman Filter and Extended Kalman Filter Based Models

    Energy Technology Data Exchange (ETDEWEB)

    Lall, Pradeep; Wei, Junchao; Davis, J Lynn

    2014-06-24

    Abstract— Solid-state lighting (SSL) luminaires containing light emitting diodes (LEDs) have the potential of seeing excessive temperatures when being transported across country or being stored in non-climate controlled warehouses. They are also being used in outdoor applications in desert environments that see little or no humidity but will experience extremely high temperatures during the day. This makes it important to increase our understanding of what effects high temperature exposure for a prolonged period of time will have on the usability and survivability of these devices. Traditional light sources “burn out” at end-of-life. For an incandescent bulb, the lamp life is defined by B50 life. However, the LEDs have no filament to “burn”. The LEDs continually degrade and the light output decreases eventually below useful levels causing failure. Presently, the TM-21 test standard is used to predict the L70 life of LEDs from LM-80 test data. Several failure mechanisms may be active in a LED at a single time causing lumen depreciation. The underlying TM-21 Model may not capture the failure physics in presence of multiple failure mechanisms. Correlation of lumen maintenance with underlying physics of degradation at system-level is needed. In this paper, Kalman Filter (KF) and Extended Kalman Filters (EKF) have been used to develop a 70-percent Lumen Maintenance Life Prediction Model for LEDs used in SSL luminaires. Ten-thousand hour LM-80 test data for various LEDs have been used for model development. System state at each future time has been computed based on the state space at preceding time step, system dynamics matrix, control vector, control matrix, measurement matrix, measured vector, process noise and measurement noise. The future state of the lumen depreciation has been estimated based on a second order Kalman Filter model and a Bayesian Framework. Life prediction of L70 life for the LEDs used in SSL luminaires from KF and EKF based models have

  2. Fast Implementation of Matched Filter Based Automatic Alignment Image Processing

    Energy Technology Data Exchange (ETDEWEB)

    Awwal, A S; Rice, K; Taha, T

    2008-04-02

    Video images of laser beams imprinted with distinguishable features are used for alignment of 192 laser beams at the National Ignition Facility (NIF). Algorithms designed to determine the position of these beams enable the control system to perform the task of alignment. Centroiding is a common approach used for determining the position of beams. However, real world beam images suffer from intensity fluctuation or other distortions which make such an approach susceptible to higher position measurement variability. Matched filtering used for identifying the beam position results in greater stability of position measurement compared to that obtained using the centroiding technique. However, this gain is achieved at the expense of extra processing time required for each beam image. In this work we explore the possibility of using a field programmable logic array (FPGA) to speed up these computations. The results indicate a performance improvement of 20 using the FPGA relative to a 3 GHz Pentium 4 processor.

  3. Content-Based Filtering for Video Sharing Social Networks

    CERN Document Server

    Valle, Eduardo; Luz, Antonio da; de Souza, Fillipe; Coelho, Marcelo; Araújo, Arnaldo

    2011-01-01

    In this paper we compare the use of several features in the task of content filtering for video social networks, a very challenging task, not only because the unwanted content is related to very high-level semantic concepts (e.g., pornography, violence, etc.) but also because videos from social networks are extremely assorted, preventing the use of constrained a priori information. We propose a simple method, able to combine diverse evidence, coming from different features and various video elements (entire video, shots, frames, keyframes, etc.). We evaluate our method in three social network applications, related to the detection of unwanted content - pornographic videos, violent videos, and videos posted to artificially manipulate popularity scores. Using challenging test databases, we show that this simple scheme is able to obtain good results, provided that adequate features are chosen. Moreover, we establish a representation using codebooks of spatiotemporal local descriptors as critical to the success o...

  4. Evaluation of new diesel particulate filters based on stabilized aluminium titanate; Untersuchung der Eigenschaften neuer Dieselpartikelfilter

    Energy Technology Data Exchange (ETDEWEB)

    Boger, T.; Rose, D.; Cutler, W.A. [Corning GmbH, Wiesbaden (Germany); Heibel, A.K.; Tennent, D.L. [Corning Incorporated Corning, New York (United States)

    2005-09-01

    A new generation of wall-flow diesel particulate filters based on an aluminium titanate composition has recently been developed by Corning, and marketed as the Corning Dura Trap AT filter. The new material combines extremely high resistance to thermal stresses with a high bulk heat capacity. In this article, the test results obtained with this new material in laboratory tests, engine bench experiments and on-road vehicle durability runs are presented and discussed. (orig.)

  5. 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.

  6. A tunable comb filter using single-mode/multimode/polarization-maintaining-fiber-based Sagnac fiber loop

    Institute of Scientific and Technical Information of China (English)

    Ruan Juan; Zhang Wei-Gang; Zhang Hao; Geng Peng-Cheng; Bai Zhi-Yong

    2013-01-01

    A novel tunable comb filter composed of a single-mode/multimode/polarization-maintaining-fiber-based Sagnac fiber loop is proposed and experimentally demonstrated.The filter tunability is achieved by rotating the polarization controller.The spectral shift is dependent on rotation direction and the position of the polarization controller.In addition,the adjustable range achieved by rotating the half-wave-plate polarization controller is twice higher than that of the quarter-wave-plate one.

  7. Multisensor Distributed Track Fusion AlgorithmBased on Strong Tracking Filter and Feedback Integration1)

    Institute of Scientific and Technical Information of China (English)

    YANGGuo-Sheng; WENCheng-Lin; TANMin

    2004-01-01

    A new multisensor distributed track fusion algorithm is put forward based on combiningthe feedback integration with the strong tracking Kalman filter. Firstly, an effective tracking gateis constructed by taking the intersection of the tracking gates formed before and after feedback.Secondly, on the basis of the constructed effective tracking gate, probabilistic data association andstrong tracking Kalman filter are combined to form the new multisensor distributed track fusionalgorithm. At last, simulation is performed on the original algorithm and the algorithm presented.

  8. Retinal Image Graph-Cut Segmentation Algorithm Using Multiscale Hessian-Enhancement-Based Nonlocal Mean Filter

    OpenAIRE

    Jian Zheng; Pei-Rong Lu; Dehui Xiang; Ya-Kang Dai; Zhao-Bang Liu; Duo-Jie Kuai; Hui Xue; Yue-Tao Yang

    2013-01-01

    We propose a new method to enhance and extract the retinal vessels. First, we employ a multiscale Hessian-based filter to compute the maximum response of vessel likeness function for each pixel. By this step, blood vessels of different widths are significantly enhanced. Then, we adopt a nonlocal mean filter to suppress the noise of enhanced image and maintain the vessel information at the same time. After that, a radial gradient symmetry transformation is adopted to suppress the nonvessel str...

  9. Directional Filter for SAR Images Based on Nonsubsampled Contourlet Transform and Immune Clonal Selection

    Institute of Scientific and Technical Information of China (English)

    Xiao-Hui Yang; Li-Cheng Jiao; Deng-Feng Li

    2009-01-01

    A directional filter algorithm for intensity synthetic aperture radar (SAR) image based on nonsubsampled contourlet transform (NSCT) and immune clonal selection (ICS) is presented. The proposed filter mainly focuses on exploiting different features of edges and noises by NSCT. Furthermore, ICS strategy is introduced to optimize threshold parameter and amplify parameter adaptively. Numerical experiments on real SAR images show that there are improvements in both visual effects and objective indexes.

  10. 2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA

    OpenAIRE

    Hafez, Samir F.; Selim, Mazen M.; Hala H. Zayed

    2015-01-01

    We present a new approach for face recognition system. The method is based on 2D face image features using subset of non-correlated and Orthogonal Gabor Filters instead of using the whole Gabor Filter Bank, then compressing the output feature vector using Linear Discriminant Analysis (LDA). The face image has been enhanced using multi stage image processing technique to normalize it and compensate for illumination variation. Experimental results show that the proposed system is effective for ...

  11. Filter-based multiscale entropy analysis of complex physiological time series.

    Science.gov (United States)

    Xu, Yuesheng; Zhao, Liang

    2013-08-01

    Multiscale entropy (MSE) has been widely and successfully used in analyzing the complexity of physiological time series. We reinterpret the averaging process in MSE as filtering a time series by a filter of a piecewise constant type. From this viewpoint, we introduce filter-based multiscale entropy (FME), which filters a time series to generate multiple frequency components, and then we compute the blockwise entropy of the resulting components. By choosing filters adapted to the feature of a given time series, FME is able to better capture its multiscale information and to provide more flexibility for studying its complexity. Motivated by the heart rate turbulence theory, which suggests that the human heartbeat interval time series can be described in piecewise linear patterns, we propose piecewise linear filter multiscale entropy (PLFME) for the complexity analysis of the time series. Numerical results from PLFME are more robust to data of various lengths than those from MSE. The numerical performance of the adaptive piecewise constant filter multiscale entropy without prior information is comparable to that of PLFME, whose design takes prior information into account.

  12. Steganalysis of content-adaptive JPEG steganography based on Gauss partial derivative filter bank

    Science.gov (United States)

    Zhang, Yi; Liu, Fenlin; Yang, Chunfang; Luo, Xiangyang; Song, Xiaofeng; Lu, Jicang

    2017-01-01

    A steganalysis feature extraction method based on Gauss partial derivative filter bank is proposed in this paper to improve the detection performance for content-adaptive JPEG steganography. Considering that the embedding changes of content-adaptive steganographic schemes are performed in the texture and edge regions, the proposed method generates filtered images comprising rich texture and edge information using Gauss partial derivative filter bank, and histograms of absolute values of filtered subimages are extracted as steganalysis features. Gauss partial derivative filter bank can represent texture and edge information in multiple orientations with less computation load than conventional methods and prevent redundancy in different filtered images. These two properties are beneficial in the extraction of low-complexity sensitive features. The results of experiments conducted on three selected modern JPEG steganographic schemes-uniform embedding distortion, JPEG universal wavelet relative distortion, and side-informed UNIWARD-indicate that the proposed feature set is superior to the prior art feature sets-discrete cosine transform residual, phase aware rich model, and Gabor filter residual.

  13. Low power, chip-based stimulated Brillouin scattering microwave photonic filter with ultrahigh selectivity

    CERN Document Server

    Marpaung, David; Pagani, Mattia; Pant, Ravi; Choi, Duk-Yong; Luther-Davies, Barry; Madden, Steve J; Eggleton, Benjamin J

    2014-01-01

    Highly selective and reconfigurable microwave filters are of great importance in radio-frequency signal processing. Microwave photonic (MWP) filters are of particular interest, as they offer flexible reconfiguration and an order of magnitude higher frequency tuning range than electronic filters. However, all MWP filters to date have been limited by trade-offs between key parameters such as tuning range, resolution, and suppression. This problem is exacerbated in the case of integrated MWP filters, blocking the path to compact, high performance filters. Here we show the first chip-based MWP band-stop filter with ultra-high suppression, high resolution in the MHz range, and 0-30 GHz frequency tuning. This record performance was achieved using an ultra-low Brillouin gain from a compact photonic chip and a novel approach of optical resonance-assisted RF signal cancellation. The results point to new ways of creating energy-efficient and reconfigurable integrated MWP signal processors for wireless communications an...

  14. Project Report: Reducing Color Rivalry in Imagery for Conjugated Multiple Bandpass Filter Based Stereo Endoscopy

    Science.gov (United States)

    Ream, Allen

    2011-01-01

    A pair of conjugated multiple bandpass filters (CMBF) can be used to create spatially separated pupils in a traditional lens and imaging sensor system allowing for the passive capture of stereo video. This method is especially useful for surgical endoscopy where smaller cameras are needed to provide ample room for manipulating tools while also granting improved visualizations of scene depth. The significant issue in this process is that, due to the complimentary nature of the filters, the colors seen through each filter do not match each other, and also differ from colors as seen under a white illumination source. A color correction model was implemented that included optimized filter selection, such that the degree of necessary post-processing correction was minimized, and a chromatic adaptation transformation that attempted to fix the imaged colors tristimulus indices based on the principle of color constancy. Due to fabrication constraints, only dual bandpass filters were feasible. The theoretical average color error after correction between these filters was still above the fusion limit meaning that rivalry conditions are possible during viewing. This error can be minimized further by designing the filters for a subset of colors corresponding to specific working environments.

  15. FPGA-Based Architecture for a Generalized Parallel 2-D MRI Filtering Algorithm

    Directory of Open Access Journals (Sweden)

    Sami Hasan

    2011-01-01

    Full Text Available Problem statement: Current Neuroimaging developments, in biological research and diagnostics, demand an edge-defined and noise-free MRI scans. Thus, this study presents a generalized parallel 2-D MRI filtering algorithm with their FPGA-based implementation in a single unified architecture. The parallel 2-D MRI filtering algorithms are Edge, Sobel X, Sobel Y, Sobel X-Y, Blur, Smooth, Sharpen, Gaussian and Beta (HYB. Then, the nine MRI image filtering algorithm, has empirically improved to generate enhanced MRI scans filtering results without significantly affecting the developed performance indices of high throughput and low power consumption at maximum operating frequency. Approach: The parallel 2-d MRI filtering algorithms are developed and FPGA implemented using Xilinx System Generator tool within the ISE 12.3 development suite. Two unified architectures are behaviorally developed, depending on the abstraction level of implementation. For performance indices comparison, two Virtex-6 FPGA boards, namely, xc6vlX240Tl-1lff1759 and xc6vlX130Tl-1lff1156 are behaviorally targeted. Results: The improved parallel 2-D filtering algorithms enhanced the filtered MRI scans to be edge-defined and noise free grayscale imaging. The single architecture is efficiently prototyped to achieve: high filtering performance of (11230 frames/second throughput for 64*64 MRI grayscale scan, minimum power consumption of 0.86 Watt with a junction temperature of 52°C and a maximum frequency of up to (230 MHz. Conclusion: The improved parallel MRI filtering algorithms which are developed as a single unified architecture provide visibility enhancement within the filtered MRI scan to aid the physician in detecting brain diseases, e.g., trauma or intracranial haemorrhage. The high filtering throughput is feasibly nominee the nine parallel MRI filtering algorithms for applications such as real-time MRI potential future applications. Future Work: a set of parallel 3-D f

  16. Arduino-based noise robust online heart-rate detection.

    Science.gov (United States)

    Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

    2017-04-01

    This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

  17. Design and manufacturing of band-rejection filters based on long period gratings for applications in next generation access networks

    Science.gov (United States)

    Dybka, Kamil; Śmietana, Bartosz; Szarniak, Przemysław; Dłubek, Michał

    2015-12-01

    An engineering tool for designing LPG-based filters is reported. Band-rejection filters for telecom applications have been designed and manufactured and an automated mass production technology has been developed. The technology utilizes single-shot LPG writing with a double CO2 laser beam. The paper discusses also the critical process parameters controlled to shape the spectral characteristics of manufactured filters.

  18. Iris image recognition wavelet filter-banks based iris feature extraction schemes

    CERN Document Server

    Rahulkar, Amol D

    2014-01-01

    This book provides the new results in wavelet filter banks based feature extraction, and the classifier in the field of iris image recognition. It provides the broad treatment on the design of separable, non-separable wavelets filter banks, and the classifier. The design techniques presented in the book are applied on iris image analysis for person authentication. This book also brings together the three strands of research (wavelets, iris image analysis, and classifier). It compares the performance of the presented techniques with state-of-the-art available schemes. This book contains the compilation of basic material on the design of wavelets that avoids reading many different books. Therefore, it provide an easier path for the new-comers, researchers to master the contents. In addition, the designed filter banks and classifier can also be effectively used than existing filter-banks in many signal processing applications like pattern classification, data-compression, watermarking, denoising etc.  that will...

  19. Silicon-based on-chip electrically tunable sidewall Bragg grating Fabry-Perot filter.

    Science.gov (United States)

    Zhang, Weifeng; Ehteshami, Nasrin; Liu, Weilin; Yao, Jianping

    2015-07-01

    We report the design, fabrication, and testing of a silicon-based on-chip electrically tunable sidewall Bragg grating Fabry-Perot filter. Spectral measurement shows that the filter has a narrow notch in reflection of approximately 46 pm, a Q-factor of 33,500, and an extinction ratio of 16.4 dB. DC measurement shows that the average central wavelength shift rates with forward and reverse bias are -1.15  nm/V and 4.2  pm/V, respectively. Due to strong light confinement in the Fabry-Perot cavity, the electro-optic frequency response shows that the filter has a 3-dB modulation bandwidth of ∼5.6  GHz. The performance of using the filter to perform modulation of a 3.5  Gb/s2(7)-1 nonreturn-to-zero pseudorandom binary sequence is evaluated.

  20. Optimization of optical filter using triple coupler ring resonators structure based on polyimide substrate

    Science.gov (United States)

    Mahmudin, D.; Estu, T. T.; Fathnan, A. A.; Maulana, Y. Y.; Daud, P.; Sugandhi, G.; Wijayanto, Y. N.

    2016-11-01

    Optical filter is very important components in WDM network. MRR is a basic structure to design the optical filter because of easy to design for improving its performance. This paper discusses an innovative structure of the MRR, which is Triple Coupler Ring Resonators (TCRR) for optical filter applications. Values of width between bus and ring and values of radius of the ring in the structure TCRR were analyzed and optimized for several variations for obtaining coupling coefficient values. Therefore, wide Free Spectral Range (FSR) and high crosstalk suppression bandwidth can be obtained. As results, at the optimized width of gap of 100 nm and the optimized radiation of 8 μm, FSR of 2.85 THz and crosstalk suppression bandwidth of 60 GHz were achieved. Based on the results, this structure can be used for filtering optical signals in optical fiber communication.

  1. Gas refractometry based on an all-fiber spatial optical filter.

    Science.gov (United States)

    Silva, Susana; Coelho, L; André, R M; Frazão, O

    2012-08-15

    A spatial optical filter based on splice misalignment between optical fibers with different diameters is proposed for gas refractometry. The sensing head is formed by a 2 mm long optical fiber with 50 μm diameter that is spliced with a strong misalignment between two single-mode fibers (SMF28) and interrogated in transmission. The misalignment causes a Fabry-Perot behavior along the reduced-size fiber and depending on the lead-out SMF28 position, it is possible to obtain different spectral responses, namely, bandpass or band-rejection filters. It is shown that the spatial filter device is highly sensitive to refractive index changes on a nitrogen environment by means of the gas pressure variation. A maximum sensitivity of -1390 nm/RIU for the bandpass filter was achieved. Both devices have shown similar temperature responses with an average sensitivity of 25.7 pm/°C.

  2. Stability analysis and active damping for LLCL-filter based grid-connected inverters

    DEFF Research Database (Denmark)

    Huang, Min; Blaabjerg, Frede; Loh, Poh Chiang

    2014-01-01

    A higher order passive power filter (LLCL-filter) for the grid-tied inverter is becoming attractive for the industrial applications due to the possibility to reduce the cost of the copper and the magnetic material. To avoid the well-known stability problems of the LLCL-filter it is requested to use...... either passive or active damping methods. This paper analyzes the stability when damping is required and when damping is not necessary considering sampling and transport delay. Basic LLCL resonance damping properties of different feedback states are also studied. Then an active damping method which...... is using the capacitor current feedback for LLCL-filter is introduced. Based on this method, a design procedure for the control method is given. Last, both simulation and experimental results are provided to validate the theoretical analysis of this paper....

  3. Design of Maximally Flat FIR Filters Based on Explicit Formulas Combined with Optimization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A maximally flat FIR filter design method based on explicit formulas combined with simulated annealing and random search was presented. Utilizing the explicit formulas to calculate the initial values, the finite-word-length FIR filter design problem was converted into optimization of the filter coefficients. An optimization method combined with local discrete random search and simulated annealing was proposed, with the result of optimum solution in the sense of Chebyshev approximation. The proposed method can simplify the design process of FIR filter and reduce the calculation burden. The simulation result indicates that the proposed method is superior to the traditional round off method and can reduce the value of the objective function to 41%-74%.

  4. Image Filtering Based on Multi-Criterion of Boundary Point Judgment

    Institute of Scientific and Technical Information of China (English)

    JINGXiaojun; FUYali; HUOXiuli; JIANGMei

    2005-01-01

    A fusion filtering algorithm based on D-S theory of evidence is proposed to combat shortcomings of linear and nonlinear filtering techniques. Firstly it analy zeshow and to what degree D-S theory of evidence can result in limitations, and then takes measures to annul dependencies among evidences and adaptively assigns contradictory information to conflict-relevant pixels, thus improving the combination criteria of D-S theory of evidence as well as increasing its fusion capability. On this foundation, and for the disadvantage in hybrid filters of great risk of misjudging image edges, lower reliability, and bad error tolerance, we add a multiple sub-source adjudging criteria, and utilize modified combination criteria in D-S theory of evidence to perform fusion judgments. Subsequent experimental resuits show the validity of the algorithm, thus providing a new way to improve image filtering techniques.

  5. Two dimensional tunable photonic crystal defect based drop filter at communication wavelength

    Science.gov (United States)

    D'souza, Nirmala Maria; Mathew, Vincent

    2017-07-01

    We propose a two dimensional photonic crystal (PhC) based drop filter, at communication wavelength with more than 90% transmission. The filtering is achieved by introducing two line defects and three point defects in a two dimensional triangular array of ferroelectric rods in air. Using the electro-optic property of the ferroelectric, about 32 nm tuning in the resonance wavelength is obtained. For the calculation of transmission, finite difference time domain (FDTD) simulations were performed. The operating frequency range is explored via the band structure which is obtained by the implementation of plane wave expansion (PWE) method. The influence of the radius of various rods on the filter wavelength as well as efficiency is also analyzed. The different possible configurations of this filter are also considered.

  6. 40 Gbps 100-km SSMF VSB-IMDD OFDM transmission experiment based on FBG filter

    Science.gov (United States)

    Ju, Cheng; Yang, Pengfei; Chen, Xue; Zhang, Zhiguo; Liu, Na

    2014-10-01

    This work studies the transmission performance of vestigial-sideband (VSB)-IMDD OFDM system by theoretical analysis and numerical simulation. The analysis shows that the detrimental effect of dispersion-induced power fading can be effectively suppressed. The presence of positive and negative chirp of modulator will increase the dispersion-, chirp- and VSB optical filter-induced subcarrier to subcarrier intermixing interference (SSII), which significantly restricts transmission performance. Relatively lower order Gaussian optical filter has almost the same performance with ideal rectangular filter over 100-km SMF transmission and have better performance in less than 60-km transmission. Furthermore, we successfully transmit a 40 Gbps, 16QAM, MZM-based VSB-IMDD OFDM signal through 100-km of uncompensated standard single mode fiber (SSMF) by using an economical FBG optical filter. The experimental results show that available bandwidth has been extended up to 10 GHz after 100-km SSMF transmission.

  7. NONLINEAR FILTER METHOD OF GPS DYNAMIC POSITIONING BASED ON BANCROFT ALGORITHM

    Institute of Scientific and Technical Information of China (English)

    ZHANGQin; TAOBen-zao; ZHAOChao-ying; WANGLi

    2005-01-01

    Because of the ignored items after linearization, the extended Kalman filter (EKF) becomes a form of suboptimal gradient descent algorithm. The emanative tendency exists in GPS solution when the filter equations are ill-posed. The deviation in the estimation cannot be avoided. Furthermore, the true solution may be lost in pseudorange positioning because the linearized pseudorange equations are partial solutions. To solve the above problems in GPS dynamic positioning by using EKF, a closed-form Kalman filter method called the two-stage algorithm is presented for the nonlinear algebraic solution of GPS dynamic positioning based on the global nonlinear least squares closed algorithm--Bancroft numerical algorithm of American. The method separates the spatial parts from temporal parts during processing the GPS filter problems, and solves the nonlinear GPS dynamic positioning, thus getting stable and reliable dynamic positioning solutions.

  8. WaVPeak: Picking NMR peaks through wavelet-based smoothing and volume-based filtering

    KAUST Repository

    Liu, Zhi

    2012-02-10

    Motivation: Nuclear magnetic resonance (NMR) has been widely used as a powerful tool to determine the 3D structures of proteins in vivo. However, the post-spectra processing stage of NMR structure determination usually involves a tremendous amount of time and expert knowledge, which includes peak picking, chemical shift assignment and structure calculation steps. Detecting accurate peaks from the NMR spectra is a prerequisite for all following steps, and thus remains a key problem in automatic NMR structure determination. Results: We introduce WaVPeak, a fully automatic peak detection method. WaVPeak first smoothes the given NMR spectrum by wavelets. The peaks are then identified as the local maxima. The false positive peaks are filtered out efficiently by considering the volume of the peaks. WaVPeak has two major advantages over the state-of-the-art peak-picking methods. First, through wavelet-based smoothing, WaVPeak does not eliminate any data point in the spectra. Therefore, WaVPeak is able to detect weak peaks that are embedded in the noise level. NMR spectroscopists need the most help isolating these weak peaks. Second, WaVPeak estimates the volume of the peaks to filter the false positives. This is more reliable than intensity-based filters that are widely used in existing methods. We evaluate the performance of WaVPeak on the benchmark set proposed by PICKY (Alipanahi et al., 2009), one of the most accurate methods in the literature. The dataset comprises 32 2D and 3D spectra from eight different proteins. Experimental results demonstrate that WaVPeak achieves an average of 96%, 91%, 88%, 76% and 85% recall on 15N-HSQC, HNCO, HNCA, HNCACB and CBCA(CO)NH, respectively. When the same number of peaks are considered, WaVPeak significantly outperforms PICKY. The Author(s) 2012. Published by Oxford University Press.

  9. Kalman/Map Filtering-Aided Fast Normalized Cross Correlation-Based Wi-Fi Fingerprinting Location Sensing

    Directory of Open Access Journals (Sweden)

    Yongliang Sun

    2013-11-01

    Full Text Available A Kalman/map filtering (KMF-aided fast normalized cross correlation (FNCC-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS mean samples, the proposed FNCC algorithm makes use of all the on-line RSS samples and reference point RSS variations to achieve higher fingerprinting accuracy. The FNCC computes efficiently while maintaining the same accuracy as the basic normalized cross correlation. Additionally, a KMF is also proposed to process fingerprinting localization results. It employs a new map matching algorithm to nonlinearize the linear location prediction process of Kalman filtering (KF that takes advantage of spatial proximities of consecutive localization results. With a calibration model integrated into an indoor map, the map matching algorithm corrects unreasonable prediction locations of the KF according to the building interior structure. Thus, more accurate prediction locations are obtained. Using these locations, the KMF considerably improves fingerprinting algorithm performance. Experimental results demonstrate that the FNCC algorithm with reduced computational complexity outperforms other neighbor selection algorithms and the KMF effectively improves location sensing accuracy by using indoor map information and spatial proximities of consecutive localization results.

  10. Digital Image Watermarking Based On Gradient Direction Quantization and Denoising Using Guided Image Filtering

    Directory of Open Access Journals (Sweden)

    I.Kullayamma

    2016-05-01

    Full Text Available Digital watermarking is the art of hiding of information or data in documents, where the embedded information or data can be extracted to resist copyright violation or to verify the uniqueness of a document which leads to security. Protecting the digital content has become a major issue for content owners and service providers. Watermarking using gradient direction quantization is based on the uniform quantization of the direction of gradient vectors, which is called gradient direction watermarking (GDWM. In GDWM, the watermark bits are embedded by quantizing the angles of significant gradient vectors at multiple wavelet scales. The proposed scheme has the advantages of increased invisibility and robustness to amplitude scaling effects. The DWT coefficients are modified to quantize the gradient direction based on the on the derived relationship between the changes in the coefficients and the change in the gradient direction. In this paper, we propose a novel explicit image filter called guided filter. It is derived from a local linear model that computes the filtering output using the content of guidance image, which can be the input image itself or any other different image. The guided filter naturally has a fast and non approximate linear time algorithm, regardless of the kernel size and the intensity range. Finally, we show simulation results of denoising method using guided image filtering over bilateral filtering

  11. [Hyperspectral image classification based on 3-D gabor filter and support vector machines].

    Science.gov (United States)

    Feng, Xiao; Xiao, Peng-feng; Li, Qi; Liu, Xiao-xi; Wu, Xiao-cui

    2014-08-01

    A three-dimensional Gabor filter was developed for classification of hyperspectral remote sensing image. This method is based on the characteristics of hyperspectral image and the principle of texture extraction with 2-D Gabor filters. Three-dimensional Gabor filter is able to filter all the bands of hyperspectral image simultaneously, capturing the specific responses in different scales, orientations, and spectral-dependent properties from enormous image information, which greatly reduces the time consumption in hyperspectral image texture extraction, and solve the overlay difficulties of filtered spectrums. Using the designed three-dimensional Gabor filters in different scales and orientations, Hyperion image which covers the typical area of Qi Lian Mountain was processed with full bands to get 26 Gabor texture features and the spatial differences of Gabor feature textures corresponding to each land types were analyzed. On the basis of automatic subspace separation, the dimensions of the hyperspectral image were reduced by band index (BI) method which provides different band combinations for classification in order to search for the optimal magnitude of dimension reduction. Adding three-dimensional Gabor texture features successively according to its discrimination to the given land types, supervised classification was carried out with the classifier support vector machines (SVM). It is shown that the method using three-dimensional Gabor texture features and BI band selection based on automatic subspace separation for hyperspectral image classification can not only reduce dimensions; but also improve the classification accuracy and efficiency of hyperspectral image.

  12. Application of GIS-Based Spatial Filtering Method for Neural Tube Defects Disease Mapping

    Institute of Scientific and Technical Information of China (English)

    CHI Wenxue; WANG Jinfeng; LI Xinhu; ZHENG Xiaoying; LIAO Yilan

    2007-01-01

    This study is to assess the prevalence rates spatial pattern of neural tube defects with geographic information system and spatial filtering technique. A total of 80 infants who diagnosed from neural tube defects in the area being studied between 1998 and 2001 were analyzed. Firstly, the geographic information system (GIS) software ArcGIS was used to map the crude prevalence rates. Secondly, the data were smoothed by the method of spatial filtering. We evaluated that the effect of changes in spatial filtering radius size was assessed by creating maps based on various filtering radius sizes, The 3 miles or larger filtering radius gives better sec tion variability than the 2 and 2.5 miles or smaller ones. The maps produced by the spatial filtering technique indicate that prevalence rates in the villages in the southeastern region are to produce higher prevalence than that in the other regions. The smoothed maps based on Heshun County display a more adequate data representation than the raw prevalence rate map.

  13. Maximum likelihood-based iterated divided difference filter for nonlinear systems from discrete noisy measurements.

    Science.gov (United States)

    Wang, Changyuan; Zhang, Jing; Mu, Jing

    2012-01-01

    A new filter named the maximum likelihood-based iterated divided difference filter (MLIDDF) is developed to improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation errors and nonlinearity of measurement equations. The MLIDDF algorithm is derivative-free and implemented only by calculating the functional evaluations. The MLIDDF algorithm involves the use of the iteration measurement update and the current measurement, and the iteration termination criterion based on maximum likelihood is introduced in the measurement update step, so the MLIDDF is guaranteed to produce a sequence estimate that moves up the maximum likelihood surface. In a simulation, its performance is compared against that of the unscented Kalman filter (UKF), divided difference filter (DDF), iterated unscented Kalman filter (IUKF) and iterated divided difference filter (IDDF) both using a traditional iteration strategy. Simulation results demonstrate that the accumulated mean-square root error for the MLIDDF algorithm in position is reduced by 63% compared to that of UKF and DDF algorithms, and by 7% compared to that of IUKF and IDDF algorithms. The new algorithm thus has better state estimation accuracy and a fast convergence rate.

  14. Maximum Likelihood-Based Iterated Divided Difference Filter for Nonlinear Systems from Discrete Noisy Measurements

    Directory of Open Access Journals (Sweden)

    Changyuan Wang

    2012-06-01

    Full Text Available A new filter named the maximum likelihood-based iterated divided difference filter (MLIDDF is developed to improve the low state estimation accuracy of nonlinear state estimation due to large initial estimation errors and nonlinearity of measurement equations. The MLIDDF algorithm is derivative-free and implemented only by calculating the functional evaluations. The MLIDDF algorithm involves the use of the iteration measurement update and the current measurement, and the iteration termination criterion based on maximum likelihood is introduced in the measurement update step, so the MLIDDF is guaranteed to produce a sequence estimate that moves up the maximum likelihood surface. In a simulation, its performance is compared against that of the unscented Kalman filter (UKF, divided difference filter (DDF, iterated unscented Kalman filter (IUKF and iterated divided difference filter (IDDF both using a traditional iteration strategy. Simulation results demonstrate that the accumulated mean-square root error for the MLIDDF algorithm in position is reduced by 63% compared to that of UKF and DDF algorithms, and by 7% compared to that of IUKF and IDDF algorithms. The new algorithm thus has better state estimation accuracy and a fast convergence rate.

  15. A Soft Sensor for Bioprocess Control Based on Sequential Filtering of Metabolic Heat Signals

    Directory of Open Access Journals (Sweden)

    Dan Paulsson

    2014-09-01

    Full Text Available Soft sensors are the combination of robust on-line sensor signals with mathematical models for deriving additional process information. Here, we apply this principle to a microbial recombinant protein production process in a bioreactor by exploiting bio-calorimetric methodology. Temperature sensor signals from the cooling system of the bioreactor were used for estimating the metabolic heat of the microbial culture and from that the specific growth rate and active biomass concentration were derived. By applying sequential digital signal filtering, the soft sensor was made more robust for industrial practice with cultures generating low metabolic heat in environments with high noise level. The estimated specific growth rate signal obtained from the three stage sequential filter allowed controlled feeding of substrate during the fed-batch phase of the production process. The biomass and growth rate estimates from the soft sensor were also compared with an alternative sensor probe and a capacitance on-line sensor, for the same variables. The comparison showed similar or better sensitivity and lower variability for the metabolic heat soft sensor suggesting that using permanent temperature sensors of a bioreactor is a realistic and inexpensive alternative for monitoring and control. However, both alternatives are easy to implement in a soft sensor, alone or in parallel.

  16. The generalization ability of online SVM classification based on Markov sampling.

    Science.gov (United States)

    Xu, Jie; Yan Tang, Yuan; Zou, Bin; Xu, Zongben; Li, Luoqing; Lu, Yang

    2015-03-01

    In this paper, we consider online support vector machine (SVM) classification learning algorithms with uniformly ergodic Markov chain (u.e.M.c.) samples. We establish the bound on the misclassification error of an online SVM classification algorithm with u.e.M.c. samples based on reproducing kernel Hilbert spaces and obtain a satisfactory convergence rate. We also introduce a novel online SVM classification algorithm based on Markov sampling, and present the numerical studies on the learning ability of online SVM classification based on Markov sampling for benchmark repository. The numerical studies show that the learning performance of the online SVM classification algorithm based on Markov sampling is better than that of classical online SVM classification based on random sampling as the size of training samples is larger.

  17. Nonlinear ultrasonic measurements based on cross-correlation filtering techniques

    Science.gov (United States)

    Yee, Andrew; Stewart, Dylan; Bunget, Gheorghe; Kramer, Patrick; Farinholt, Kevin; Friedersdorf, Fritz; Pepi, Marc; Ghoshal, Anindya

    2017-02-01

    Cyclic loading of mechanical components promotes the formation of dislocation dipoles in metals, which can serve as precursors to crack nucleation and ultimately lead to failure. In the laboratory setting, an acoustic nonlinearity parameter has been assessed as an effective indicator for characterizing the progression of fatigue damage precursors. However, the need to use monochromatic waves of medium-to-high acoustic energy has presented a constraint, making it problematic for use in field applications. This paper presents a potential approach for field measurement of acoustic nonlinearity by using general purpose ultrasonic pulser-receivers. Nonlinear ultrasonic measurements during fatigue testing were analyzed by the using contact and immersion pulse-through method. A novel cross-correlation filtering technique was developed to extract the fundamental and higher harmonic waves from the signals. As in the case of the classic harmonic generation, the nonlinearity parameters of the second and third harmonics indicate a strong correlation with fatigue cycles. Consideration was given to potential nonlinearities in the measurement system, and tests have confirmed that measured second harmonic signals exhibit a linear dependence on the input signal strength, further affirming the conclusion that this parameter relates to damage precursor formation from cyclic loading.

  18. Discrete Kalman Filter based Sensor Fusion for Robust Accessibility Interfaces

    Science.gov (United States)

    Ghersi, I.; Mariño, M.; Miralles, M. T.

    2016-04-01

    Human-machine interfaces have evolved, benefiting from the growing access to devices with superior, embedded signal-processing capabilities, as well as through new sensors that allow the estimation of movements and gestures, resulting in increasingly intuitive interfaces. In this context, sensor fusion for the estimation of the spatial orientation of body segments allows to achieve more robust solutions, overcoming specific disadvantages derived from the use of isolated sensors, such as the sensitivity of magnetic-field sensors to external influences, when used in uncontrolled environments. In this work, a method for the combination of image-processing data and angular-velocity registers from a 3D MEMS gyroscope, through a Discrete-time Kalman Filter, is proposed and deployed as an alternate user interface for mobile devices, in which an on-screen pointer is controlled with head movements. Results concerning general performance of the method are presented, as well as a comparative analysis, under a dedicated test application, with results from a previous version of this system, in which the relative-orientation information was acquired directly from MEMS sensors (3D magnetometer-accelerometer). These results show an improved response for this new version of the pointer, both in terms of precision and response time, while keeping many of the benefits that were highlighted for its predecessor, giving place to a complementary method for signal acquisition that can be used as an alternative-input device, as well as for accessibility solutions.

  19. Collaborating Filtering Community Image Recommendation System Based on Scene

    Directory of Open Access Journals (Sweden)

    He Tao

    2017-01-01

    Full Text Available With the advancement of smart city, the development of intelligent mobile terminal and wireless network, the traditional text information service no longer meet the needs of the community residents, community image service appeared as a new media service. “There are pictures of the truth” has become a community residents to understand and master the new dynamic community, image information service has become a new information service. However, there are two major problems in image information service. Firstly, the underlying eigenvalues extracted by current image feature extraction techniques are difficult for users to understand, and there is a semantic gap between the image content itself and the user’s understanding; secondly, in community life of the image data increasing quickly, it is difficult to find their own interested image data. Aiming at the two problems, this paper proposes a unified image semantic scene model to express the image content. On this basis, a collaborative filtering recommendation model of fusion scene semantics is proposed. In the recommendation model, a comprehensiveness and accuracy user interest model is proposed to improve the recommendation quality. The results of the present study have achieved good results in the pilot cities of Wenzhou and Yan'an, and it is applied normally.

  20. Robust and Adaptive Block Tracking Method Based on Particle Filter

    Directory of Open Access Journals (Sweden)

    Bin Sun

    2015-10-01

    Full Text Available In the field of video analysis and processing, object tracking is attracting more and more attention especially in traffic management, digital surveillance and so on. However problems such as objects’ abrupt motion, occlusion and complex target structures would bring difficulties to academic study and engineering application. In this paper, a fragmentsbased tracking method using the block relationship coefficient is proposed. In this method, we use particle filter algorithm and object region is divided into blocks initially. The contribution of this method is that object features are not extracted just from a single block, the relationship between current block and its neighbor blocks are extracted to describe the variation of the block. Each block is weighted according to the block relationship coefficient when the block is voted on the most matched region in next frame. This method can make full use of the relationship between blocks. The experimental results demonstrate that our method can provide good performance in condition of occlusion and abrupt posture variation.

  1. Filtering Data Based on Human-Inspired Forgetting.

    Science.gov (United States)

    Freedman, S T; Adams, J A

    2011-12-01

    Robots are frequently presented with vast arrays of diverse data. Unfortunately, perfect memory and recall provides a mixed blessing. While flawless recollection of episodic data allows increased reasoning, photographic memory can hinder a robot's ability to operate in real-time dynamic environments. Human-inspired forgetting methods may enable robotic systems to rid themselves of out-dated, irrelevant, and erroneous data. This paper presents the use of human-inspired forgetting to act as a filter, removing unnecessary, erroneous, and out-of-date information. The novel ActSimple forgetting algorithm has been developed specifically to provide effective forgetting capabilities to robotic systems. This paper presents the ActSimple algorithm and how it was optimized and tested in a WiFi signal strength estimation task. The results generated by real-world testing suggest that human-inspired forgetting is an effective means of improving the ability of mobile robots to move and operate within complex and dynamic environments.

  2. VLSI IMPLEMENTATION OF FIR FILTER USING COMPUTATIONAL SHARING MULTIPLIER BASED ON HIGH SPEED CARRY SELECT ADDER

    Directory of Open Access Journals (Sweden)

    S. Karunakaran

    2012-01-01

    Full Text Available Recent advances in mobile computing and multimedia applications demand high-performance and low-power VLSI Digital Signal Processing (DSP systems. One of the most widely used operations in DSP is Finite-Impulse Response (FIR filtering. In the existing method FIR filter is designed using array multiplier, which is having higher delay and power dissipation. The proposed method presents a programmable digital Finite Impulse Response (FIR filter for high-performance applications. The architecture is based on a computational sharing multiplier which specifically doing add and shift operation and also targets computation re-use in vector-scalar products. CSHM multiplier can be implemented by Carry Select Adder which is a high speed adder. A Carry-Select Adder (CSA can be implemented by using single ripple carry adder and add-one circuits using the fast all-one finding circuit and low-delay multiplexers to reduce the area and accelerate the speed of CSA. An 8-tap programmable FIR filter was implemented in tanner EDA tool using CMOS 180nm technology based on the proposed CSHM technique. In which the number of transistor, power (mW and clock cycle (ns of the filter using array multiplier are 6000, 3.732 and 9 respectively. The FIR filter using CSHM in which the number of transistor, power (mW and clock cycle (ns are 23500, 2.627 and 4.5 respectively. By adopting the proposed method for the design of FIR filter, the delay is reduced to about 43.2% in comparison with the existing method. The CSHM scheme and circuit-level techniques helped to achieve high-performance FIR filtering operation.

  3. Stereo vision based SLAM using Rao-Blackwellised particle filter

    Institute of Scientific and Technical Information of China (English)

    Er-yong WU; Gong-yan LI; Zhi-yu XIANG; Ji-lin LIU

    2008-01-01

    We present an algorithm which can realize 3D stereo vision simultaneous localization and mapping (SLAM) for mobile robot in unknown outdoor environments, which means the 6-DOF motion and a sparse but persistent map of natural landmarks be constructed online only with a stereo camera. In mobile robotics research, we extend FastSLAM 2.0 like stereo vision SLAM with "pure vision" domain to outdoor environments. Unlike popular stochastic motion model used in conventional monocular vision SLAM, we utilize the ideas of structure from motion (SFM) for initial motion estimation, which is more suitable for the robot moving in large-scale outdoor, and textured environments. SIFT features are used as natural landmarks, and its 3D positions are constructed directly through triangulation. Considering the computational complexity and memory consumption,Bkd-tree and Best-Bin-First (BBF) search strategy are utilized for SIFT feature descriptor matching. Results show high accuracy of our algorithm, even in the circumstance of large translation and large rotation movements.

  4. On-line Test for Train Communication Based System

    Institute of Scientific and Technical Information of China (English)

    Zeng Xiaoqing; Masayuki Matsumoto; Kinji Mori; XU Fucang

    2002-01-01

    This paper gives out a new train automatic control system, which is based on train communication, and proposes a high assurance method to construct the system from current system. In current automatic train control (ATC) system, the central logic device detects position of each train and calculates permissible speed of each blocking section. Therefore, the central logic device controls speed of all trains. On the contrary, in the new system proposed in this paper, there is no central logical device and, train can communicate each other. The train detects the position and calculates the permissible speed itself according to the received position information of the preceding train. In the traditional method of changing an old system to a new one, test must be done off-line.While the integration technique proposed in this paper achieves on-line properties, and high assurance can be satisfied.

  5. Multiple Maneuvering Target Tracking by Improved Particle Filter Based on Multiscan JPDA

    Directory of Open Access Journals (Sweden)

    Jing Liu

    2012-01-01

    Full Text Available The multiple maneuvering target tracking algorithm based on a particle filter is addressed. The equivalent-noise approach is adopted, which uses a simple dynamic model consisting of target state and equivalent noise which accounts for the combined effects of the process noise and maneuvers. The equivalent-noise approach converts the problem of maneuvering target tracking to that of state estimation in the presence of nonstationary process noise with unknown statistics. A novel method for identifying the nonstationary process noise is proposed in the particle filter framework. Furthermore, a particle filter based multiscan Joint Probability Data Association (JPDA filter is proposed to deal with the data association problem in a multiple maneuvering target tracking. In the proposed multiscan JPDA algorithm, the distributions of interest are the marginal filtering distributions for each of the targets, and these distributions are approximated with particles. The multiscan JPDA algorithm examines the joint association events in a multiscan sliding window and calculates the marginal posterior probability based on the multiscan joint association events. The proposed algorithm is illustrated via an example involving the tracking of two highly maneuvering, at times closely spaced and crossed, targets, based on resolved measurements.

  6. Online tools for teaching evidence-based veterinary medicine.

    Science.gov (United States)

    Steele, Michael; Crabb, Nicholas P; Moore, Lynda J; Reyher, Kristen K; Baillie, Sarah; Eisler, Mark C

    2013-01-01

    Evidence-based veterinary medicine (EBVM) is of interest and relevance to veterinary practitioners. Consequently, veterinary schools take responsibility for teaching students how to appraise scientific articles and for equipping them with the skills needed to obtain and evaluate the best evidence and to apply this approach to their own cases. As part of our farm animal clinical rotation, we train students in qualitative and quantitative EBVM methods using an e-learning environment, online teaching materials, a wiki (a Web site that allows its users to edit its content via a Web browser), and face-to-face tutorials that support learning. Students working in small groups use a wiki to record details of the history, clinical presentation, diagnostic tests, herd data, and management plans for their chosen farm animal clinical cases. Using a standardized patient, intervention, comparison, and outcome (PICO) format, each group formulates a patient question based on either a proposed intervention or diagnostic procedure for the case and conducts an online scientific literature database search. The students appraise the articles retrieved using EBVM approaches and record the information in the wiki. The summation of this body of work, the group's critically appraised topic (CAT), includes the original PICO, a standardized table of the scientific evidence for the effectiveness of the intervention or diagnostic procedure, a summary statement in the form of a clinical bottom line, and their reflections upon the CAT. At the end of the rotation, students take part in a structured "CAT Club" where they present and discuss their findings with fellow students and clinicians.

  7. Electronically Tunable Current-mode High-order Ladder Low-pass Filters Based on CMOS Technology

    Directory of Open Access Journals (Sweden)

    T. Kunto

    2015-12-01

    Full Text Available This paper describes the design of current mode low-pass ladder filters based on CMOS technology. The filters are derived from passive RLC ladder filter prototypes using new CMOS lossy and lossless integrators. The all-pole and Elliptic approximations are used in the proposed low-pass filter realizations. The proposed two types of filter can be electronically tuned between 10kHz and 100MHz through bias current from 0.03µA to 300µA. The proposed filters use 1.5 V power supply with 3 mW power consumption at 300 µA bias current. The proposed filters are resistorless, use grounded capacitors and are suitable for further integration. The total harmonic distortion (THD of the low-pass filters is less than 1% over the operating frequency range. PSPICE simulation results, obtained by using TSMC 0.18µm technology, confirm the presented theory.

  8. Miniaturized sharp band-pass filter based on complementary electric-LC resonator

    Science.gov (United States)

    Torabi, Yalda; Dadashzadeh, Golamreza; Oraizi, Homayoon

    2016-04-01

    In this paper, a novel application of complementary electric-LC (CELC) resonator as a basic element to synthesize miniaturized sharp band-pass filters is introduced. The proposed metamaterial band-pass filter is a three-stage CELC-based device, where two shunt short-circuited stubs are employed in the input and output stages and a series gap is etched in the middle stage. By these means, a high-selectivity prototype band-pass filter with 2 % fractional bandwidth in S band is designed and fabricated. The out-of-band attenuation is better than 40 dB, and the upper and lower transition bands are also quite sharp due to the presence of two transmission zeros (nearly 60 and 30 dB fall in 0.2 GHz at lower and upper edges, respectively). Moreover, the filter is substantially miniaturized with a size of effective region of 1.3 cm × 1 cm at 2.9 GHz, which is quite smaller relative to conventional designs with the same performance. The fabrication and measurement of the proposed filter configuration attest to its expected desirable features. Therefore, the application of CELC resonator is proposed for super-compact sharp band-pass filters.

  9. CUDA-based acceleration of collateral filtering in brain MR images

    Science.gov (United States)

    Li, Cheng-Yuan; Chang, Herng-Hua

    2017-02-01

    Image denoising is one of the fundamental and essential tasks within image processing. In medical imaging, finding an effective algorithm that can remove random noise in MR images is important. This paper proposes an effective noise reduction method for brain magnetic resonance (MR) images. Our approach is based on the collateral filter which is a more powerful method than the bilateral filter in many cases. However, the computation of the collateral filter algorithm is quite time-consuming. To solve this problem, we improved the collateral filter algorithm with parallel computing using GPU. We adopted CUDA, an application programming interface for GPU by NVIDIA, to accelerate the computation. Our experimental evaluation on an Intel Xeon CPU E5-2620 v3 2.40GHz with a NVIDIA Tesla K40c GPU indicated that the proposed implementation runs dramatically faster than the traditional collateral filter. We believe that the proposed framework has established a general blueprint for achieving fast and robust filtering in a wide variety of medical image denoising applications.

  10. Speckle reduction in ultrasound medical images using adaptive filter based on second order statistics.

    Science.gov (United States)

    Thakur, A; Anand, R S

    2007-01-01

    This article discusses an adaptive filtering technique for reducing speckle using second order statistics of the speckle pattern in ultrasound medical images. Several region-based adaptive filter techniques have been developed for speckle noise suppression, but there are no specific criteria for selecting the region growing size in the post processing of the filter. The size appropriate for one local region may not be appropriate for other regions. Selection of the correct region size involves a trade-off between speckle reduction and edge preservation. Generally, a large region size is used to smooth speckle and a small size to preserve the edges into an image. In this paper, a smoothing procedure combines the first order statistics of speckle for the homogeneity test and second order statistics for selection of filters and desired region growth. Grey level co-occurrence matrix (GLCM) is calculated for every region during the region contraction and region growing for second order statistics. Further, these GLCM features determine the appropriate filter for the region smoothing. The performance of this approach is compared with the aggressive region-growing filter (ARGF) using edge preservation and speckle reduction tests. The processed image results show that the proposed method effectively reduces speckle noise and preserves edge details.

  11. Tunable multiple-channel filters based on photonic heterostructures using single-negative materials

    Institute of Scientific and Technical Information of China (English)

    DENG XinHua; LIU NianHua; AN LiPing

    2009-01-01

    We studied the multiple-channel filters based on photonic heterostructures consisting of single-negative permittivity and single-negative permeability media. The results showed that the number of resonance modes inside the zero-φeff gap increases as the number of heterogenous interface M increases. The number of resonance modes inside the zero-φeff gap is equal to that of heterogenous interface M, and it can be used as M channels filter. This result provides a feasible method to adjust the channel number of multiple-channel filters. When losses are involved, the results showed that the electric fields of the resonance modes decay largely with the increase of the number of heterogenous interface and damping factors. Besides, the relationship between the quality factor of multiple-channel filters and the number of heterogenous interface M is linear, and the quality factor of multiple-channel filters decreases with the increase of the damping factor. These results provide feasible methods to adjust the quality factor of multiple-channel filters.

  12. Map-Based Indoor Pedestrian Navigation Using an Auxiliary Particle Filter

    Directory of Open Access Journals (Sweden)

    Chunyang Yu

    2017-07-01

    Full Text Available In this research, a non-infrastructure-based and low-cost indoor navigation method is proposed through the integration of smartphone built-in microelectromechanical systems (MEMS sensors and indoor map information using an auxiliary particle filter (APF. A cascade structure Kalman particle filter algorithm is designed to reduce the computational burden and improve the estimation speed of the APF by decreasing its update frequency and the number of particles used in this research. In the lower filter (Kalman filter, zero velocity update and non-holonomic constraints are used to correct the error of the inertial navigation-derived solutions. The innovation of the design lies in the combination of upper filter (particle filter map-matching and map-aiding methods to further constrain the navigation solutions. This proposed navigation method simplifies indoor positioning and makes it accessible to individual and group users, while guaranteeing the system’s accuracy. The availability and accuracy of the proposed algorithm are tested and validated through experiments in various practical scenarios.

  13. Design of quadrature mirror filter bank using Lagrange multiplier method based on fractional derivative constraints

    Directory of Open Access Journals (Sweden)

    B. Kuldeep

    2015-06-01

    Full Text Available Fractional calculus has recently been identified as a very important mathematical tool in the field of signal processing. Digital filters designed by fractional derivatives give more accurate frequency response in the prescribed frequency region. Digital filters are most important part of multi-rate filter bank systems. In this paper, an improved method based on fractional derivative constraints is presented for the design of two-channel quadrature mirror filter (QMF bank. The design problem is formulated as minimization of L2 error of filter bank transfer function in passband, stopband interval and at quadrature frequency, and then Lagrange multiplier method with fractional derivative constraints is applied to solve it. The proposed method is then successfully applied for the design of two-channel QMF bank with higher order filter taps. Performance of the QMF bank design is then examined through study of various parameters such as passband error, stopband error, transition band error, peak reconstruction error (PRE, stopband attenuation (As. It is found that, the good design can be obtained with the change of number and value of fractional derivative constraint coefficients.

  14. Seismic data filtering using non-local means algorithm based on structure tensor

    Science.gov (United States)

    Yang, Shuai; Chen, Anqing; Chen, Hongde

    2017-05-01

    Non-Local means algorithm is a new and effective filtering method. It calculates weights of all similar neighborhoods' center points relative to filtering point within searching range by Gaussian weighted Euclidean distance between neighborhoods, then gets filtering point's value by weighted average to complete the filtering operation. In this paper, geometric distance of neighborhood's center point is taken into account in the distance measure calculation, making the non-local means algorithm more reasonable. Furthermore, in order to better protect the geometry structure information of seismic data, we introduce structure tensor that can depict the local geometrical features of seismic data. The coherence measure, which reflects image local contrast, is extracted from the structure tensor, is integrated into the non-local means algorithm to participate in the weight calculation, the control factor of geometry structure similarity is added to form a non-local means filtering algorithm based on structure tensor. The experimental results prove that the algorithm can effectively restrain noise, with strong anti-noise and amplitude preservation effect, improving PSNR and protecting structure information of seismic image. The method has been successfully applied in seismic data processing, indicating that it is a new and effective technique to conduct the structure-preserved filtering of seismic data.

  15. Curved-Region-Based Ridge Frequency Estimation and Curved Gabor Filters for Fingerprint Image Enhancement

    Science.gov (United States)

    Gottschlich, Carsten

    2012-04-01

    Gabor filters play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved Gabor filters which locally adapt their shape to the direction of flow. These curved Gabor filters enable the choice of filter parameters which increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved Gabor filters are applied to the curved ridge and valley structure of low-quality fingerprint images. First, we combine two orientation field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation and they are used for estimating the local ridge frequency. Lastly, curved Gabor filters are defined based on curved regions and they are applied for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison to state-of-the-art enhancement methods.

  16. Optimal design study of high order FIR digital filters based on neural network algorithm

    Institute of Scientific and Technical Information of China (English)

    王小华; 何怡刚

    2004-01-01

    An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amplitude response of the desired FIR filter and that of the designed by training the weights of neural networks, then obtains the impulse response of FIR digital filter . The convergence theorem of the neural networks algorithm is presented and proved,and the optimal design method is introduced by designing four kinds of FIR digital filters , i.e., low-pass, high-pass,bandpass , and band-stop FIR digital filter. The results of the amplitude responses show that attenuation in stop-bands is more than 60 dB with no ripple and pulse existing in pass-bands, and cutoff frequency of passband and stop-band is easily controlled precisely . The presented optimal design approach of high order FIR digital filter is significantly effective.

  17. Tunable M-channel filter based on Thue-Morse heterostructures containing meta materials

    Directory of Open Access Journals (Sweden)

    H Pashaei Adl

    2015-01-01

    Full Text Available In this paper the tunable M-channel filters based on Thue-Morse heterostructures consisting of single -negative materials has been studied. The results showed that the number of resonance modes inside the zero- gap increases as the number of heterogenous interface, M, increases. The number of resonance modes inside the zero- gap is equal to that of heterogenous interface M, and it can be used as M channels filter. This result provides a feasible method to adjust the channel number of multiple-channel filters. When losses are involved, the results showed that the electric fields of the resonance modes decay largely with the increase of the number of heterogenous interface and damping factors. Besides, the relationship between the quality factor of multiple-channel filters and the number of heterogenous interface M is linear, and the quality factor of multiple-channel filters decreases with the increase of the damping factor. These results provide feasible methods to adjust the quality factor of multiple-channel filters

  18. RSSI-Based Distance Estimation Framework Using a Kalman Filter for Sustainable Indoor Computing Environments

    Directory of Open Access Journals (Sweden)

    Yunsick Sung

    2016-11-01

    Full Text Available Given that location information is the key to providing a variety of services in sustainable indoor computing environments, it is required to obtain accurate locations. Locations can be estimated by three distances from three fixed points. Therefore, if the distance between two points can be measured or estimated accurately, the location in indoor environments can be estimated. To increase the accuracy of the measured distance, noise filtering, signal revision, and distance estimation processes are generally performed. This paper proposes a novel framework for estimating the distance between a beacon and an access point (AP in a sustainable indoor computing environment. Diverse types of received strength signal indications (RSSIs are used for WiFi, Bluetooth, and radio signals, and the proposed distance estimation framework is unique in that it is independent of the specific wireless signal involved, being based on the Bluetooth signal of the beacon. Generally, RSSI measurement, noise filtering, and revision are required for distance estimation using RSSIs. The employed RSSIs are first measured from an AP, with multiple APs sometimes used to increase the accuracy of the distance estimation. Owing to the inevitable presence of noise in the measured RSSIs, the application of noise filtering is essential, and further revision is used to address the inaccuracy and instability that characterizes RSSIs measured in an indoor environment. The revised RSSIs are then used to estimate the distance. The proposed distance estimation framework uses one AP to measure the RSSIs, a Kalman filter to eliminate noise, and a log-distance path loss model to revise the measured RSSIs. In the experimental implementation of the framework, both a RSSI filter and a Kalman filter were respectively used for noise elimination to comparatively evaluate the performance of the latter for the specific application. The Kalman filter was found to reduce the accumulated errors by 8

  19. Integration of GPS Precise Point Positioning and MEMS-Based INS Using Unscented Particle Filter

    Directory of Open Access Journals (Sweden)

    Mahmoud Abd Rabbou

    2015-03-01

    Full Text Available Integration of Global Positioning System (GPS and Inertial Navigation System (INS integrated system involves nonlinear motion state and measurement models. However, the extended Kalman filter (EKF is commonly used as the estimation filter, which might lead to solution divergence. This is usually encountered during GPS outages, when low-cost micro-electro-mechanical sensors (MEMS inertial sensors are used. To enhance the navigation system performance, alternatives to the standard EKF should be considered. Particle filtering (PF is commonly considered as a nonlinear estimation technique to accommodate severe MEMS inertial sensor biases and noise behavior. However, the computation burden of PF limits its use. In this study, an improved version of PF, the unscented particle filter (UPF, is utilized, which combines the unscented Kalman filter (UKF and PF for the integration of GPS precise point positioning and MEMS-based inertial systems. The proposed filter is examined and compared with traditional estimation filters, namely EKF, UKF and PF. Tightly coupled mechanization is adopted, which is developed in the raw GPS and INS measurement domain. Un-differenced ionosphere-free linear combinations of pseudorange and carrier-phase measurements are used for PPP. The performance of the UPF is analyzed using a real test scenario in downtown Kingston, Ontario. It is shown that the use of UPF reduces the number of samples needed to produce an accurate solution, in comparison with the traditional PF, which in turn reduces the processing time. In addition, UPF enhances the positioning accuracy by up to 15% during GPS outages, in comparison with EKF. However, all filters produce comparable results when the GPS measurement updates are available.

  20. LC Filter Design for Wide Band Gap Device Based Adjustable Speed Drives

    DEFF Research Database (Denmark)

    Vadstrup, Casper; Wang, Xiongfei; Blaabjerg, Frede

    2014-01-01

    the LC filter with a higher cut off frequency and without damping resistors. The selection of inductance and capacitance is chosen based on capacitor voltage ripple and current ripple. The filter adds a base load to the inverter, which increases the inverter losses. It is shown how the modulation index......This paper presents a simple design procedure for LC filters used in wide band gap device based adjustable speed drives. Wide band gap devices offer fast turn-on and turn-off times, thus producing high dV/dt into the motor terminals. The high dV/dt can be harmful for the motor windings and bearings...... affects the capacitor capacitor and the inverter current....