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Sample records for adaptive signal processing

  1. Fundamentals of adaptive signal processing

    CERN Document Server

    Uncini, Aurelio

    2015-01-01

    This book is an accessible guide to adaptive signal processing methods that equips the reader with advanced theoretical and practical tools for the study and development of circuit structures and provides robust algorithms relevant to a wide variety of application scenarios. Examples include multimodal and multimedia communications, the biological and biomedical fields, economic models, environmental sciences, acoustics, telecommunications, remote sensing, monitoring, and, in general, the modeling and prediction of complex physical phenomena. The reader will learn not only how to design and implement the algorithms but also how to evaluate their performance for specific applications utilizing the tools provided. While using a simple mathematical language, the employed approach is very rigorous. The text will be of value both for research purposes and for courses of study.

  2. Interactive Teaching of Adaptive Signal Processing

    OpenAIRE

    Stewart, R W; Harteneck, M; Weiss, S

    2000-01-01

    Over the last 30 years adaptive digital signal processing has progressed from being a strictly graduate level advanced class in signal processing theory to a topic that is part of the core curriculum for many undergraduate signal processing classes. The key reason is the continued advance of communications technology, with its need for echo control and equalisation, and the widespread use of adaptive filters in audio, biomedical, and control applications. In this paper we will review the basi...

  3. An adaptive signal-processing approach to online adaptive tutoring.

    Science.gov (United States)

    Bergeron, Bryan; Cline, Andrew

    2011-01-01

    Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

  4. Optimal and adaptive methods of processing hydroacoustic signals (review)

    Science.gov (United States)

    Malyshkin, G. S.; Sidel'nikov, G. B.

    2014-09-01

    Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

  5. A mixed signal ECG processing platform with an adaptive sampling ADC for portable monitoring applications.

    Science.gov (United States)

    Kim, Hyejung; Van Hoof, Chris; Yazicioglu, Refet Firat

    2011-01-01

    This paper describes a mixed-signal ECG processing platform with an 12-bit ADC architecture that can adapt its sampling rate according to the input signals rate of change. This enables the sampling of ECG signals with significantly reduced data rate without loss of information. The presented adaptive sampling scheme reduces the ADC power consumption, enables the processing of ECG signals with lower power consumption, and reduces the power consumption of the radio while streaming the ECG signals. The test results show that running a CWT-based R peak detection algorithm using the adaptively sampled ECG signals consumes only 45.6 μW and it leads to 36% less overall system power consumption.

  6. Adaptive electric potential sensors for smart signal acquisition and processing

    International Nuclear Information System (INIS)

    Prance, R J; Beardsmore-Rust, S; Prance, H; Harland, C J; Stiffell, P B

    2007-01-01

    Current applications of the Electric Potential Sensor operate in a strongly (capacitively) coupled limit, with the sensor physically close to or touching the source. This mode of operation screens the sensor effectively from the majority of external noise. To date however the full capability of these sensors operating in a remote mode has not been realised outside of a screened environment (Faraday cage). This paper describes the results of preliminary work in tailoring the response of the sensors to particular signals and so reject background noise, thereby enhancing both the dynamic range and signal to noise ratio significantly

  7. Adaptive electric potential sensors for smart signal acquisition and processing

    Science.gov (United States)

    Prance, R. J.; Beardsmore-Rust, S.; Prance, H.; Harland, C. J.; Stiffell, P. B.

    2007-07-01

    Current applications of the Electric Potential Sensor operate in a strongly (capacitively) coupled limit, with the sensor physically close to or touching the source. This mode of operation screens the sensor effectively from the majority of external noise. To date however the full capability of these sensors operating in a remote mode has not been realised outside of a screened environment (Faraday cage). This paper describes the results of preliminary work in tailoring the response of the sensors to particular signals and so reject background noise, thereby enhancing both the dynamic range and signal to noise ratio significantly.

  8. Application of adaptive digital signal processing to speech enhancement for the hearing impaired.

    Science.gov (United States)

    Chabries, D M; Christiansen, R W; Brey, R H; Robinette, M S; Harris, R W

    1987-01-01

    A major complaint of individuals with normal hearing and hearing impairments is a reduced ability to understand speech in a noisy environment. This paper describes the concept of adaptive noise cancelling for removing noise from corrupted speech signals. Application of adaptive digital signal processing has long been known and is described from a historical as well as technical perspective. The Widrow-Hoff LMS (least mean square) algorithm developed in 1959 forms the introduction to modern adaptive signal processing. This method uses a "primary" input which consists of the desired speech signal corrupted with noise and a second "reference" signal which is used to estimate the primary noise signal. By subtracting the adaptively filtered estimate of the noise, the desired speech signal is obtained. Recent developments in the field as they relate to noise cancellation are described. These developments include more computationally efficient algorithms as well as algorithms that exhibit improved learning performance. A second method for removing noise from speech, for use when no independent reference for the noise exists, is referred to as single channel noise suppression. Both adaptive and spectral subtraction techniques have been applied to this problem--often with the result of decreased speech intelligibility. Current techniques applied to this problem are described, including signal processing techniques that offer promise in the noise suppression application.

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

    Science.gov (United States)

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

    2017-10-01

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

  10. Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes

    NARCIS (Netherlands)

    Janssen, A.J.E.M.; Veldhuis, R.N.J.; Vries, L.B.

    1986-01-01

    The authors present an adaptive algorithm for the restoration of lost sample values in discrete-time signals that can locally be described by means of autoregressive processes. The only restrictions are that the positions of the unknown samples should be known and that they should be embedded in a

  11. Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes

    NARCIS (Netherlands)

    Janssen, A.J.E.M.; Veldhuis, Raymond N.J.; Vries, Lodewijk B.

    1986-01-01

    This paper presents an adaptive algorithm for the restoration of lost sample values in discrete-time signals that can locally be described by means of autoregressive processes. The only restrictions are that the positions of the unknown samples should be known and that they should be embedded in a

  12. Processing of pulse oximeter signals using adaptive filtering and autocorrelation to isolate perfusion and oxygenation components

    Science.gov (United States)

    Ibey, Bennett; Subramanian, Hariharan; Ericson, Nance; Xu, Weijian; Wilson, Mark; Cote, Gerard L.

    2005-03-01

    A blood perfusion and oxygenation sensor has been developed for in situ monitoring of transplanted organs. In processing in situ data, motion artifacts due to increased perfusion can create invalid oxygenation saturation values. In order to remove the unwanted artifacts from the pulsatile signal, adaptive filtering was employed using a third wavelength source centered at 810nm as a reference signal. The 810 nm source resides approximately at the isosbestic point in the hemoglobin absorption curve where the absorbance of light is nearly equal for oxygenated and deoxygenated hemoglobin. Using an autocorrelation based algorithm oxygenation saturation values can be obtained without the need for large sampling data sets allowing for near real-time processing. This technique has been shown to be more reliable than traditional techniques and proven to adequately improve the measurement of oxygenation values in varying perfusion states.

  13. Adaptive signal processor

    Energy Technology Data Exchange (ETDEWEB)

    Walz, H.V.

    1980-07-01

    An experimental, general purpose adaptive signal processor system has been developed, utilizing a quantized (clipped) version of the Widrow-Hoff least-mean-square adaptive algorithm developed by Moschner. The system accommodates 64 adaptive weight channels with 8-bit resolution for each weight. Internal weight update arithmetic is performed with 16-bit resolution, and the system error signal is measured with 12-bit resolution. An adapt cycle of adjusting all 64 weight channels is accomplished in 8 ..mu..sec. Hardware of the signal processor utilizes primarily Schottky-TTL type integrated circuits. A prototype system with 24 weight channels has been constructed and tested. This report presents details of the system design and describes basic experiments performed with the prototype signal processor. Finally some system configurations and applications for this adaptive signal processor are discussed.

  14. Adaptive signal processor

    International Nuclear Information System (INIS)

    Walz, H.V.

    1980-07-01

    An experimental, general purpose adaptive signal processor system has been developed, utilizing a quantized (clipped) version of the Widrow-Hoff least-mean-square adaptive algorithm developed by Moschner. The system accommodates 64 adaptive weight channels with 8-bit resolution for each weight. Internal weight update arithmetic is performed with 16-bit resolution, and the system error signal is measured with 12-bit resolution. An adapt cycle of adjusting all 64 weight channels is accomplished in 8 μsec. Hardware of the signal processor utilizes primarily Schottky-TTL type integrated circuits. A prototype system with 24 weight channels has been constructed and tested. This report presents details of the system design and describes basic experiments performed with the prototype signal processor. Finally some system configurations and applications for this adaptive signal processor are discussed

  15. Locally-adaptive Myriad Filters for Processing ECG Signals in Real Time

    Directory of Open Access Journals (Sweden)

    Nataliya Tulyakova

    2017-03-01

    Full Text Available The locally adaptive myriad filters to suppress noise in electrocardiographic (ECG signals in almost in real time are proposed. Statistical estimates of efficiency according to integral values of such criteria as mean square error (MSE and signal-to-noise ratio (SNR for the test ECG signals sampled at 400 Hz embedded in additive Gaussian noise with different values of variance are obtained. Comparative analysis of adaptive filters is carried out. High efficiency of ECG filtering and high quality of signal preservation are demonstrated. It is shown that locally adaptive myriad filters provide higher degree of suppressing additive Gaussian noise with possibility of real time implementation.

  16. Experimental verification of preset time count rate meters based on adaptive digital signal processing algorithms

    Directory of Open Access Journals (Sweden)

    Žigić Aleksandar D.

    2005-01-01

    Full Text Available Experimental verifications of two optimized adaptive digital signal processing algorithms implemented in two pre set time count rate meters were per formed ac cording to appropriate standards. The random pulse generator realized using a personal computer, was used as an artificial radiation source for preliminary system tests and performance evaluations of the pro posed algorithms. Then measurement results for background radiation levels were obtained. Finally, measurements with a natural radiation source radioisotope 90Sr-90Y, were carried out. Measurement results, con ducted without and with radio isotopes for the specified errors of 10% and 5% showed to agree well with theoretical predictions.

  17. Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

    Energy Technology Data Exchange (ETDEWEB)

    Chai, Tianyou; Jia, Yao; Wang, Hong; Su, Chun-Yi

    2017-07-09

    The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperature are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.

  18. Compensation for the signal processing characteristics of ultrasound B-mode scanners in adaptive speckle reduction.

    Science.gov (United States)

    Crawford, D C; Bell, D S; Bamber, J C

    1993-01-01

    A systematic method to compensate for nonlinear amplification of individual ultrasound B-scanners has been investigated in order to optimise performance of an adaptive speckle reduction (ASR) filter for a wide range of clinical ultrasonic imaging equipment. Three potential methods have been investigated: (1) a method involving an appropriate selection of the speckle recognition feature was successful when the scanner signal processing executes simple logarithmic compressions; (2) an inverse transform (decompression) of the B-mode image was effective in correcting for the measured characteristics of image data compression when the algorithm was implemented in full floating point arithmetic; (3) characterising the behaviour of the statistical speckle recognition feature under conditions of speckle noise was found to be the method of choice for implementation of the adaptive speckle reduction algorithm in limited precision integer arithmetic. In this example, the statistical features of variance and mean were investigated. The third method may be implemented on commercially available fast image processing hardware and is also better suited for transfer into dedicated hardware to facilitate real-time adaptive speckle reduction. A systematic method is described for obtaining ASR calibration data from B-mode images of a speckle producing phantom.

  19. Adaptive Signal Processing Testbed: VME-based DSP board market survey

    Science.gov (United States)

    Ingram, Rick E.

    1992-04-01

    The Adaptive Signal Processing Testbed (ASPT) is a real-time multiprocessor system utilizing digital signal processor technology on VMEbus based printed circuit boards installed on a Sun workstation. The ASPT has specific requirements, particularly as regards to the signal excision application, with respect to interfacing with current and planned data generation equipment, processing of the data, storage to disk of final and intermediate results, and the development tools for applications development and integration into the overall EW/COM computing environment. A prototype ASPT was implemented using three VME-C-30 boards from Applied Silicon. Experience gained during the prototype development led to the conclusions that interprocessor communications capability is the most significant contributor to overall ASPT performance. In addition, the host involvement should be minimized. Boards using different processors were evaluated with respect to the ASPT system requirements, pricing, and availability. Specific recommendations based on various priorities are made as well as recommendations concerning the integration and interaction of various tools developed during the prototype implementation.

  20. Adaptive variational mode decomposition method for signal processing based on mode characteristic

    Science.gov (United States)

    Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

    2018-07-01

    Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

  1. Signal Processing

    International Nuclear Information System (INIS)

    Anon.

    1992-01-01

    Signal processing techniques, extensively used nowadays to maximize the performance of audio and video equipment, have been a key part in the design of hardware and software for high energy physics detectors since pioneering applications in the UA1 experiment at CERN in 1979

  2. Model-based design of self-Adapting networked signal processing systems

    NARCIS (Netherlands)

    Oliveira Filho, J.A. de; Papp, Z.; Djapic, R.; Oostveen, J.C.

    2013-01-01

    The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication,

  3. A New Waveform Signal Processing Method Based on Adaptive Clustering-Genetic Algorithms

    International Nuclear Information System (INIS)

    Noha Shaaban; Fukuzo Masuda; Hidetsugu Morota

    2006-01-01

    We present a fast digital signal processing method for numerical analysis of individual pulses from CdZnTe compound semiconductor detectors. Using Maxi-Mini Distance Algorithm and Genetic Algorithms based discrimination technique. A parametric approach has been used for classifying the discriminated waveforms into a set of clusters each has a similar signal shape with a corresponding pulse height spectrum. A corrected total pulse height spectrum was obtained by applying a normalization factor for the full energy peak for each cluster with a highly improvements in the energy spectrum characteristics. This method applied successfully for both simulated and real measured data, it can be applied to any detector suffers from signal shape variation. (authors)

  4. Foundations of signal processing

    CERN Document Server

    Vetterli, Martin; Goyal, Vivek K

    2014-01-01

    This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression. The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localisation, the limitations of uncertainty and computational costs. Standard engineering notation is used throughout, making mathematical examples easy for students to follow, understand and apply. It includes over 150 homework problems and over 180 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, ...

  5. Development of an Advanced, Automatic, Ultrasonic NDE Imaging System via Adaptive Learning Network Signal Processing Techniques

    Science.gov (United States)

    1981-03-13

    UNCLASSIFIED SECURITY CLAS,:FtfC ’i OF TH*!’ AGC W~ct P- A* 7~9r1) 0. ABSTRACT (continued) onuing in concert with a sophisticated detector has...and New York, 1969. Whalen, M.F., L.J. O’Brien, and A.N. Mucciardi, "Application of Adaptive Learning Netowrks for the Characterization of Two

  6. Collective Signal Processing in Cluster Chemotaxis: Roles of Adaptation, Amplification, and Co-attraction in Collective Guidance

    Science.gov (United States)

    Camley, Brian A.; Zimmermann, Juliane; Levine, Herbert; Rappel, Wouter-Jan

    2016-01-01

    Single eukaryotic cells commonly sense and follow chemical gradients, performing chemotaxis. Recent experiments and theories, however, show that even when single cells do not chemotax, clusters of cells may, if their interactions are regulated by the chemoattractant. We study this general mechanism of “collective guidance” computationally with models that integrate stochastic dynamics for individual cells with biochemical reactions within the cells, and diffusion of chemical signals between the cells. We show that if clusters of cells use the well-known local excitation, global inhibition (LEGI) mechanism to sense chemoattractant gradients, the speed of the cell cluster becomes non-monotonic in the cluster’s size—clusters either larger or smaller than an optimal size will have lower speed. We argue that the cell cluster speed is a crucial readout of how the cluster processes chemotactic signals; both amplification and adaptation will alter the behavior of cluster speed as a function of size. We also show that, contrary to the assumptions of earlier theories, collective guidance does not require persistent cell-cell contacts and strong short range adhesion. If cell-cell adhesion is absent, and the cluster cohesion is instead provided by a co-attraction mechanism, e.g. chemotaxis toward a secreted molecule, collective guidance may still function. However, new behaviors, such as cluster rotation, may also appear in this case. Co-attraction and adaptation allow for collective guidance that is robust to varying chemoattractant concentrations while not requiring strong cell-cell adhesion. PMID:27367541

  7. The newest digital signal processing

    International Nuclear Information System (INIS)

    Lee, Chae Uk

    2002-08-01

    This book deal with the newest digital signal processing, which contains introduction on conception of digital signal processing, constitution and purpose, signal and system such as signal, continuos signal, discrete signal and discrete system, I/O expression on impress response, convolution, mutual connection of system and frequency character,z transform of definition, range, application of z transform and relationship with laplace transform, Discrete fourier, Fast fourier transform on IDFT algorithm and FFT application, foundation of digital filter of notion, expression, types, frequency characteristic of digital filter and design order of filter, Design order of filter, Design of FIR digital filter, Design of IIR digital filter, Adaptive signal processing, Audio signal processing, video signal processing and application of digital signal processing.

  8. Basic digital signal processing

    CERN Document Server

    Lockhart, Gordon B

    1985-01-01

    Basic Digital Signal Processing describes the principles of digital signal processing and experiments with BASIC programs involving the fast Fourier theorem (FFT). The book reviews the fundamentals of the BASIC program, continuous and discrete time signals including analog signals, Fourier analysis, discrete Fourier transform, signal energy, power. The text also explains digital signal processing involving digital filters, linear time-variant systems, discrete time unit impulse, discrete-time convolution, and the alternative structure for second order infinite impulse response (IIR) sections.

  9. Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

    Directory of Open Access Journals (Sweden)

    Denis Delisle-Rodriguez

    2017-11-01

    Full Text Available This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs based on Canonical Correlation Analysis (CCA to recognize 40 targets of steady-state visual evoked potential (SSVEP, providing an accuracy (ACC of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly ( p < 0.01 improved for most of the subjects ( A C C ≥ 74.79 % , when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry.

  10. Digital signal processing for NDT

    International Nuclear Information System (INIS)

    Georgel, B.

    1994-01-01

    NDT begins to adapt and use the most recent developments of digital signal and image processing. We briefly sum up the main characteristics of NDT situations (particularly noise and inverse problem formulation) and comment on techniques already used or just emerging (SAFT, split spectrum, adaptive learning network, noise reference filtering, stochastic models, neural networks). This survey is focused on ultrasonics, eddy currents and X-ray radiography. The final objective of end users (availability of automatic diagnosis systems) cannot be achieved only by signal processing algorithms. A close cooperation with other techniques such as artificial intelligence has therefore to be implemented. (author). 20 refs

  11. A universal electronical adaptation of automats for biochemical analysis to a central processing computer by applying CAMAC-signals

    International Nuclear Information System (INIS)

    Schaefer, R.

    1975-01-01

    A universal expansion of a CAMAC-subsystem - BORER 3000 - for adapting analysis instruments in biochemistry to a processing computer is described. The possibility of standardizing input interfaces for lab instruments with such circuits is discussed and the advantages achieved by applying the CAMAC-specifications are described

  12. A dynamic dual role of IL-2 signaling in the two-step differentiation process of adaptive regulatory T cells.

    Science.gov (United States)

    Guo, Zhiyong; Khattar, Mithun; Schroder, Paul M; Miyahara, Yoshihiro; Wang, Guohua; He, Xiaoshung; Chen, Wenhao; Stepkowski, Stanislaw M

    2013-04-01

    The molecular mechanism of the extrathymic generation of adaptive, or inducible, CD4(+)Foxp3(+) regulatory T cells (iTregs) remains incompletely defined. We show that exposure of splenic CD4(+)CD25(+)Foxp3(-) cells to IL-2, but not other common γ-chain cytokines, resulted in Stat5 phosphorylation and induced Foxp3 expression in ∼10% of the cells. Thus, IL-2/Stat5 signaling may be critical for Foxp3 induction in peripheral CD4(+)CD25(+)Foxp3(-) iTreg precursors. In this study, to further define the role of IL-2 in the formation of iTreg precursors as well as their subsequent Foxp3 expression, we designed a two-step iTreg differentiation model. During the initial "conditioning" step, CD4(+)CD25(-)Foxp3(-) naive T cells were activated by TCR stimulation. Inhibition of IL-2 signaling via Jak3-Stat5 was required during this step to generate CD4(+)CD25(+)Foxp3(-) cells containing iTreg precursors. During the subsequent Foxp3-induction step driven by cytokines, IL-2 was the most potent cytokine to induce Foxp3 expression in these iTreg precursors. This two-step method generated a large number of iTregs with relatively stable expression of Foxp3, which were able to prevent CD4(+)CD45RB(high) cell-mediated colitis in Rag1(-/-) mice. In consideration of this information, whereas initial inhibition of IL-2 signaling upon T cell priming generates iTreg precursors, subsequent activation of IL-2 signaling in these precursors induces the expression of Foxp3. These findings advance the understanding of iTreg differentiation and may facilitate the therapeutic use of iTregs in immune disorders.

  13. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  14. Adaptive Processes in Hearing

    DEFF Research Database (Denmark)

    Santurette, Sébastien; Christensen-Dalsgaard, Jakob; Tranebjærg, Lisbeth

    2018-01-01

    , and is essential to achieve successful speech communication, correct orientation in our full environment, and eventually survival. These adaptive processes may differ in individuals with hearing loss, whose auditory system may cope via ‘‘readapting’’ itself over a longer time scale to the changes in sensory input...... induced by hearing impairment and the compensation provided by hearing devices. These devices themselves are now able to adapt to the listener’s individual environment, attentional state, and behavior. These topics related to auditory adaptation, in the broad sense of the term, were central to the 6th...... International Symposium on Auditory and Audiological Research held in Nyborg, Denmark, in August 2017. The symposium addressed adaptive processes in hearing from different angles, together with a wide variety of other auditory and audiological topics. The papers in this special issue result from some...

  15. Adaptive Evolution of Signaling Partners

    Science.gov (United States)

    Urano, Daisuke; Dong, Taoran; Bennetzen, Jeffrey L.; Jones, Alan M.

    2015-01-01

    Proteins that interact coevolve their structures. When mutation disrupts the interaction, compensation by the partner occurs to restore interaction otherwise counterselection occurs. We show in this study how a destabilizing mutation in one protein is compensated by a stabilizing mutation in its protein partner and their coevolving path. The pathway in this case and likely a general principle of coevolution is that the compensatory change must tolerate both the original and derived structures with equivalence in function and activity. Evolution of the structure of signaling elements in a network is constrained by specific protein pair interactions, by requisite conformational changes, and by catalytic activity. The heterotrimeric G protein-coupled signaling is a paragon of this protein interaction/function complexity and our deep understanding of this pathway in diverse organisms lends itself to evolutionary study. Regulators of G protein Signaling (RGS) proteins accelerate the intrinsic GTP hydrolysis rate of the Gα subunit of the heterotrimeric G protein complex. An important RGS-contact site is a hydroxyl-bearing residue on the switch I region of Gα subunits in animals and most plants, such as Arabidopsis. The exception is the grasses (e.g., rice, maize, sugarcane, millets); these plants have Gα subunits that replaced the critical hydroxyl-bearing threonine with a destabilizing asparagine shown to disrupt interaction between Arabidopsis RGS protein (AtRGS1) and the grass Gα subunit. With one known exception (Setaria italica), grasses do not encode RGS genes. One parsimonious deduction is that the RGS gene was lost in the ancestor to the grasses and then recently acquired horizontally in the lineage S. italica from a nongrass monocot. Like all investigated grasses, S. italica has the Gα subunit with the destabilizing asparagine residue in the protein interface but, unlike other known grass genomes, still encodes an expressed RGS gene, SiRGS1. SiRGS1

  16. Radiation signal processing system

    International Nuclear Information System (INIS)

    Bennett, M.; Knoll, G.; Strange, D.

    1980-01-01

    An improved signal processing system for radiation imaging apparatus comprises: a radiation transducer producing transducer signals proportional to apparent spatial coordinates of detected radiation events; means for storing true spatial coordinates corresponding to a plurality of predetermined apparent spatial coordinates relative to selected detected radiation events said means for storing responsive to said transducer signal and producing an output signal representative of said true spatial coordinates; and means for interpolating the true spatial coordinates of the detected radiation events located intermediate the stored true spatial coordinates, said means for interpolating communicating with said means for storing

  17. Digital signal processing

    CERN Document Server

    O'Shea, Peter; Hussain, Zahir M

    2011-01-01

    In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis. It also treats important applications including signal detection in noise, radar range estimation for airborne targets, binary communication systems, channel estimation, banking and financial applications, and audio effects production. Part II considers sel

  18. Acoustic MIMO signal processing

    CERN Document Server

    Huang, Yiteng; Chen, Jingdong

    2006-01-01

    A timely and important book addressing a variety of acoustic signal processing problems under multiple-input multiple-output (MIMO) scenarios. It uniquely investigates these problems within a unified framework offering a novel and penetrating analysis.

  19. Ultrahigh bandwidth signal processing

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo

    2016-01-01

    Optical time lenses have proven to be very versatile for advanced optical signal processing. Based on a controlled interplay between dispersion and phase-modulation by e.g. four-wave mixing, the processing is phase-preserving, an hence useful for all types of data signals including coherent multi......-level modulation founats. This has enabled processing of phase-modulated spectrally efficient data signals, such as orthogonal frequency division multiplexed (OFDM) signa In that case, a spectral telescope system was used, using two time lenses with different focal lengths (chirp rates), yielding a spectral...... regeneratio These operations require a broad bandwidth nonlinear platform, and novel photonic integrated nonlinear platform like aluminum gallium arsenide nano-waveguides used for 1.28 Tbaud optical signal processing will be described....

  20. Topological signal processing

    CERN Document Server

    Robinson, Michael

    2014-01-01

    Signal processing is the discipline of extracting information from collections of measurements. To be effective, the measurements must be organized and then filtered, detected, or transformed to expose the desired information.  Distortions caused by uncertainty, noise, and clutter degrade the performance of practical signal processing systems. In aggressively uncertain situations, the full truth about an underlying signal cannot be known.  This book develops the theory and practice of signal processing systems for these situations that extract useful, qualitative information using the mathematics of topology -- the study of spaces under continuous transformations.  Since the collection of continuous transformations is large and varied, tools which are topologically-motivated are automatically insensitive to substantial distortion. The target audience comprises practitioners as well as researchers, but the book may also be beneficial for graduate students.

  1. Error signals driving locomotor adaptation

    DEFF Research Database (Denmark)

    Choi, Julia T; Jensen, Peter; Nielsen, Jens Bo

    2016-01-01

    Locomotor patterns must be adapted to external forces encountered during daily activities. The contribution of different sensory inputs to detecting perturbations and adapting movements during walking is unclear. Here we examined the role of cutaneous feedback in adapting walking patterns to force...... walking (Choi et al. 2013). Sensory tests were performed to measure cutaneous touch threshold and perceptual threshold of force perturbations. Ankle movement were measured while subjects walked on the treadmill over three periods: baseline (1 min), adaptation (1 min) and post-adaptation (3 min). Subjects...

  2. VLSI signal processing technology

    CERN Document Server

    Swartzlander, Earl

    1994-01-01

    This book is the first in a set of forthcoming books focussed on state-of-the-art development in the VLSI Signal Processing area. It is a response to the tremendous research activities taking place in that field. These activities have been driven by two factors: the dramatic increase in demand for high speed signal processing, especially in consumer elec­ tronics, and the evolving microelectronic technologies. The available technology has always been one of the main factors in determining al­ gorithms, architectures, and design strategies to be followed. With every new technology, signal processing systems go through many changes in concepts, design methods, and implementation. The goal of this book is to introduce the reader to the main features of VLSI Signal Processing and the ongoing developments in this area. The focus of this book is on: • Current developments in Digital Signal Processing (DSP) pro­ cessors and architectures - several examples and case studies of existing DSP chips are discussed in...

  3. Mitochondrial Stress Signaling Promotes Cellular Adaptations

    Directory of Open Access Journals (Sweden)

    Jayne Alexandra Barbour

    2014-01-01

    Full Text Available Mitochondrial dysfunction has been implicated in the aetiology of many complex diseases, as well as the ageing process. Much of the research on mitochondrial dysfunction has focused on how mitochondrial damage may potentiate pathological phenotypes. The purpose of this review is to draw attention to the less well-studied mechanisms by which the cell adapts to mitochondrial perturbations. This involves communication of stress to the cell and successful induction of quality control responses, which include mitophagy, unfolded protein response, upregulation of antioxidant and DNA repair enzymes, morphological changes, and if all else fails apoptosis. The mitochondrion is an inherently stressful environment and we speculate that dysregulation of stress signaling or an inability to switch on these adaptations during times of mitochondrial stress may underpin mitochondrial dysfunction and hence amount to pathological states over time.

  4. Signal processing in microdosimetry

    International Nuclear Information System (INIS)

    Arbel, A.

    1984-01-01

    Signals occurring in microdosimetric measurements cover a dynamic range of 100 dB at a counting rate which normally stays below 10 4 but could increase significantly in case of an accident. The need for high resolution at low energies, non-linear signal processing to accommodate the specified dynamic range, easy calibration and thermal stability are conflicting requirements which pose formidable design problems. These problems are reviewed, and a practical approach to their solution is given employing a single processing channel. (author)

  5. Genomic signal processing

    CERN Document Server

    Shmulevich, Ilya

    2007-01-01

    Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathema

  6. Television picture signal processing

    NARCIS (Netherlands)

    1998-01-01

    Field or frame memories are often used in television receivers for video signal processing functions, such as noise reduction and/or flicker reduction. Television receivers also have graphic features such as teletext, menu-driven control systems, multilingual subtitling, an electronic TV-Guide, etc.

  7. The Development and Application of Random Matrix Theory in Adaptive Signal Processing in the Sample Deficient Regime

    Science.gov (United States)

    2014-09-01

    been great source of encouragement, support and inspiration thousands of miles away. Mum and Dad , thank you for taking good care of me, for believing in...definition as given in (3.28). 115 Scenario 2: Separated Arrivals with Low SNR in a Snapshot Poor Regime In this scenario, 2 signals are arriving at...whose channel is characterized by rich scattering need to be sufficiently apart so that the signals at their outputs are uncorrelated [20], conventional

  8. Adaptive DCTNet for Audio Signal Classification

    OpenAIRE

    Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

    2016-01-01

    In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to h...

  9. Diagnostic analysis of vibration signals using adaptive digital filtering techniques

    Science.gov (United States)

    Jewell, R. E.; Jones, J. H.; Paul, J. E.

    1983-01-01

    Signal enhancement techniques are described using recently developed digital adaptive filtering equipment. Adaptive filtering concepts are not new; however, as a result of recent advances in microprocessor-based electronics, hardware has been developed that has stable characteristics and of a size exceeding 1000th order. Selected data processing examples are presented illustrating spectral line enhancement, adaptive noise cancellation, and transfer function estimation in the presence of corrupting noise.

  10. Phonocardiography Signal Processing

    CERN Document Server

    Abbas, Abbas K

    2009-01-01

    The auscultation method is an important diagnostic indicator for hemodynamic anomalies. Heart sound classification and analysis play an important role in the auscultative diagnosis. The term phonocardiography refers to the tracing technique of heart sounds and the recording of cardiac acoustics vibration by means of a microphone-transducer. Therefore, understanding the nature and source of this signal is important to give us a tendency for developing a competent tool for further analysis and processing, in order to enhance and optimize cardiac clinical diagnostic approach. This book gives the

  11. Multidimensional Signal Processing for Sensing & Communications

    Science.gov (United States)

    2015-07-29

    Spectrum Sensing,” submitted to IEEE Intl. Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Mexico , 13-16 Dec. 2015...Sensing,” submitted to IEEE Intl. Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Cancun, Mexico , 13-16 Dec. 2015...diversity in echolocating mammals ,” IEEE Signal Processing Magazine, vol. 26, no. 1, pp. 65- 75, Jan. 2009. DISTRIBUTION A: Distribution approved for

  12. Signal Processing and Neural Network Simulator

    Science.gov (United States)

    Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

    1995-04-01

    The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

  13. ECG signal processing

    NARCIS (Netherlands)

    2009-01-01

    A system extracts an ECG signal from a composite signal (308) representing an electric measurement of a living subject. Identification means (304) identify a plurality of temporal segments (309) of the composite signal corresponding to a plurality of predetermined segments (202,204,206) of an ECG

  14. Biomedical signal and image processing

    CERN Document Server

    Najarian, Kayvan

    2012-01-01

    INTRODUCTION TO DIGITAL SIGNAL AND IMAGE PROCESSINGSignals and Biomedical Signal ProcessingIntroduction and OverviewWhat is a ""Signal""?Analog, Discrete, and Digital SignalsProcessing and Transformation of SignalsSignal Processing for Feature ExtractionSome Characteristics of Digital ImagesSummaryProblemsFourier TransformIntroduction and OverviewOne-Dimensional Continuous Fourier TransformSampling and NYQUIST RateOne-Dimensional Discrete Fourier TransformTwo-Dimensional Discrete Fourier TransformFilter DesignSummaryProblemsImage Filtering, Enhancement, and RestorationIntroduction and Overview

  15. Machine intelligence and signal processing

    CERN Document Server

    Vatsa, Mayank; Majumdar, Angshul; Kumar, Ajay

    2016-01-01

    This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning – instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning). And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intel...

  16. Underwater Acoustic Signal Processing

    National Research Council Canada - National Science Library

    Culver, Richard L; Sibul, Leon H; Bradley, David L

    2007-01-01

    .... The research is directed toward passive sonar detection and classification, continuous wave (CW) and broadband signals, shallow water operation, both platform-mounted and distributed systems, and frequencies below 1 kHz...

  17. Digital signal processing the Tevatron BPM signals

    International Nuclear Information System (INIS)

    Cancelo, G.; James, E.; Wolbers, S.

    2005-01-01

    The Beam Position Monitor (TeV BPM) readout system at Fermilab's Tevatron has been updated and is currently being commissioned. The new BPMs use new analog and digital hardware to achieve better beam position measurement resolution. The new system reads signals from both ends of the existing directional stripline pickups to provide simultaneous proton and antiproton measurements. The signals provided by the two ends of the BPM pickups are processed by analog band-pass filters and sampled by 14-bit ADCs at 74.3MHz. A crucial part of this work has been the design of digital filters that process the signal. This paper describes the digital processing and estimation techniques used to optimize the beam position measurement. The BPM electronics must operate in narrow-band and wide-band modes to enable measurements of closed-orbit and turn-by-turn positions. The filtering and timing conditions of the signals are tuned accordingly for the operational modes. The analysis and the optimized result for each mode are presented

  18. Signal processing for radiation detectors

    CERN Document Server

    Nakhostin, Mohammad

    2018-01-01

    This book provides a clear understanding of the principles of signal processing of radiation detectors. It puts great emphasis on the characteristics of pulses from various types of detectors and offers a full overview on the basic concepts required to understand detector signal processing systems and pulse processing techniques. Signal Processing for Radiation Detectors covers all of the important aspects of signal processing, including energy spectroscopy, timing measurements, position-sensing, pulse-shape discrimination, and radiation intensity measurement. The book encompasses a wide range of applications so that readers from different disciplines can benefit from all of the information. In addition, this resource: * Describes both analog and digital techniques of signal processing * Presents a complete compilation of digital pulse processing algorithms * Extrapolates content from more than 700 references covering classic papers as well as those of today * Demonstrates concepts with more than 340 origin...

  19. Resource-adaptive cognitive processes

    CERN Document Server

    Crocker, Matthew W

    2010-01-01

    This book investigates the adaptation of cognitive processes to limited resources. The central topics of this book are heuristics considered as results of the adaptation to resource limitations, through natural evolution in the case of humans, or through artificial construction in the case of computational systems; the construction and analysis of resource control in cognitive processes; and an analysis of resource-adaptivity within the paradigm of concurrent computation. The editors integrated the results of a collaborative 5-year research project that involved over 50 scientists. After a mot

  20. Adaptive Beamforming Based on Complex Quaternion Processes

    Directory of Open Access Journals (Sweden)

    Jian-wu Tao

    2014-01-01

    Full Text Available Motivated by the benefits of array signal processing in quaternion domain, we investigate the problem of adaptive beamforming based on complex quaternion processes in this paper. First, a complex quaternion least-mean squares (CQLMS algorithm is proposed and its performance is analyzed. The CQLMS algorithm is suitable for adaptive beamforming of vector-sensor array. The weight vector update of CQLMS algorithm is derived based on the complex gradient, leading to lower computational complexity. Because the complex quaternion can exhibit the orthogonal structure of an electromagnetic vector-sensor in a natural way, a complex quaternion model in time domain is provided for a 3-component vector-sensor array. And the normalized adaptive beamformer using CQLMS is presented. Finally, simulation results are given to validate the performance of the proposed adaptive beamformer.

  1. Fundamentals of statistical signal processing

    CERN Document Server

    Kay, Steven M

    1993-01-01

    A unified presentation of parameter estimation for those involved in the design and implementation of statistical signal processing algorithms. Covers important approaches to obtaining an optimal estimator and analyzing its performance; and includes numerous examples as well as applications to real- world problems. MARKETS: For practicing engineers and scientists who design and analyze signal processing systems, i.e., to extract information from noisy signals — radar engineer, sonar engineer, geophysicist, oceanographer, biomedical engineer, communications engineer, economist, statistician, physicist, etc.

  2. Principles of Adaptive Array Processing

    Science.gov (United States)

    2006-09-01

    ACE with and without tapering (homogeneous case). These analytical results are less suited to predict the detection performance of a real system ...Nickel: Adaptive Beamforming for Phased Array Radars. Proc. Int. Radar Symposium IRS’98 (Munich, Sept. 1998), DGON and VDE /ITG, pp. 897-906.(Reprint also...strategies for airborne radar. Asilomar Conf. on Signals, Systems and Computers, Pacific Grove, CA, 1998, IEEE Cat.Nr. 0-7803-5148-7/98, pp. 1327-1331. [17

  3. Statistical-uncertainty-based adaptive filtering of lidar signals

    International Nuclear Information System (INIS)

    Fuehrer, P. L.; Friehe, C. A.; Hristov, T. S.; Cooper, D. I.; Eichinger, W. E.

    2000-01-01

    An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometerological humidity data were used to calibrate the ratio of the lidar gains of the H 2 O and the N 2 photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem. (c) 2000 Optical Society of America

  4. Symbolic signal processing

    International Nuclear Information System (INIS)

    Rechester, A.B.; White, R.B.

    1993-01-01

    Complex dynamic processes exhibit many complicated patterns of evolution. How can all these patterns be recognized using only output (observational, experimental) data without prior knowledge of the equations of motion? The powerful method for doing this is based on symbolic dynamics: (1) Present output data in symbolic form (trial language). (2) Topological and metric entropies are constructed. (3) Develop algorithms for computer optimization of entropies. (4) By maximizing entropies, find the most appropriate symbolic language for the purpose of pattern recognition. (5) Test this method using a variety of dynamical models from nonlinear science. The authors are in the process of applying this method for analysis of MHD fluctuations in tokamaks

  5. Digital Signal Processing applied to Physical Signals

    CERN Document Server

    Alberto, Diego; Musa, L

    2011-01-01

    It is well known that many of the scientific and technological discoveries of the XXI century will depend on the capability of processing and understanding a huge quantity of data. With the advent of the digital era, a fully digital and automated treatment can be designed and performed. From data mining to data compression, from signal elaboration to noise reduction, a processing is essential to manage and enhance features of interest after every data acquisition (DAQ) session. In the near future, science will go towards interdisciplinary research. In this work there will be given an example of the application of signal processing to different fields of Physics from nuclear particle detectors to biomedical examinations. In Chapter 1 a brief description of the collaborations that allowed this thesis is given, together with a list of the publications co-produced by the author in these three years. The most important notations, definitions and acronyms used in the work are also provided. In Chapter 2, the last r...

  6. Sensor array signal processing

    CERN Document Server

    Naidu, Prabhakar S

    2009-01-01

    Chapter One: An Overview of Wavefields 1.1 Types of Wavefields and the Governing Equations 1.2 Wavefield in open space 1.3 Wavefield in bounded space 1.4 Stochastic wavefield 1.5 Multipath propagation 1.6 Propagation through random medium 1.7 ExercisesChapter Two: Sensor Array Systems 2.1 Uniform linear array (ULA) 2.2 Planar array 2.3 Distributed sensor array 2.4 Broadband sensor array 2.5 Source and sensor arrays 2.6 Multi-component sensor array2.7 ExercisesChapter Three: Frequency Wavenumber Processing 3.1 Digital filters in the w-k domain 3.2 Mapping of 1D into 2D filters 3.3 Multichannel Wiener filters 3.4 Wiener filters for ULA and UCA 3.5 Predictive noise cancellation 3.6 Exercises Chapter Four: Source Localization: Frequency Wavenumber Spectrum4.1 Frequency wavenumber spectrum 4.2 Beamformation 4.3 Capon's w-k spectrum 4.4 Maximum entropy w-k spectrum 4.5 Doppler-Azimuth Processing4.6 ExercisesChapter Five: Source Localization: Subspace Methods 5.1 Subspace methods (Narrowband) 5.2 Subspace methods (B...

  7. Necroptotic signaling in adaptive and innate immunity.

    Science.gov (United States)

    Lu, Jennifer V; Chen, Helen C; Walsh, Craig M

    2014-11-01

    The vertebrate immune system is highly dependent on cell death for efficient responsiveness to microbial pathogens and oncogenically transformed cells. Cell death pathways are vital to the function of many immune cell types during innate, humoral and cellular immune responses. In addition, cell death regulation is imperative for proper adaptive immune self-tolerance and homeostasis. While apoptosis has been found to be involved in several of these roles in immunity, recent data demonstrate that alternative cell death pathways are required. Here, we describe the involvement of a programmed form of cellular necrosis called "necroptosis" in immunity. We consider the signaling pathways that promote necroptosis downstream of death receptors, type I transmembrane proteins of the tumor necrosis factor (TNF) receptor family. The involvement of necroptotic signaling through a "RIPoptosome" assembled in response to innate immune stimuli or genotoxic stress is described. We also characterize the induction of necroptosis following antigenic stimulation in T cells lacking caspase-8 or FADD function. While necroptotic signaling remains poorly understood, it is clear that this pathway is an essential component to effective vertebrate immunity. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Linear ubiquitination signals in adaptive immune responses.

    Science.gov (United States)

    Ikeda, Fumiyo

    2015-07-01

    Ubiquitin can form eight different linkage types of chains using the intrinsic Met 1 residue or one of the seven intrinsic Lys residues. Each linkage type of ubiquitin chain has a distinct three-dimensional topology, functioning as a tag to attract specific signaling molecules, which are so-called ubiquitin readers, and regulates various biological functions. Ubiquitin chains linked via Met 1 in a head-to-tail manner are called linear ubiquitin chains. Linear ubiquitination plays an important role in the regulation of cellular signaling, including the best-characterized tumor necrosis factor (TNF)-induced canonical nuclear factor-κB (NF-κB) pathway. Linear ubiquitin chains are specifically generated by an E3 ligase complex called the linear ubiquitin chain assembly complex (LUBAC) and hydrolyzed by a deubiquitinase (DUB) called ovarian tumor (OTU) DUB with linear linkage specificity (OTULIN). LUBAC linearly ubiquitinates critical molecules in the TNF pathway, such as NEMO and RIPK1. The linear ubiquitin chains are then recognized by the ubiquitin readers, including NEMO, which control the TNF pathway. Accumulating evidence indicates an importance of the LUBAC complex in the regulation of apoptosis, development, and inflammation in mice. In this article, I focus on the role of linear ubiquitin chains in adaptive immune responses with an emphasis on the TNF-induced signaling pathways. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. Neural Adaptation Effects in Conceptual Processing

    Directory of Open Access Journals (Sweden)

    Barbara F. M. Marino

    2015-07-01

    Full Text Available We investigated the conceptual processing of nouns referring to objects characterized by a highly typical color and orientation. We used a go/no-go task in which we asked participants to categorize each noun as referring or not to natural entities (e.g., animals after a selective adaptation of color-edge neurons in the posterior LV4 region of the visual cortex was induced by means of a McCollough effect procedure. This manipulation affected categorization: the green-vertical adaptation led to slower responses than the green-horizontal adaptation, regardless of the specific color and orientation of the to-be-categorized noun. This result suggests that the conceptual processing of natural entities may entail the activation of modality-specific neural channels with weights proportional to the reliability of the signals produced by these channels during actual perception. This finding is discussed with reference to the debate about the grounded cognition view.

  10. SignalPlant: an open signal processing software platform.

    Science.gov (United States)

    Plesinger, F; Jurco, J; Halamek, J; Jurak, P

    2016-07-01

    The growing technical standard of acquisition systems allows the acquisition of large records, often reaching gigabytes or more in size as is the case with whole-day electroencephalograph (EEG) recordings, for example. Although current 64-bit software for signal processing is able to process (e.g. filter, analyze, etc) such data, visual inspection and labeling will probably suffer from rather long latency during the rendering of large portions of recorded signals. For this reason, we have developed SignalPlant-a stand-alone application for signal inspection, labeling and processing. The main motivation was to supply investigators with a tool allowing fast and interactive work with large multichannel records produced by EEG, electrocardiograph and similar devices. The rendering latency was compared with EEGLAB and proves significantly faster when displaying an image from a large number of samples (e.g. 163-times faster for 75  ×  10(6) samples). The presented SignalPlant software is available free and does not depend on any other computation software. Furthermore, it can be extended with plugins by third parties ensuring its adaptability to future research tasks and new data formats.

  11. Handbook of signal processing systems

    CERN Document Server

    Deprettere, Ed; Leupers, Rainer; Takala, Jarmo

    2013-01-01

    Handbook of Signal Processing Systems is organized in three parts. The first part motivates representative applications that drive and apply state-of-the art methods for design and implementation of signal processing systems; the second part discusses architectures for implementing these applications; the third part focuses on compilers and simulation tools, describes models of computation and their associated design tools and methodologies. This handbook is an essential tool for professionals in many fields and researchers of all levels.

  12. Digital signal processing theory and practice

    CERN Document Server

    Rao, K Deergha

    2018-01-01

    The book provides a comprehensive exposition of all major topics in digital signal processing (DSP). With numerous illustrative examples for easy understanding of the topics, it also includes MATLAB-based examples with codes in order to encourage the readers to become more confident of the fundamentals and to gain insights into DSP. Further, it presents real-world signal processing design problems using MATLAB and programmable DSP processors. In addition to problems that require analytical solutions, it discusses problems that require solutions using MATLAB at the end of each chapter. Divided into 13 chapters, it addresses many emerging topics, which are not typically found in advanced texts on DSP. It includes a chapter on adaptive digital filters used in the signal processing problems for faster acceptable results in the presence of changing environments and changing system requirements. Moreover, it offers an overview of wavelets, enabling readers to easily understand the basics and applications of this po...

  13. The process of organisational adaptation through innovations, and organisational adaptability

    OpenAIRE

    Tikka, Tommi

    2010-01-01

    This study is about the process of organisational adaptation and organisational adaptability. The study generates a theoretical framework about organisational adaptation behaviour and conditions that have influence on success of organisational adaptation. The research questions of the study are: How does an organisation adapt through innovations, and which conditions enhance or impede organisational adaptation through innovations? The data were gathered from five case organisations withi...

  14. Biomedical signal and image processing.

    Science.gov (United States)

    Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro

    2011-01-01

    Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.

  15. Proceedings of the IEEE Machine Learning for Signal Processing XVII

    DEFF Research Database (Denmark)

    The seventeenth of a series of workshops sponsored by the IEEE Signal Processing Society and organized by the Machine Learning for Signal Processing Technical Committee (MLSP-TC). The field of machine learning has matured considerably in both methodology and real-world application domains and has...... become particularly important for solution of problems in signal processing. As reflected in this collection, machine learning for signal processing combines many ideas from adaptive signal/image processing, learning theory and models, and statistics in order to solve complex real-world signal processing......, and two papers from the winners of the Data Analysis Competition. The program included papers in the following areas: genomic signal processing, pattern recognition and classification, image and video processing, blind signal processing, models, learning algorithms, and applications of machine learning...

  16. Signal processing for cognitive radios

    CERN Document Server

    Jayaweera, Sudharman K

    2014-01-01

    This book covers power electronics, in depth, by presenting the basic principles and application details, and it can be used both as a textbook and reference book.  Introduces the specific type of CR that has gained the most research attention in recent years: the CR for Dynamic Spectrum Access (DSA). Provides signal processing solutions to each task by relating the tasks to materials covered in Part II. Specialized chapters then discuss specific signal processing algorithms required for DSA and DSS cognitive radios  

  17. PSpice for digital signal processing

    CERN Document Server

    Tobin, Paul

    2007-01-01

    PSpice for Digital Signal Processing is the last in a series of five books using Cadence Orcad PSpice version 10.5 and introduces a very novel approach to learning digital signal processing (DSP). DSP is traditionally taught using Matlab/Simulink software but has some inherent weaknesses for students particularly at the introductory level. The 'plug in variables and play' nature of these software packages can lure the student into thinking they possess an understanding they don't actually have because these systems produce results quicklywithout revealing what is going on. However, it must be

  18. Multivariate Analysis for the Processing of Signals

    Directory of Open Access Journals (Sweden)

    Beattie J.R.

    2014-01-01

    Full Text Available Real-world experiments are becoming increasingly more complex, needing techniques capable of tracking this complexity. Signal based measurements are often used to capture this complexity, where a signal is a record of a sample’s response to a parameter (e.g. time, displacement, voltage, wavelength that is varied over a range of values. In signals the responses at each value of the varied parameter are related to each other, depending on the composition or state sample being measured. Since signals contain multiple information points, they have rich information content but are generally complex to comprehend. Multivariate Analysis (MA has profoundly transformed their analysis by allowing gross simplification of the tangled web of variation. In addition MA has also provided the advantage of being much more robust to the influence of noise than univariate methods of analysis. In recent years, there has been a growing awareness that the nature of the multivariate methods allows exploitation of its benefits for purposes other than data analysis, such as pre-processing of signals with the aim of eliminating irrelevant variations prior to analysis of the signal of interest. It has been shown that exploiting multivariate data reduction in an appropriate way can allow high fidelity denoising (removal of irreproducible non-signals, consistent and reproducible noise-insensitive correction of baseline distortions (removal of reproducible non-signals, accurate elimination of interfering signals (removal of reproducible but unwanted signals and the standardisation of signal amplitude fluctuations. At present, the field is relatively small but the possibilities for much wider application are considerable. Where signal properties are suitable for MA (such as the signal being stationary along the x-axis, these signal based corrections have the potential to be highly reproducible, and highly adaptable and are applicable in situations where the data is noisy or

  19. Wavelets and multiscale signal processing

    CERN Document Server

    Cohen, Albert

    1995-01-01

    Since their appearance in mid-1980s, wavelets and, more generally, multiscale methods have become powerful tools in mathematical analysis and in applications to numerical analysis and signal processing. This book is based on "Ondelettes et Traitement Numerique du Signal" by Albert Cohen. It has been translated from French by Robert D. Ryan and extensively updated by both Cohen and Ryan. It studies the existing relations between filter banks and wavelet decompositions and shows how these relations can be exploited in the context of digital signal processing. Throughout, the book concentrates on the fundamentals. It begins with a chapter on the concept of multiresolution analysis, which contains complete proofs of the basic results. The description of filter banks that are related to wavelet bases is elaborated in both the orthogonal case (Chapter 2), and in the biorthogonal case (Chapter 4). The regularity of wavelets, how this is related to the properties of the filters and the importance of regularity for t...

  20. Processing oscillatory signals by incoherent feedforward loops

    Science.gov (United States)

    Zhang, Carolyn; Wu, Feilun; Tsoi, Ryan; Shats, Igor; You, Lingchong

    From the timing of amoeba development to the maintenance of stem cell pluripotency,many biological signaling pathways exhibit the ability to differentiate between pulsatile and sustained signals in the regulation of downstream gene expression.While networks underlying this signal decoding are diverse,many are built around a common motif, the incoherent feedforward loop (IFFL),where an input simultaneously activates an output and an inhibitor of the output.With appropriate parameters,this motif can generate temporal adaptation,where the system is desensitized to a sustained input.This property serves as the foundation for distinguishing signals with varying temporal profiles.Here,we use quantitative modeling to examine another property of IFFLs,the ability to process oscillatory signals.Our results indicate that the system's ability to translate pulsatile dynamics is limited by two constraints.The kinetics of IFFL components dictate the input range for which the network can decode pulsatile dynamics.In addition,a match between the network parameters and signal characteristics is required for optimal ``counting''.We elucidate one potential mechanism by which information processing occurs in natural networks with implications in the design of synthetic gene circuits for this purpose. This work was partially supported by the National Science Foundation Graduate Research Fellowship (CZ).

  1. Adaptive Processing for Sequence Alignment

    KAUST Repository

    Zidan, Mohammed A.; Bonny, Talal; Salama, Khaled N.

    2012-01-01

    Disclosed are various embodiments for adaptive processing for sequence alignment. In one embodiment, among others, a method includes obtaining a query sequence and a plurality of database sequences. A first portion of the plurality of database sequences is distributed to a central processing unit (CPU) and a second portion of the plurality of database sequences is distributed to a graphical processing unit (GPU) based upon a predetermined splitting ratio associated with the plurality of database sequences, where the database sequences of the first portion are shorter than the database sequences of the second portion. A first alignment score for the query sequence is determined with the CPU based upon the first portion of the plurality of database sequences and a second alignment score for the query sequence is determined with the GPU based upon the second portion of the plurality of database sequences.

  2. Adaptive Processing for Sequence Alignment

    KAUST Repository

    Zidan, Mohammed A.

    2012-01-26

    Disclosed are various embodiments for adaptive processing for sequence alignment. In one embodiment, among others, a method includes obtaining a query sequence and a plurality of database sequences. A first portion of the plurality of database sequences is distributed to a central processing unit (CPU) and a second portion of the plurality of database sequences is distributed to a graphical processing unit (GPU) based upon a predetermined splitting ratio associated with the plurality of database sequences, where the database sequences of the first portion are shorter than the database sequences of the second portion. A first alignment score for the query sequence is determined with the CPU based upon the first portion of the plurality of database sequences and a second alignment score for the query sequence is determined with the GPU based upon the second portion of the plurality of database sequences.

  3. RF applications in digital signal processing

    CERN Document Server

    Schilcher, T

    2008-01-01

    Ever higher demands for stability, accuracy, reproducibility, and monitoring capability are being placed on Low-Level Radio Frequency (LLRF) systems of particle accelerators. Meanwhile, continuing rapid advances in digital signal processing technology are being exploited to meet these demands, thus leading to development of digital LLRF systems. The rst part of this course will begin by focusing on some of the important building-blocks of RF signal processing including mixer theory and down-conversion, I/Q (amplitude and phase) detection, digital down-conversion (DDC) and decimation, concluding with a survey of I/Q modulators. The second part of the course will introduce basic concepts of feedback systems, including examples of digital cavity eld and phase control, followed by radial loop architectures. Adaptive feed-forward systems used for the suppression of repetitive beam disturbances will be examined. Finally, applications and principles of system identi cation approaches will be summarized.

  4. Signal processing for smart cards

    Science.gov (United States)

    Quisquater, Jean-Jacques; Samyde, David

    2003-06-01

    In 1998, Paul Kocher showed that when a smart card computes cryptographic algorithms, for signatures or encryption, its consumption or its radiations leak information. The keys or the secrets hidden in the card can then be recovered using a differential measurement based on the intercorrelation function. A lot of silicon manufacturers use desynchronization countermeasures to defeat power analysis. In this article we detail a new resynchronization technic. This method can be used to facilitate the use of a neural network to do the code recognition. It becomes possible to reverse engineer a software code automatically. Using data and clock separation methods, we show how to optimize the synchronization using signal processing. Then we compare these methods with watermarking methods for 1D and 2D signal. The very last watermarking detection improvements can be applied to signal processing for smart cards with very few modifications. Bayesian processing is one of the best ways to do Differential Power Analysis, and it is possible to extract a PIN code from a smart card in very few samples. So this article shows the need to continue to set up effective countermeasures for cryptographic processors. Although the idea to use advanced signal processing operators has been commonly known for a long time, no publication explains that results can be obtained. The main idea of differential measurement is to use the cross-correlation of two random variables and to repeat consumption measurements on the processor to be analyzed. We use two processors clocked at the same external frequency and computing the same data. The applications of our design are numerous. Two measurements provide the inputs of a central operator. With the most accurate operator we can improve the signal noise ratio, re-synchronize the acquisition clock with the internal one, or remove jitter. The analysis based on consumption or electromagnetic measurements can be improved using our structure. At first sight

  5. Fixed-point signal processing

    CERN Document Server

    Padgett, Wayne T

    2009-01-01

    This book is intended to fill the gap between the ""ideal precision"" digital signal processing (DSP) that is widely taught, and the limited precision implementation skills that are commonly required in fixed-point processors and field programmable gate arrays (FPGAs). These skills are often neglected at the university level, particularly for undergraduates. We have attempted to create a resource both for a DSP elective course and for the practicing engineer with a need to understand fixed-point implementation. Although we assume a background in DSP, Chapter 2 contains a review of basic theory

  6. Low power digital signal processing

    DEFF Research Database (Denmark)

    Paker, Ozgun

    2003-01-01

    hardwired ASICs and more than 6 21 times lower than current state of the art low-power DSP processors. An orthogonal but practical contribution of this thesis is the test bench implementation. A PCI-based FPGA board has been used to equip a standard desktop PC with tester facilities. The test bench proved...... to be a viable alternative to conventional expensive test equipment. Finally, the work presented in this thesis has been published at several IEEE workshops and conferences, and in the Journal of VLSI Signal Processing....

  7. Efficient ECG Signal Compression Using Adaptive Heart Model

    National Research Council Canada - National Science Library

    Szilagyi, S

    2001-01-01

    This paper presents an adaptive, heart-model-based electrocardiography (ECG) compression method. After conventional pre-filtering the waves from the signal are localized and the model's parameters are determined...

  8. A simple method to adapt time sampling of the analog signal

    International Nuclear Information System (INIS)

    Kalinin, Yu.G.; Martyanov, I.S.; Sadykov, Kh.; Zastrozhnova, N.N.

    2004-01-01

    In this paper we briefly describe the time sampling method, which is adapted to the speed of the signal change. Principally, this method is based on a simple idea--the combination of discrete integration with differentiation of the analog signal. This method can be used in nuclear electronics research into the characteristics of detectors and the shape of the pulse signal, pulse and transitive characteristics of inertial systems of processing of signals, etc

  9. Advanced digital signal processing and noise reduction

    CERN Document Server

    Vaseghi, Saeed V

    2008-01-01

    Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates an

  10. Adaptive Arrays for Multiple Simultaneous Desired Signals.

    Science.gov (United States)

    1983-08-01

    weights [Equation (4)]. Using Equation (6), the inverse of the covariance matrix is given by 5 4 i *ŕm * T ". -1 1 I d Z dij (7) L -I + UT U* 4 di x di...Equations (11) and (12) p k = A k Ik d (14) dk aki*~~* ( ~ dk LJk Udk) and 1 t IjI II di l() 27 x = (1 + t UT U*) Thus, the output SNR of the kth desired...signals are assumed to be of the same frequency. There is no jammer 9 0 dB SIGNAL 10 dB SIGNAL 90 % 90 180 Fiur .dptdpatrnofalier rayo tn strpc lmet

  11. Experiment and practice on signal processing

    International Nuclear Information System (INIS)

    2002-11-01

    The contents of this book contains basic practice of CEM Tool, discrete time signal and experiment and practice of system, experiment and practice of discrete time signal sampling, practice of frequency analysis, experiment of digital filter design, application of digital signal processing, project related voice, basic principle of signal processing, the technique of basic image signal processing, biology astronomy and Robot soccer with apply of image signal processing technique, control video signal and project related image. It also has an introduction of CEM Linker I. O in the end.

  12. Experiment and practice on signal processing

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2002-11-15

    The contents of this book contains basic practice of CEM Tool, discrete time signal and experiment and practice of system, experiment and practice of discrete time signal sampling, practice of frequency analysis, experiment of digital filter design, application of digital signal processing, project related voice, basic principle of signal processing, the technique of basic image signal processing, biology astronomy and Robot soccer with apply of image signal processing technique, control video signal and project related image. It also has an introduction of CEM Linker I. O in the end.

  13. Digital signal processing using MATLAB

    CERN Document Server

    Schilling, Robert L

    2016-01-01

    Focus on the development, implementation, and application of modern DSP techniques with DIGITAL SIGNAL PROCESSING USING MATLAB(R), 3E. Written in an engaging, informal style, this edition immediately captures your attention and encourages you to explore each critical topic. Every chapter starts with a motivational section that highlights practical examples and challenges that you can solve using techniques covered in the chapter. Each chapter concludes with a detailed case study example, a chapter summary with learning outcomes, and practical homework problems cross-referenced to specific chapter sections for your convenience. DSP Companion software accompanies each book to enable further investigation. The DSP Companion software operates with MATLAB(R) and provides intriguing demonstrations as well as interactive explorations of analysis and design concepts.

  14. General programmed system for physiological signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Tournier, E; Monge, J; Magnet, C; Sonrel, C

    1975-01-01

    Improvements made to the general programmed signal acquisition and processing system, Plurimat S, are described, the aim being to obtain a less specialized system adapted to the biological and medical field. In this modified system the acquisition will be simplified. The standard processings offered will be integrated to a real advanced language which will enable the user to create his own processings, the loss of speed being compensated by a greater flexibility and universality. The observation screen will be large and the quality of the recording very good so that a large signal fraction may be displayed. The data will be easily indexed and filed for subsequent display and processing. This system will be used for two kinds of task: it can either be specialized, as an integral part of measurement and diagnostic preparation equipment used routinely in clinical work (e.g. vectocardiographic examination), or its versatility can be used for studies of limited duration to gain information in a given field or to study new diagnosis or treatment methods.

  15. Adaptive EMG noise reduction in ECG signals using noise level approximation

    Science.gov (United States)

    Marouf, Mohamed; Saranovac, Lazar

    2017-12-01

    In this paper the usage of noise level approximation for adaptive Electromyogram (EMG) noise reduction in the Electrocardiogram (ECG) signals is introduced. To achieve the adequate adaptiveness, a translation-invariant noise level approximation is employed. The approximation is done in the form of a guiding signal extracted as an estimation of the signal quality vs. EMG noise. The noise reduction framework is based on a bank of low pass filters. So, the adaptive noise reduction is achieved by selecting the appropriate filter with respect to the guiding signal aiming to obtain the best trade-off between the signal distortion caused by filtering and the signal readability. For the evaluation purposes; both real EMG and artificial noises are used. The tested ECG signals are from the MIT-BIH Arrhythmia Database Directory, while both real and artificial records of EMG noise are added and used in the evaluation process. Firstly, comparison with state of the art methods is conducted to verify the performance of the proposed approach in terms of noise cancellation while preserving the QRS complex waves. Additionally, the signal to noise ratio improvement after the adaptive noise reduction is computed and presented for the proposed method. Finally, the impact of adaptive noise reduction method on QRS complexes detection was studied. The tested signals are delineated using a state of the art method, and the QRS detection improvement for different SNR is presented.

  16. Adaptive control of human action: The role of outcome representations and reward signals

    Directory of Open Access Journals (Sweden)

    Hans eMarien

    2013-09-01

    Full Text Available The present paper aims to advance the understanding of the control of human behavior by integrating two lines of literature that so far have led separate lives. First, one line of literature is concerned with the ideomotor principle of human behavior, according to which actions are represented in terms of their outcomes. The second line of literature mainly considers the role of reward signals in adaptive control. Here, we offer a combined perspective on how outcome representations and reward signals work together to modulate adaptive control processes. We propose that reward signals signify the value of outcome representations and facilitate the recruitment of control resources in situations where behavior needs to be maintained or adapted to attain the represented outcome. We discuss recent research demonstrating how adaptive control of goal-directed behavior may emerge when outcome representations are co-activated with positive reward signals.

  17. Signal and image processing for monitoring and testing at EDF

    International Nuclear Information System (INIS)

    Georgel, B.; Garreau, D.

    1992-04-01

    The quality of monitoring and non destructive testing devices in plants and utilities today greatly depends on the efficient processing of signal and image data. In this context, signal or image processing techniques, such as adaptive filtering or detection or 3D reconstruction, are required whenever manufacturing nonconformances or faulty operation have to be recognized and identified. This paper reviews the issues of industrial image and signal processing, by briefly considering the relevant studies and projects under way at EDF. (authors). 1 fig., 11 refs

  18. Radar signal analysis and processing using Matlab

    CERN Document Server

    Mahafza, Bassem R

    2008-01-01

    Offering radar-related software for the analysis and design of radar waveform and signal processing, this book provides comprehensive coverage of radar signals and signal processing techniques and algorithms. It contains numerous graphical plots, common radar-related functions, table format outputs, and end-of-chapter problems. The complete set of MATLAB[registered] functions and routines are available for download online.

  19. A signal theoretic introduction to random processes

    CERN Document Server

    Howard, Roy M

    2015-01-01

    A fresh introduction to random processes utilizing signal theory By incorporating a signal theory basis, A Signal Theoretic Introduction to Random Processes presents a unique introduction to random processes with an emphasis on the important random phenomena encountered in the electronic and communications engineering field. The strong mathematical and signal theory basis provides clarity and precision in the statement of results. The book also features:  A coherent account of the mathematical fundamentals and signal theory that underpin the presented material Unique, in-depth coverage of

  20. Digital signal processing with kernel methods

    CERN Document Server

    Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo

    2018-01-01

    A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...

  1. Process Dissociation and Mixture Signal Detection Theory

    Science.gov (United States)

    DeCarlo, Lawrence T.

    2008-01-01

    The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

  2. Advanced optical signal processing of broadband parallel data signals

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Hu, Hao; Kjøller, Niels-Kristian

    2016-01-01

    Optical signal processing may aid in reducing the number of active components in communication systems with many parallel channels, by e.g. using telescopic time lens arrangements to perform format conversion and allow for WDM regeneration.......Optical signal processing may aid in reducing the number of active components in communication systems with many parallel channels, by e.g. using telescopic time lens arrangements to perform format conversion and allow for WDM regeneration....

  3. [Automated processing of electrophysiologic signals].

    Science.gov (United States)

    Korenevskiĭ, N A; Gubanov, V V

    1995-01-01

    The paper outlines a diagram of a multichannel analyzer of electrophysiological signals while are significantly non-stationary (such as those of electroencephalograms, myograms, etc.), by using a method based on the ranging procedure by the change-over points which may be the points of infection, impaired locality, minima, maxima, discontinuity, etc.

  4. Advanced Methods of Biomedical Signal Processing

    CERN Document Server

    Cerutti, Sergio

    2011-01-01

    This book grew out of the IEEE-EMBS Summer Schools on Biomedical Signal Processing, which have been held annually since 2002 to provide the participants state-of-the-art knowledge on emerging areas in biomedical engineering. Prominent experts in the areas of biomedical signal processing, biomedical data treatment, medicine, signal processing, system biology, and applied physiology introduce novel techniques and algorithms as well as their clinical or physiological applications. The book provides an overview of a compelling group of advanced biomedical signal processing techniques, such as mult

  5. Radar signal processing and its applications

    CERN Document Server

    Hummel, Robert; Stoica, Petre; Zelnio, Edmund

    2003-01-01

    Radar Signal Processing and Its Applications brings together in one place important contributions and up-to-date research results in this fast-moving area. In twelve selected chapters, it describes the latest advances in architectures, design methods, and applications of radar signal processing. The contributors to this work were selected from the leading researchers and practitioners in the field. This work, originally published as Volume 14, Numbers 1-3 of the journal, Multidimensional Systems and Signal Processing, will be valuable to anyone working or researching in the field of radar signal processing. It serves as an excellent reference, providing insight into some of the most challenging issues being examined today.

  6. Signal processing for boiling noise detection

    International Nuclear Information System (INIS)

    Ledwidge, T.J.; Black, J.L.

    1989-01-01

    The present paper deals with investigations of acoustic signals from a boiling experiment performed on the KNS I loop at KfK Karlsruhe. Signals have been analysed in frequency as well as in time domain. Signal characteristics successfully used to detect the boiling process have been found in time domain. (author). 6 refs, figs

  7. Digital signal processing an experimental approach

    CERN Document Server

    Engelberg, Shlomo

    2008-01-01

    Digital Signal Processing is a mathematically rigorous but accessible treatment of digital signal processing that intertwines basic theoretical techniques with hands-on laboratory instruction. Divided into three parts, the book covers various aspects of the digital signal processing (DSP) ""problem."" It begins with the analysis of discrete-time signals and explains sampling and the use of the discrete and fast Fourier transforms. The second part of the book???covering digital to analog and analog to digital conversion???provides a practical interlude in the mathematical content before Part II

  8. Fast digitizing and digital signal processing of detector signals

    International Nuclear Information System (INIS)

    Hannaske, Roland

    2008-01-01

    A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22 Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing. (orig.)

  9. Cognitive Algorithms for Signal Processing

    Science.gov (United States)

    2011-03-18

    Analysis of Millennial Spiritual Issues,” Zygon, Journal of Science and Religion , 43(4), 797-821, 2008. [46] R. Linnehan, C. Mutz, L.I. Perlovsky, B...dimensions of X and Y : (a) true ‘smile’ and ‘frown’ patterns are shown without clutter; (b) actual image available for recognition (signal is below...clutter in 2 dimensions of X(n) = (X, Y ), is given by l(X(n)|m = clutter) = 1/ (X •  Y ), X = (Xmax-Xmin),  Y = (Ymax-Ymin); (6) 13 Minimal

  10. Handbook of Signal Processing in Acoustics

    CERN Document Server

    Havelock, David; Vorländer, Michael

    2009-01-01

    The Handbook of Signal Processing in Acoustics presents signal processing as it is practiced in the field of acoustics. The Handbook is organized by areas of acoustics, with recognized leaders coordinating the self-contained chapters of each section. It brings together a wide range of perspectives from over 100 authors to reveal the interdisciplinary nature of signal processing in acoustics. Success in acoustic applications often requires juggling both the acoustic and the signal processing parameters of the problem. This handbook brings the key issues from both into perspective and is complementary to other reference material on the two subjects. It is a unique resource for experts and practitioners alike to find new ideas and techniques within the diversity of signal processing in acoustics.

  11. Specificity, cross-talk and adaptation in Interferon signaling

    Science.gov (United States)

    Zilman, Anton

    Innate immune system is the first line of defense of higher organisms against pathogens. It coordinates the behavior of millions of cells of multiple types, achieved through numerous signaling molecules. This talk focuses on the signaling specificity of a major class of signaling molecules - Type I Interferons - which are also used therapeutically in the treatment of a number of diseases, such as Hepatitis C, multiple sclerosis and some cancers. Puzzlingly, different Interferons act through the same cell surface receptor but have different effects on the target cells. They also exhibit a strange pattern of temporal cross-talk resulting in a serious clinical problem - loss of response to Interferon therapy. We combined mathematical modeling with quantitative experiments to develop a quantitative model of specificity and adaptation in the Interferon signaling pathway. The model resolves several outstanding experimental puzzles and directly affects the clinical use of Type I Interferons in treatment of viral hepatitis and other diseases.

  12. Advances in heuristic signal processing and applications

    CERN Document Server

    Chatterjee, Amitava; Siarry, Patrick

    2013-01-01

    There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and multidimensional signal processing, namely image and video processing, with the recent focus changing from a step-by-step procedure of designing the algorithm first and following up with in-depth analysis and performance improvement to instead applying heuristic-based methods to solve signal-processing problems. In this book the contributing authors demonstrate both general-purpose algorithms and those aimed at solving specialized application problems, with a spec

  13. Ultrafast Nonlinear Signal Processing in Silicon Waveguides

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Mulvad, Hans Christian Hansen; Hu, Hao

    2012-01-01

    We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling.......We describe recent demonstrations of exploiting highly nonlinear silicon waveguides for ultrafast optical signal processing. We describe wavelength conversion and serial-to-parallel conversion of 640 Gbit/s data signals and 1.28 Tbit/s demultiplexing and all-optical sampling....

  14. Signal processing methods for MFE plasma diagnostics

    International Nuclear Information System (INIS)

    Candy, J.V.; Casper, T.; Kane, R.

    1985-02-01

    The application of various signal processing methods to extract energy storage information from plasma diamagnetism sensors occurring during physics experiments on the Tandom Mirror Experiment-Upgrade (TMX-U) is discussed. We show how these processing techniques can be used to decrease the uncertainty in the corresponding sensor measurements. The algorithms suggested are implemented using SIG, an interactive signal processing package developed at LLNL

  15. Parametric Adaptive Radar Detector with Enhanced Mismatched Signals Rejection Capabilities

    Directory of Open Access Journals (Sweden)

    Liu Bin

    2010-01-01

    Full Text Available We consider the problem of adaptive signal detection in the presence of Gaussian noise with unknown covariance matrix. We propose a parametric radar detector by introducing a design parameter to trade off the target sensitivity with sidelobes energy rejection. The resulting detector merges the statistics of Kelly's GLRT and of the Rao test and so covers Kelly's GLRT and the Rao test as special cases. Both invariance properties and constant false alarm rate (CFAR behavior for this detector are studied. At the analysis stage, the performance of the new receiver is assessed and compared with several traditional adaptive detectors. The results highlight better rejection capabilities of this proposed detector for mismatched signals. Further, we develop two two-stage detectors, one of which consists of an adaptive matched filter (AMF followed by the aforementioned detector, and the other is obtained by cascading a GLRT-based Subspace Detector (SD and the proposed adaptive detector. We show that the former two-stage detector outperforms traditional two-stage detectors in terms of selectivity, and the latter yields more robustness.

  16. Signal and image processing in medical applications

    CERN Document Server

    Kumar, Amit; Rahim, B Abdul; Kumar, D Sravan

    2016-01-01

    This book highlights recent findings on and analyses conducted on signals and images in the area of medicine. The experimental investigations involve a variety of signals and images and their methodologies range from very basic to sophisticated methods. The book explains how signal and image processing methods can be used to detect and forecast abnormalities in an easy-to-follow manner, offering a valuable resource for researchers, engineers, physicians and bioinformatics researchers alike.

  17. Pseudo random signal processing theory and application

    CERN Document Server

    Zepernick, Hans-Jurgen

    2013-01-01

    In recent years, pseudo random signal processing has proven to be a critical enabler of modern communication, information, security and measurement systems. The signal's pseudo random, noise-like properties make it vitally important as a tool for protecting against interference, alleviating multipath propagation and allowing the potential of sharing bandwidth with other users. Taking a practical approach to the topic, this text provides a comprehensive and systematic guide to understanding and using pseudo random signals. Covering theoretical principles, design methodologies and applications

  18. Electronic devices for analog signal processing

    CERN Document Server

    Rybin, Yu K

    2012-01-01

    Electronic Devices for Analog Signal Processing is intended for engineers and post graduates and considers electronic devices applied to process analog signals in instrument making, automation, measurements, and other branches of technology. They perform various transformations of electrical signals: scaling, integration, logarithming, etc. The need in their deeper study is caused, on the one hand, by the extension of the forms of the input signal and increasing accuracy and performance of such devices, and on the other hand, new devices constantly emerge and are already widely used in practice, but no information about them are written in books on electronics. The basic approach of presenting the material in Electronic Devices for Analog Signal Processing can be formulated as follows: the study with help from self-education. While divided into seven chapters, each chapter contains theoretical material, examples of practical problems, questions and tests. The most difficult questions are marked by a diamon...

  19. Adaptive filtration of speech signals in the presence of correlated noise with random variation of probabilistic characteristics

    OpenAIRE

    M. O. Partala; S. Ya. Zhuk

    2007-01-01

    On the base of mixed Markoff process in discrete time optimal and quasioptimal algorithms is designed for adaptive filtration of speech signals in the presence of correlated noise with random variation of probabilistic characteristics.

  20. Multibeam swath bathymetry signal processing techniques

    Digital Repository Service at National Institute of Oceanography (India)

    Ranade, G.; Sudhakar, T.

    Mathematical advances and the advances in the real time signal processing techniques in the recent times, have considerably improved the state of art in the bathymetry systems. These improvements have helped in developing high resolution swath...

  1. Cyclic LTI Systems in Digital Signal Processing

    National Research Council Canada - National Science Library

    Vaidyanathan, P

    1998-01-01

    .... While circular convolution has been the centerpiece of many algorithms in signal processing for decades, such freedom, especially from the viewpoint of linear system theory, has not been studied in the past...

  2. Denoising of Mechanical Vibration Signals Using Quantum-Inspired Adaptive Wavelet Shrinkage

    Directory of Open Access Journals (Sweden)

    Yan-long Chen

    2014-01-01

    Full Text Available The potential application of a quantum-inspired adaptive wavelet shrinkage (QAWS technique to mechanical vibration signals with a focus on noise reduction is studied in this paper. This quantum-inspired shrinkage algorithm combines three elements: an adaptive non-Gaussian statistical model of dual-tree complex wavelet transform (DTCWT coefficients proposed to improve practicability of prior information, the quantum superposition introduced to describe the interscale dependencies of DTCWT coefficients, and the quantum-inspired probability of noise defined to shrink wavelet coefficients in a Bayesian framework. By combining all these elements, this signal processing scheme incorporating the DTCWT with quantum theory can both reduce noise and preserve signal details. A practical vibration signal measured from a power-shift steering transmission is utilized to evaluate the denoising ability of QAWS. Application results demonstrate the effectiveness of the proposed method. Moreover, it achieves better performance than hard and soft thresholding.

  3. Book: Marine Bioacoustic Signal Processing and Analysis

    Science.gov (United States)

    2011-09-30

    physicists , and mathematicians . However, more and more biologists and psychologists are starting to use advanced signal processing techniques and...Book: Marine Bioacoustic Signal Processing and Analysis 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT ...chapters than it should be, since the project must be finished by Dec. 31. I have started setting aside 2 hours of uninterrupted per workday to work

  4. Non-commutative tomography and signal processing

    International Nuclear Information System (INIS)

    Mendes, R Vilela

    2015-01-01

    Non-commutative tomography is a technique originally developed and extensively used by Professors M A Man’ko and V I Man’ko in quantum mechanics. Because signal processing deals with operators that, in general, do not commute with time, the same technique has a natural extension to this domain. Here, a review is presented of the theory and some applications of non-commutative tomography for time series as well as some new results on signal processing on graphs. (paper)

  5. Processing of acoustic signal in rock desintegration

    Directory of Open Access Journals (Sweden)

    Futó Jozef

    2002-12-01

    Full Text Available For the determination of an effective rock disintegration for a given tool and rock type it is needed to define an optimal disintegration regime. Optimisation of the disintegration process by drilling denotes the finding out an appropriate couple of input parameters of disintegration, i.e. the thrust and revolutions for a quasi-equal rock environment. The disintegration process can be optimised to reach the maximum immediate drilling rate, to reach the minimum specific disintegration energy or to reach the maximum ratio of immediate drilling rate and specific disintegration energy. For the determination of the optimal thrust and revolutions it is needed to monitor the disintegration process. Monitoring of the disintegration process in real conditions is complicated by unfavourable factors, such as the presence of water, dust, vibrations etc. Following our present experience in the monitoring of drilling or full-profile driving, we try to replace the monitoring of input values by monitoring of the scanned acoustic signal. This method of monitoring can extend the optimisation of disintegration process in the technical practice. Its advantage consists in the registration of one acoustic signal by an appropriate microphone. Monitoring of acoustic signal is used also in monitoring of metal machining by milling and turning jobs. The research results of scanning of the acoustic signal in machining of metals are encouraging. Acoustic signal can be processed by different statistical parameters. The paper decribes some results of monitoring of the acoustic signal in rock disintegration on the drilling stand of the Institute of Geotechnics SAS in Košice. The acoustic signal has been registered and processed in no-load run of electric motor, in no-load run of electric motor with a drilling fluid, and in the Ruskov andesite drilling. Registration and processing of the acoustic signal is solved as a part of the research grant task within the basic research

  6. Liquid Argon TPC Signal Formation, Signal Processing and Hit Reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Baller, Bruce [Fermilab

    2017-03-11

    This document describes the early stage of the reconstruction chain that was developed for the ArgoNeuT and MicroBooNE experiments at Fermilab. These experiments study accelerator neutrino interactions that occur in a Liquid Argon Time Projection Chamber. Reconstructing the properties of particles produced in these interactions requires knowledge of the micro-physics processes that affect the creation and transport of ionization electrons to the readout system. A wire signal deconvolution technique was developed to convert wire signals to a standard form for hit reconstruction, to remove artifacts in the electronics chain and to remove coherent noise.

  7. An adaptive orienting theory of error processing.

    Science.gov (United States)

    Wessel, Jan R

    2018-03-01

    The ability to detect and correct action errors is paramount to safe and efficient goal-directed behaviors. Existing work on the neural underpinnings of error processing and post-error behavioral adaptations has led to the development of several mechanistic theories of error processing. These theories can be roughly grouped into adaptive and maladaptive theories. While adaptive theories propose that errors trigger a cascade of processes that will result in improved behavior after error commission, maladaptive theories hold that error commission momentarily impairs behavior. Neither group of theories can account for all available data, as different empirical studies find both impaired and improved post-error behavior. This article attempts a synthesis between the predictions made by prominent adaptive and maladaptive theories. Specifically, it is proposed that errors invoke a nonspecific cascade of processing that will rapidly interrupt and inhibit ongoing behavior and cognition, as well as orient attention toward the source of the error. It is proposed that this cascade follows all unexpected action outcomes, not just errors. In the case of errors, this cascade is followed by error-specific, controlled processing, which is specifically aimed at (re)tuning the existing task set. This theory combines existing predictions from maladaptive orienting and bottleneck theories with specific neural mechanisms from the wider field of cognitive control, including from error-specific theories of adaptive post-error processing. The article aims to describe the proposed framework and its implications for post-error slowing and post-error accuracy, propose mechanistic neural circuitry for post-error processing, and derive specific hypotheses for future empirical investigations. © 2017 Society for Psychophysiological Research.

  8. Pedagogical reforms of digital signal processing education

    Science.gov (United States)

    Christensen, Michael

    The future of the engineering discipline is arguably predicated heavily upon appealing to the future generation, in all its sensibilities. The greatest burden in doing so, one might rightly believe, lies on the shoulders of the educators. In examining the causal means by which the profession arrived at such a state, one finds that the technical revolution, precipitated by global war, had, as its catalyst, institutions as expansive as the government itself to satisfy the demand for engineers, who, as a result of such an existential crisis, were taught predominantly theoretical underpinnings to address a finite purpose. By contrast, the modern engineer, having expanded upon this vision and adapted to an evolving society, is increasingly placed in the proverbial role of the worker who must don many hats: not solely a scientist, yet often an artist; not a businessperson alone, but neither financially naive; not always a representative, though frequently a collaborator. Inasmuch as change then serves as the only constancy in a global climate, therefore, the educational system - if it is to mimic the demands of the industry - is left with an inherent need for perpetual revitalization to remain relevant. This work aims to serve that end. Motivated by existing research in engineering education, an epistemological challenge is molded into the framework of the electrical engineer with emphasis on digital signal processing. In particular, it is investigated whether students are better served by a learning paradigm that tolerates and, when feasible, encourages error via a medium free of traditional adjudication. Through the creation of learning modules using the Adobe Captivate environment, a wide range of fundamental knowledge in signal processing is challenged within the confines of existing undergraduate courses. It is found that such an approach not only conforms to the research agenda outlined for the engineering educator, but also reflects an often neglected reality

  9. Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique

    Science.gov (United States)

    Abbaspour, S; Fallah, A

    2014-01-01

    Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful. Objective: Removing electrocardiogram contamination from electromyogram signals. Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and electrocardiogram signal were recorded from leg muscles, the pectoralis major muscle of the left side and V4, respectively. After the pre-processing, contaminated electromyogram signal is simulated with a combination of clean electromyogram and electrocardiogram artifact. Then, contaminated electromyogram is cleaned using adaptive subtraction method. This method contains some steps; (1) QRS detection, (2) formation of electrocardiogram template by averaging the electrocardiogram complexes, (3) using low pass filter to remove undesirable artifacts, (4) subtraction. Results: Performance of our method is evaluated using qualitative criteria, power spectrum density and coherence and quantitative criteria signal to noise ratio, relative error and cross correlation. The result of signal to noise ratio, relative error and cross correlation is equal to 10.493, 0.04 and %97 respectively. Finally, there is a comparison between proposed method and some existing methods. Conclusion: The result indicates that adaptive subtraction method is somewhat effective to remove electrocardiogram artifact from contaminated electromyogram signal and has an acceptable result. PMID:25505766

  10. Signal processing: opportunities for superconductive circuits

    International Nuclear Information System (INIS)

    Ralston, R.W.

    1985-01-01

    Prime motivators in the evolution of increasingly sophisticated communication and detection systems are the needs for handling ever wider signal bandwidths and higher data processing speeds. These same needs drive the development of electronic device technology. Until recently the superconductive community has been tightly focused on digital devices for high speed computers. The purpose of this paper is to describe opportunities and challenges which exist for both analog and digital devices in a less familiar area, that of wideband signal processing. The function and purpose of analog signal-processing components, including matched filters, correlators and Fourier transformers, will be described and examples of superconductive implementations given. A canonic signal-processing system is then configured using these components in combination with analog/digital converters and digital output circuits to highlight the important issues of dynamic range, accuracy and equivalent computation rate. Superconductive circuits hold promise for processing signals of 10-GHz bandwidth. Signal processing systems, however, can be properly designed and implemented only through a synergistic combination of the talents of device physicists, circuit designers, algorithm architects and system engineers. An immediate challenge to the applied superconductivity community is to begin sharing ideas with these other researchers

  11. Signal processing in noise waveform radar

    CERN Document Server

    Kulpa, Krzysztof

    2013-01-01

    This book is devoted to the emerging technology of noise waveform radar and its signal processing aspects. It is a new kind of radar, which use noise-like waveform to illuminate the target. The book includes an introduction to basic radar theory, starting from classical pulse radar, signal compression, and wave radar. The book then discusses the properties, difficulties and potential of noise radar systems, primarily for low-power and short-range civil applications. The contribution of modern signal processing techniques to making noise radar practical are emphasized, and application examples

  12. Bayesian nonparametric adaptive control using Gaussian processes.

    Science.gov (United States)

    Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A

    2015-03-01

    Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.

  13. Signal Adaptive System for Space/Spatial-Frequency Analysis

    Directory of Open Access Journals (Sweden)

    Veselin N. Ivanović

    2009-01-01

    Full Text Available This paper outlines the development of a multiple-clock-cycle implementation (MCI of a signal adaptive two-dimensional (2D system for space/spatial-frequency (S/SF signal analysis. The design is based on a method for improved S/SF representation of the analyzed 2D signals, also proposed here. The proposed MCI design optimizes critical design performances related to hardware complexity, making it a suitable system for real time implementation on an integrated chip. Additionally, the design allows the implemented system to take a variable number of clock cycles (CLKs (the only necessary ones regarding desirable—2D Wigner distribution-presentation of autoterms in different frequency-frequency points during the execution. This ability represents a major advantage of the proposed design which helps to optimize the time required for execution and produce an improved, cross-terms-free S/SF signal representation. The design has been verified by a field-programmable gate array (FPGA circuit design, capable of performing S/SF analysis of 2D signals in real time.

  14. Radiation-induced adaptive response and intracellular signal transduction pathways

    International Nuclear Information System (INIS)

    Tachibana, Akira

    2009-01-01

    As an essential biological function, cells can sense the radiation even at low dose and respond to it, and which is one of bases of the radiation-induced adaptive response (AR) where effects caused by high dose radiation are reduced by prior exposure to low dose radiation (LDR). Here described are studies of AR in well established m5S cells on the intracellular signal transduction that involves sensing of LDR and transmitting of its signal within the cell network. The first signal for AR yielded by LDR on the cell membrane is exactly unknown though hydrogen peroxide and phorbol ester (PMA) can reportedly cause AR. As PMA activates protein kinase C (PKC) and its inhibitors suppress AR, participation of PKC in AR has been suggested and supported by studies showing PKCα activation by LDR. In addition, p38 mitogen-activated protein kinase (MAPK) is shown to participate in AR by those facts that the enzyme is activated by LDR, a p38 MAPK inhibitor suppresses AR, and PKC inhibitors suppress the enzyme activation, which also suggesting that the signaling from PKC to p38 MAPK can become operative by LDR. However, the possible reverse signaling is also suggested, and thus the activation of positive feedback mechanism is postulated in PKC/p38 MAPK/phospholipase δ1/ PKC pathway. Cells introduced with siRNA against Prkca gene (coding PKCs) produce reduced amount of the enzyme, particularly, of PKCα. In those cells, AR by 5 Gy X-ray is not observed and thereby PKCα is involved in AR. The signaling in AR is only partly elucidated at present as above, and more detailed studies including identification of more PKC subtypes and signaling to DNA repair system are considered necessary. (K.T.)

  15. Adaptive plasticity in wild field cricket's acoustic signaling.

    Directory of Open Access Journals (Sweden)

    Susan M Bertram

    Full Text Available Phenotypic plasticity can be adaptive when phenotypes are closely matched to changes in the environment. In crickets, rhythmic fluctuations in the biotic and abiotic environment regularly result in diel rhythms in density of sexually active individuals. Given that density strongly influences the intensity of sexual selection, we asked whether crickets exhibit plasticity in signaling behavior that aligns with these rhythmic fluctuations in the socio-sexual environment. We quantified the acoustic mate signaling behavior of wild-caught males of two cricket species, Gryllus veletis and G. pennsylvanicus. Crickets exhibited phenotypically plastic mate signaling behavior, with most males signaling more often and more attractively during the times of day when mating activity is highest in the wild. Most male G. pennsylvanicus chirped more often and louder, with shorter interpulse durations, pulse periods, chirp durations, and interchirp durations, and at slightly higher carrier frequencies during the time of the day that mating activity is highest in the wild. Similarly, most male G. veletis chirped more often, with more pulses per chirp, longer interpulse durations, pulse periods, and chirp durations, shorter interchirp durations, and at lower carrier frequencies during the time of peak mating activity in the wild. Among-male variation in signaling plasticity was high, with some males signaling in an apparently maladaptive manner. Body size explained some of the among-male variation in G. pennsylvanicus plasticity but not G. veletis plasticity. Overall, our findings suggest that crickets exhibit phenotypically plastic mate attraction signals that closely match the fluctuating socio-sexual context they experience.

  16. Frequency Adaptability and Waveform Design for OFDM Radar Space-Time Adaptive Processing

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Satyabrata [ORNL; Glover, Charles Wayne [ORNL

    2012-01-01

    We propose an adaptive waveform design technique for an orthogonal frequency division multiplexing (OFDM) radar signal employing a space-time adaptive processing (STAP) technique. We observe that there are inherent variabilities of the target and interference responses in the frequency domain. Therefore, the use of an OFDM signal can not only increase the frequency diversity of our system, but also improve the target detectability by adaptively modifying the OFDM coefficients in order to exploit the frequency-variabilities of the scenario. First, we formulate a realistic OFDM-STAP measurement model considering the sparse nature of the target and interference spectra in the spatio-temporal domain. Then, we show that the optimal STAP-filter weight-vector is equal to the generalized eigenvector corresponding to the minimum generalized eigenvalue of the interference and target covariance matrices. With numerical examples we demonstrate that the resultant OFDM-STAP filter-weights are adaptable to the frequency-variabilities of the target and interference responses, in addition to the spatio-temporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDM-waveform design technique, and consequently gain a significant amount of STAP-performance improvement.

  17. Processing and Linguistics Properties of Adaptable Systems

    Directory of Open Access Journals (Sweden)

    Dumitru TODOROI

    2006-01-01

    Full Text Available Continuation and development of the research in Adaptable Programming Initialization [Tod-05.1,2,3] is presented. As continuation of [Tod-05.2,3] in this paper metalinguistic tools used in the process of introduction of new constructions (data, operations, instructions and controls are developed. The generalization schemes of evaluation of adaptable languages and systems are discussed. These results analogically with [Tod-05.2,3] are obtained by the team, composed from the researchers D. Todoroi [Tod-05.4], Z. Todoroi [ZTod-05], and D. Micusa [Mic-03]. Presented results will be included in the book [Tod-06].

  18. Signal recovery of the corrupted metal impact signal using the adaptive filtering in NPPs

    International Nuclear Information System (INIS)

    Kim, Dai Il; Shin, Won Ky; Oh, Sung Hun; Yun, Won Young

    1995-01-01

    Loose Part Monitoring System (LPMS) is one of the fundamental diagnostic tools installed in the nuclear power plants. In this paper, recovery process algorithm and model for the corrupted impact signal generated by loose parts is presented. The characteristics of this algorithm can obtain a proper burst signal even though background noise is considerably high level comparing with actual impact signal. To verify performance of the proposed algorithm, we evaluate mathematically signal-to-noise ratio of primary output and noise. The performance of this recovery process algorithm is shown through computer simulation

  19. SignalPlant: an open signal processing software platform

    Czech Academy of Sciences Publication Activity Database

    Plešinger, Filip; Jurčo, Juraj; Halámek, Josef; Jurák, Pavel

    2016-01-01

    Roč. 37, č. 7 (2016), N38-N48 ISSN 0967-3334 R&D Projects: GA ČR GAP103/11/0933; GA MŠk(CZ) LO1212; GA ČR GAP102/12/2034 Institutional support: RVO:68081731 Keywords : data visualization * software * signal processing * ECG * EEG Subject RIV: FS - Medical Facilities ; Equipment Impact factor: 2.058, year: 2016

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

    Directory of Open Access Journals (Sweden)

    Makowski Ryszard

    2014-06-01

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

  1. Adaptive motion compensation in sonar array processing

    NARCIS (Netherlands)

    Groen, J.

    2006-01-01

    In recent years, sonar performance has mainly improved via a significant increase in array ap-erture, signal bandwidth and computational power. This thesis aims at improving sonar array processing techniques based on these three steps forward. In applications such as anti-submarine warfare and mine

  2. Financial signal processing and machine learning

    CERN Document Server

    Kulkarni,Sanjeev R; Dmitry M. Malioutov

    2016-01-01

    The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analy...

  3. Nonlinear filtering for LIDAR signal processing

    Directory of Open Access Journals (Sweden)

    D. G. Lainiotis

    1996-01-01

    Full Text Available LIDAR (Laser Integrated Radar is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF, which has been the standard nonlinear filter in past engineering applications.

  4. Digital signal processing application in nuclear spectroscopy

    Directory of Open Access Journals (Sweden)

    O. V. Zeynalova

    2009-06-01

    Full Text Available Digital signal processing algorithms for nuclear particle spectroscopy are described along with a digital pile-up elimination method applicable to equidistantly sampled detector signals pre-processed by a charge-sensitive preamplifier. The signal processing algorithms provided as recursive one- or multi-step procedures which can be easily programmed using modern computer programming languages. The influence of the number of bits of the sampling analogue-to-digital converter to the final signal-to-noise ratio of the spectrometer considered. Algorithms for a digital shaping-filter amplifier, for a digital pile-up elimination scheme and for ballistic deficit correction were investigated using a high purity germanium detector. The pile-up elimination method was originally developed for fission fragment spectroscopy using a Frisch-grid back-to-back double ionisation chamber and was mainly intended for pile-up elimination in case of high alpha-radioactivity of the fissile target. The developed pile-up elimination method affects only the electronic noise generated by the preamplifier. Therefore, the influence of the pile-up elimination scheme on the final resolution of the spectrometer investigated in terms of the distance between piled-up pulses. The efficiency of developed algorithms compared with other signal processing schemes published in literature.

  5. Liquid argon TPC signal formation, signal processing and reconstruction techniques

    Science.gov (United States)

    Baller, B.

    2017-07-01

    This document describes a reconstruction chain that was developed for the ArgoNeuT and MicroBooNE experiments at Fermilab. These experiments study accelerator neutrino interactions that occur in a Liquid Argon Time Projection Chamber. Reconstructing the properties of particles produced in these interactions benefits from the knowledge of the micro-physics processes that affect the creation and transport of ionization electrons to the readout system. A wire signal deconvolution technique was developed to convert wire signals to a standard form for hit reconstruction, to remove artifacts in the electronics chain and to remove coherent noise. A unique clustering algorithm reconstructs line-like trajectories and vertices in two dimensions which are then matched to create of 3D objects. These techniques and algorithms are available to all experiments that use the LArSoft suite of software.

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

    Science.gov (United States)

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

    2007-11-01

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

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

    International Nuclear Information System (INIS)

    Garces Correa, A; Laciar, E; Patino, H D; Valentinuzzi, M E

    2007-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Garces Correa, A [Gabinete de TecnologIa Medica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Laciar, E [Gabinete de TecnologIa Medica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Patino, H D [Instituto de Automatica, Facultad de Ingenieria, Universidad Nacional de San Juan (Argentina); Valentinuzzi, M E [Instituto Superior de Investigaciones Biologicas (INSIBIO), UNT-CONICET, Tucuman (Argentina)

    2007-11-15

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

  9. Adaptive multiple importance sampling for Gaussian processes

    Czech Academy of Sciences Publication Activity Database

    Xiong, X.; Šmídl, Václav; Filippone, M.

    2017-01-01

    Roč. 87, č. 8 (2017), s. 1644-1665 ISSN 0094-9655 R&D Projects: GA MŠk(CZ) 7F14287 Institutional support: RVO:67985556 Keywords : Gaussian Process * Bayesian estimation * Adaptive importance sampling Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 0.757, year: 2016 http://library.utia.cas.cz/separaty/2017/AS/smidl-0469804.pdf

  10. Python for signal processing featuring IPython notebooks

    CERN Document Server

    Unpingco, José

    2013-01-01

    This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to ""experiment and learn"" as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remai

  11. Signal Processing Methods Monitor Cranial Pressure

    Science.gov (United States)

    2010-01-01

    Dr. Norden Huang, of Goddard Space Flight Center, invented a set of algorithms (called the Hilbert-Huang Transform, or HHT) for analyzing nonlinear and nonstationary signals that developed into a user-friendly signal processing technology for analyzing time-varying processes. At an auction managed by Ocean Tomo Federal Services LLC, licenses of 10 U.S. patents and 1 domestic patent application related to HHT were sold to DynaDx Corporation, of Mountain View, California. DynaDx is now using the licensed NASA technology for medical diagnosis and prediction of brain blood flow-related problems, such as stroke, dementia, and traumatic brain injury.

  12. Digital signal processing - growth of a technology

    International Nuclear Information System (INIS)

    Peek, J.B.H.

    1985-01-01

    The rapid development of microelectronics has led to an increasing extent in circuits and systems for digital signal processing. This happened first in professional applications, e.g. geophysics, astronomy and space flight, and now, with the Compact Disc player, these techniques have entered the consumer field. In the near future digital TV applications will undoubtedly follow. This article outlines a number of the developments behind the advancing 'digitization' of modern technology. The article also considers the main advantages and disadvantages of digital signal processing the main modules now used and some common applications. Particular attention is paid to medical applications. (Auth.)

  13. An introduction to digital signal processing

    CERN Document Server

    Karl, John H

    1989-01-01

    An Introduction to Digital Signal Processing is written for those who need to understand and use digital signal processing and yet do not wish to wade through a multi-semester course sequence. Using only calculus-level mathematics, this book progresses rapidly through the fundamentals to advanced topics such as iterative least squares design of IIR filters, inverse filters, power spectral estimation, and multidimensional applications--all in one concise volume.This book emphasizes both the fundamental principles and their modern computer implementation. It presents and demonstrates how si

  14. Motion-adaptive intraframe transform coding of video signals

    NARCIS (Netherlands)

    With, de P.H.N.

    1989-01-01

    Spatial transform coding has been widely applied for image compression because of its high coding efficiency. However, in many intraframe systems, in which every TV frame is independently processed, coding of moving objects in the case of interlaced input signals is not addressed. In this paper, we

  15. Attracting and repelling in homogeneous signal processes

    International Nuclear Information System (INIS)

    Downarowicz, T; Grzegorek, P; Lacroix, Y

    2010-01-01

    Attracting and repelling are discussed on two levels: in abstract signal processes and in signal processes arising as returns to a fixed set in an ergodic dynamical system. In the first approach, among other things, we give three examples in which the sum of two Poisson (hence neutral—neither attracting nor repelling) processes comes out either neutral or attracting, or repelling, depending on how the two processes depend on each other. The main new result of the second type concerns so-called 'composite events' in the form of a union of all cylinders over blocks belonging to the δ-ball in the Hamming distance around a fixed block. We prove that in a typical ergodic nonperiodic process the majority of such 'composite events' reveal strong attracting. We discuss the practical interpretation of this result

  16. Functional adaptation in female rats: the role of estrogen signaling.

    Directory of Open Access Journals (Sweden)

    Susannah J Sample

    Full Text Available Sex steroids have direct effects on the skeleton. Estrogen acts on the skeleton via the classical genomic estrogen receptors alpha and beta (ERα and ERβ, a membrane ER, and the non-genomic G-protein coupled estrogen receptor (GPER. GPER is distributed throughout the nervous system, but little is known about its effects on bone. In male rats, adaptation to loading is neuronally regulated, but this has not been studied in females.We used the rat ulna end-loading model to induce an adaptive modeling response in ovariectomized (OVX female Sprague-Dawley rats. Rats were treated with a placebo, estrogen (17β-estradiol, or G-1, a GPER-specific agonist. Fourteen days after OVX, rats underwent unilateral cyclic loading of the right ulna; half of the rats in each group had brachial plexus anesthesia (BPA of the loaded limb before loading. Ten days after loading, serum estrogen concentrations, dorsal root ganglion (DRG gene expression of ERα, ERβ, GPER, CGRPα, TRPV1, TRPV4 and TRPA1, and load-induced skeletal responses were quantified. We hypothesized that estrogen and G-1 treatment would influence skeletal responses to cyclic loading through a neuronal mechanism. We found that estrogen suppresses periosteal bone formation in female rats. This physiological effect is not GPER-mediated. We also found that absolute mechanosensitivity in female rats was decreased, when compared with male rats. Blocking of adaptive bone formation by BPA in Placebo OVX females was reduced.Estrogen acts to decrease periosteal bone formation in female rats in vivo. This effect is not GPER-mediated. Gender differences in absolute bone mechanosensitivity exist in young Sprague-Dawley rats with reduced mechanosensitivity in females, although underlying bone formation rate associated with growth likely influences this observation. In contrast to female and male rats, central neuronal signals had a diminished effect on adaptive bone formation in estrogen-deficient female rats.

  17. Broadband Nonlinear Signal Processing in Silicon Nanowires

    DEFF Research Database (Denmark)

    Yvind, Kresten; Pu, Minhao; Hvam, Jørn Märcher

    The fast non-linearity of silicon allows Tbit/s optical signal processing. By choosing suitable dimensions of silicon nanowires their dispersion can be tailored to ensure a high nonlinearity at power levels low enough to avoid significant two-photon abso We have fabricated low insertion...

  18. Power systems signal processing for smart grids

    NARCIS (Netherlands)

    Ribeiro, P.F.; Duque, C.A.; Da Silveira, P.M.; Cerqueira, A.S.

    2013-01-01

    With special relation to smart grids, this book provides clear and comprehensive explanation of how Digital Signal Processing (DSP) and Computational Intelligence (CI) techniques can be applied to solve problems in the power system. Its unique coverage bridges the gap between DSP, electrical power

  19. Optimisation in signal and image processing

    CERN Document Server

    Siarry, Patrick

    2010-01-01

    This book describes the optimization methods most commonly encountered in signal and image processing: artificial evolution and Parisian approach; wavelets and fractals; information criteria; training and quadratic programming; Bayesian formalism; probabilistic modeling; Markovian approach; hidden Markov models; and metaheuristics (genetic algorithms, ant colony algorithms, cross-entropy, particle swarm optimization, estimation of distribution algorithms, and artificial immune systems).

  20. Computer Aided Teaching of Digital Signal Processing.

    Science.gov (United States)

    Castro, Ian P.

    1990-01-01

    Describes a microcomputer-based software package developed at the University of Surrey for teaching digital signal processing to undergraduate science and engineering students. Menu-driven software capabilities are explained, including demonstration of qualitative concepts and experimentation with quantitative data, and examples are given of…

  1. Digital signal processing with Matlab examples

    CERN Document Server

    Giron-Sierra, Jose Maria

    2017-01-01

    This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.

  2. Calcium efflux systems in stress signalling and adaptation in plants

    Directory of Open Access Journals (Sweden)

    Jayakumar eBose

    2011-12-01

    Full Text Available Transient cytosolic calcium ([Ca2+]cyt elevation is an ubiquitous denominator of the signalling network when plants are exposed to literally every known abiotic and biotic stress. These stress-induced [Ca2+]cyt elevations vary in magnitude, frequency and shape, depending on the severity of the stress as well the type of stress experienced. This creates a unique stress-specific calcium signature that is then decoded by signal transduction networks. While most published papers have been focused predominantly on the role of Ca2+ influx mechanisms in shaping [Ca2+]cyt signatures, restoration of the basal [Ca2+]cyt levels is impossible without both cytosolic Ca2+ buffering and efficient Ca2+ efflux mechanisms removing excess Ca2+ from cytosol, to reload Ca2+ stores and to terminate Ca2+ signalling. This is the topic of the current review. The molecular identity of two major types of Ca2+ efflux systems, Ca2+-ATPase pumps and Ca2+/H+ exchangers, is described, and their regulatory modes are analysed in detail. The spatial and temporal organisation of calcium signalling networks is described, and the importance of existence of intracellular calcium microdomains is discussed. Experimental evidence for the role of Ca2+ efflux systems in plant responses to a range of abiotic and biotic factors is summarised. Contribution of Ca2+-ATPase pumps and Ca2+/H+ exchangers in shaping [Ca2+]cyt signatures is then modelled by using a four-component model (plasma- and endo- membrane-based Ca2+-permeable channels and efflux systems taking into account the cytosolic Ca2+ buffering. It is concluded that physiologically relevant variations in the activity of Ca2+-ATPase pumps and Ca2+/H+ exchangers are sufficient to fully describe all the reported experimental evidence and determine the shape of [Ca2+]cyt signatures in response to environmental stimuli, emphasising the crucial role these active efflux systems play in plant adaptive responses to environment.

  3. Digital Signal Processing for In-Vehicle Systems and Safety

    CERN Document Server

    Boyraz, Pinar; Takeda, Kazuya; Abut, Hüseyin

    2012-01-01

    Compiled from papers of the 4th Biennial Workshop on DSP (Digital Signal Processing) for In-Vehicle Systems and Safety this edited collection features world-class experts from diverse fields focusing on integrating smart in-vehicle systems with human factors to enhance safety in automobiles. Digital Signal Processing for In-Vehicle Systems and Safety presents new approaches on how to reduce driver inattention and prevent road accidents. The material addresses DSP technologies in adaptive automobiles, in-vehicle dialogue systems, human machine interfaces, video and audio processing, and in-vehicle speech systems. The volume also features: Recent advances in Smart-Car technology – vehicles that take into account and conform to the driver Driver-vehicle interfaces that take into account the driving task and cognitive load of the driver Best practices for In-Vehicle Corpus Development and distribution Information on multi-sensor analysis and fusion techniques for robust driver monitoring and driver recognition ...

  4. Digital signal and image processing using Matlab

    CERN Document Server

    Blanchet , Gérard

    2015-01-01

    The most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals, the theory being supported by exercises and computer simulations relating to real applications.   More than 200 programs and functions are provided in the MATLAB® language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.  Following on from the first volume, this second installation takes a more practical stance, provi

  5. Digital signal and image processing using MATLAB

    CERN Document Server

    Blanchet , Gérard

    2014-01-01

    This fully revised and updated second edition presents the most important theoretical aspects of Image and Signal Processing (ISP) for both deterministic and random signals. The theory is supported by exercises and computer simulations relating to real applications. More than 200 programs and functions are provided in the MATLABÒ language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject. This fully revised new edition updates : - the

  6. Invariance algorithms for processing NDE signals

    Science.gov (United States)

    Mandayam, Shreekanth; Udpa, Lalita; Udpa, Satish S.; Lord, William

    1996-11-01

    Signals that are obtained in a variety of nondestructive evaluation (NDE) processes capture information not only about the characteristics of the flaw, but also reflect variations in the specimen's material properties. Such signal changes may be viewed as anomalies that could obscure defect related information. An example of this situation occurs during in-line inspection of gas transmission pipelines. The magnetic flux leakage (MFL) method is used to conduct noninvasive measurements of the integrity of the pipe-wall. The MFL signals contain information both about the permeability of the pipe-wall and the dimensions of the flaw. Similar operational effects can be found in other NDE processes. This paper presents algorithms to render NDE signals invariant to selected test parameters, while retaining defect related information. Wavelet transform based neural network techniques are employed to develop the invariance algorithms. The invariance transformation is shown to be a necessary pre-processing step for subsequent defect characterization and visualization schemes. Results demonstrating the successful application of the method are presented.

  7. Advanced Signal Processing for Wireless Multimedia Communications

    Directory of Open Access Journals (Sweden)

    Xiaodong Wang

    2000-01-01

    Full Text Available There is at present a worldwide effort to develop next-generation wireless communication systems. It is envisioned that many of the future wireless systems will incorporate considerable signal-processing intelligence in order to provide advanced services such as multimedia transmission. In general, wireless channels can be very hostile media through which to communicate, due to substantial physical impediments, primarily radio-frequency interference and time-arying nature of the channel. The need of providing universal wireless access at high data-rate (which is the aim of many merging wireless applications presents a major technical challenge, and meeting this challenge necessitates the development of advanced signal processing techniques for multiple-access communications in non-stationary interference-rich environments. In this paper, we present some key advanced signal processing methodologies that have been developed in recent years for interference suppression in wireless networks. We will focus primarily on the problem of jointly suppressing multiple-access interference (MAI and intersymbol interference (ISI, which are the limiting sources of interference for the high data-rate wireless systems being proposed for many emerging application areas, such as wireless multimedia. We first present a signal subspace approach to blind joint suppression of MAI and ISI. We then discuss a powerful iterative technique for joint interference suppression and decoding, so-called Turbo multiuser detection, that is especially useful for wireless multimedia packet communications. We also discuss space-time processing methods that employ multiple antennas for interference rejection and signal enhancement. Finally, we touch briefly on the problems of suppressing narrowband interference and impulsive ambient noise, two other sources of radio-frequency interference present in wireless multimedia networks.

  8. Multivariable adaptive control of bio process

    Energy Technology Data Exchange (ETDEWEB)

    Maher, M.; Bahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Maher, M. [Faculte des Sciences, Rabat (Morocco). Lab. de Physique

    1995-12-31

    This paper presents a multivariable adaptive control of a continuous-flow fermentation process for the alcohol production. The linear quadratic control strategy is used for the regulation of substrate and ethanol concentrations in the bioreactor. The control inputs are the dilution rate and the influent substrate concentration. A robust identification algorithm is used for the on-line estimation of linear MIMO model`s parameters. Experimental results of a pilot-plant fermenter application are reported and show the control performances. (authors) 8 refs.

  9. Adaptive Layer Height During DLP Materials Processing

    DEFF Research Database (Denmark)

    Pedersen, David Bue; Zhang, Yang; Nielsen, Jakob Skov

    2016-01-01

    for considerable process speedup during the Additive Manufacture of components that contain areas of low cross-section variability, at no loss of surface quality. The adaptive slicing strategy was tested with a purpose built vat polymerisation system and numerical engine designed and constructed to serve as a Next......-Gen technology platform. By means of assessing hemispherical manufactured test specimen and through 3D surface mapping with variable-focus microscopy and confocal microscopy, a balance between minimal loss of surface quality with a maximal increase of manufacturing rate has been identified as a simple angle...

  10. Partial Adaptation of Obtained and Observed Value Signals Preserves Information about Gains and Losses.

    Science.gov (United States)

    Burke, Christopher J; Baddeley, Michelle; Tobler, Philippe N; Schultz, Wolfram

    2016-09-28

    Given that the range of rewarding and punishing outcomes of actions is large but neural coding capacity is limited, efficient processing of outcomes by the brain is necessary. One mechanism to increase efficiency is to rescale neural output to the range of outcomes expected in the current context, and process only experienced deviations from this expectation. However, this mechanism comes at the cost of not being able to discriminate between unexpectedly low losses when times are bad versus unexpectedly high gains when times are good. Thus, too much adaptation would result in disregarding information about the nature and absolute magnitude of outcomes, preventing learning about the longer-term value structure of the environment. Here we investigate the degree of adaptation in outcome coding brain regions in humans, for directly experienced outcomes and observed outcomes. We scanned participants while they performed a social learning task in gain and loss blocks. Multivariate pattern analysis showed two distinct networks of brain regions adapt to the most likely outcomes within a block. Frontostriatal areas adapted to directly experienced outcomes, whereas lateral frontal and temporoparietal regions adapted to observed social outcomes. Critically, in both cases, adaptation was incomplete and information about whether the outcomes arose in a gain block or a loss block was retained. Univariate analysis confirmed incomplete adaptive coding in these regions but also detected nonadapting outcome signals. Thus, although neural areas rescale their responses to outcomes for efficient coding, they adapt incompletely and keep track of the longer-term incentives available in the environment. Optimal value-based choice requires that the brain precisely and efficiently represents positive and negative outcomes. One way to increase efficiency is to adapt responding to the most likely outcomes in a given context. However, too strong adaptation would result in loss of precise

  11. Processing Electromyographic Signals to Recognize Words

    Science.gov (United States)

    Jorgensen, C. C.; Lee, D. D.

    2009-01-01

    A recently invented speech-recognition method applies to words that are articulated by means of the tongue and throat muscles but are otherwise not voiced or, at most, are spoken sotto voce. This method could satisfy a need for speech recognition under circumstances in which normal audible speech is difficult, poses a hazard, is disturbing to listeners, or compromises privacy. The method could also be used to augment traditional speech recognition by providing an additional source of information about articulator activity. The method can be characterized as intermediate between (1) conventional speech recognition through processing of voice sounds and (2) a method, not yet developed, of processing electroencephalographic signals to extract unspoken words directly from thoughts. This method involves computational processing of digitized electromyographic (EMG) signals from muscle innervation acquired by surface electrodes under a subject's chin near the tongue and on the side of the subject s throat near the larynx. After preprocessing, digitization, and feature extraction, EMG signals are processed by a neural-network pattern classifier, implemented in software, that performs the bulk of the recognition task as described.

  12. An adaptive segment method for smoothing lidar signal based on noise estimation

    Science.gov (United States)

    Wang, Yuzhao; Luo, Pingping

    2014-10-01

    An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

  13. Real-time adaptive concepts in acoustics blind signal separation and multichannel echo cancellation

    CERN Document Server

    Schobben, Daniel W E

    2001-01-01

    Blind Signal Separation (BSS) deals with recovering (filtered versions of) source signals from an observed mixture thereof. The term `blind' relates to the fact that there are no reference signals for the source signals and also that the mixing system is unknown. This book presents a new method for blind signal separation, which is developed to work on microphone signals. Acoustic Echo Cancellation (AEC) is a well-known technique to suppress the echo that a microphone picks up from a loudspeaker in the same room. Such acoustic feedback occurs for example in hands-free telephony and can lead to a perceived loud tone. For an application such as a voice-controlled television, a stereo AEC is required to suppress the contribution of the stereo loudspeaker setup. A generalized AEC is presented that is suited for multi-channel operation. New algorithms for Blind Signal Separation and multi-channel Acoustic Echo Cancellation are presented. A background is given in array signal processing methods, adaptive filter the...

  14. Signals, processes, and systems an interactive multimedia introduction to signal processing

    CERN Document Server

    Karrenberg, Ulrich

    2013-01-01

    This is a very new concept for learning Signal Processing, not only from the physically-based scientific fundamentals, but also from the didactic perspective, based on modern results of brain research. The textbook together with the DVD form a learning system that provides investigative studies and enables the reader to interactively visualize even complex processes. The unique didactic concept is built on visualizing signals and processes on the one hand, and on graphical programming of signal processing systems on the other. The concept has been designed especially for microelectronics, computer technology and communication. The book allows to develop, modify, and optimize useful applications using DasyLab - a professional and globally supported software for metrology and control engineering. With the 3rd edition, the software is also suitable for 64 bit systems running on Windows 7. Real signals can be acquired, processed and played on the sound card of your computer. The book provides more than 200 pre-pr...

  15. Extraction of ECG signal with adaptive filter for hearth abnormalities detection

    Science.gov (United States)

    Turnip, Mardi; Saragih, Rijois. I. E.; Dharma, Abdi; Esti Kusumandari, Dwi; Turnip, Arjon; Sitanggang, Delima; Aisyah, Siti

    2018-04-01

    This paper demonstrates an adaptive filter method for extraction ofelectrocardiogram (ECG) feature in hearth abnormalities detection. In particular, electrocardiogram (ECG) is a recording of the heart's electrical activity by capturing a tracingof cardiac electrical impulse as it moves from the atrium to the ventricles. The applied algorithm is to evaluate and analyze ECG signals for abnormalities detection based on P, Q, R and S peaks. In the first phase, the real-time ECG data is acquired and pre-processed. In the second phase, the procured ECG signal is subjected to feature extraction process. The extracted features detect abnormal peaks present in the waveform. Thus the normal and abnormal ECG signal could be differentiated based on the features extracted.

  16. Haptic teleoperation systems signal processing perspective

    CERN Document Server

    Lee, Jae-young

    2015-01-01

    This book examines the signal processing perspective in haptic teleoperation systems. This text covers the topics of prediction, estimation, architecture, data compression, and error correction that can be applied to haptic teleoperation systems. The authors begin with an overview of haptic teleoperation systems, then look at a Bayesian approach to haptic teleoperation systems. They move onto a discussion of haptic data compression, haptic data digitization and forward error correction.   ·         Presents haptic data prediction/estimation methods that compensate for unreliable networks   ·         Discusses haptic data compression that reduces haptic data size over limited network bandwidth and haptic data error correction that compensate for packet loss problem   ·         Provides signal processing techniques used with existing control architectures.

  17. Genomic signal processing for DNA sequence clustering.

    Science.gov (United States)

    Mendizabal-Ruiz, Gerardo; Román-Godínez, Israel; Torres-Ramos, Sulema; Salido-Ruiz, Ricardo A; Vélez-Pérez, Hugo; Morales, J Alejandro

    2018-01-01

    Genomic signal processing (GSP) methods which convert DNA data to numerical values have recently been proposed, which would offer the opportunity of employing existing digital signal processing methods for genomic data. One of the most used methods for exploring data is cluster analysis which refers to the unsupervised classification of patterns in data. In this paper, we propose a novel approach for performing cluster analysis of DNA sequences that is based on the use of GSP methods and the K-means algorithm. We also propose a visualization method that facilitates the easy inspection and analysis of the results and possible hidden behaviors. Our results support the feasibility of employing the proposed method to find and easily visualize interesting features of sets of DNA data.

  18. Signal processing method for Johnson noise thermometry

    International Nuclear Information System (INIS)

    Hwang, I. G.; Moon, B. S.; Kinser, Rpger

    2003-01-01

    The development of Johnson Noise Thermometry requires a high sensitive preamplifier circuit to pick up the temperature-related noise on the sensing element. However, the random noise generated in this amplification circuit causes a significant erroneous influence to the measurement. This paper describes signal processing mechanism of the Johnson Noise Thermometry system which is underway of development in collaboration between KAERI and ORNL. It adopts two identical amplifier channels and utilizes a digital signal processing technique to remove the independent noise of each channel. The CPSD(Cross Power Spectral Density) function is used to cancel the independent noise and the differentiation of narrow or single frequency peak from the CPSD data separates the common mode electromagnetic interference noise

  19. Visible light communications modulation and signal processing

    CERN Document Server

    Wang, Zhaocheng; Huang, Wei; Xu, Zhengyuan

    2018-01-01

    This informative new book on state-of-the-art visible light communication (VLC) provides, for the first time, a systematical and advanced treatment of modulation and signal processing for VLC. Visible Light Communications: Modulation and Signal Processing offers a practical guide to designing VLC, linking academic research with commercial applications. In recent years, VLC has attracted attention from academia and industry since it has many advantages over the traditional radio frequency, including wide unregulated bandwidth, high security, and low cost. It is a promising complementary technique in 5G and beyond wireless communications, especially in indoor applications. However, lighting constraints have not been fully considered in the open literature when considering VLC system design, and its importance has been underestimated. That’s why this book—written by a team of experts with both academic research experience and industrial development experience in the field—is so welcome. To help readers u...

  20. Electron quantum optics as quantum signal processing

    OpenAIRE

    Roussel, B.; Cabart, C.; Fève, G.; Thibierge, E.; Degiovanni, P.

    2016-01-01

    The recent developments of electron quantum optics in quantum Hall edge channels have given us new ways to probe the behavior of electrons in quantum conductors. It has brought new quantities called electronic coherences under the spotlight. In this paper, we explore the relations between electron quantum optics and signal processing through a global review of the various methods for accessing single- and two-electron coherences in electron quantum optics. We interpret electron quantum optics...

  1. Hot topics: Signal processing in acoustics

    Science.gov (United States)

    Gaumond, Charles F.

    2005-09-01

    Signal processing in acoustics is a multidisciplinary group of people that work in many areas of acoustics. We have chosen two areas that have shown exciting new applications of signal processing to acoustics or have shown exciting and important results from the use of signal processing. In this session, two hot topics are shown: the use of noiselike acoustic fields to determine sound propagation structure and the use of localization to determine animal behaviors. The first topic shows the application of correlation on geo-acoustic fields to determine the Greens function for propagation through the Earth. These results can then be further used to solve geo-acoustic inverse problems. The first topic also shows the application of correlation using oceanic noise fields to determine the Greens function through the ocean. These results also have utility for oceanic inverse problems. The second topic shows exciting results from the detection, localization, and tracking of marine mammals by two different groups. Results from detection and localization of bullfrogs are shown, too. Each of these studies contributed to the knowledge of animal behavior. [Work supported by ONR.

  2. Signal processing for the profoundly deaf.

    Science.gov (United States)

    Boothyroyd, A

    1990-01-01

    Profound deafness, defined here as a hearing loss in excess of 90 dB, is characterized by high thresholds, reduced hearing range in the intensity and frequency domains, and poor resolution in the frequency and time domains. The high thresholds call for hearing aids with unusually high gains or remote microphones that can be placed close to the signal source. The former option creates acoustic feedback problems for which digital signal processing may yet offer solutions. The latter option calls for carrier wave technology that is already available. The reduced frequency and intensity ranges would appear to call for frequency and/or amplitude compression. It might also be argued, however, that any attempts to compress the acoustic signal into the limited hearing range of the profoundly deaf will be counterproductive because of poor frequency and time resolution, especially when the signal is present in noise. In experiments with a 2-channel compression system, only 1 of 9 subjects showed an improvement of perception with the introduction of fast-release (20 ms) compression. The other 8 experienced no benefit or a slight deterioration of performance. These results support the concept of providing the profoundly deaf with simpler, rather than more complex, patterns, perhaps through the use of feature extraction hearing aids. Data from users of cochlear implants already employing feature extraction techniques also support this concept.

  3. Modeling, estimation and optimal filtration in signal processing

    CERN Document Server

    Najim, Mohamed

    2010-01-01

    The purpose of this book is to provide graduate students and practitioners with traditional methods and more recent results for model-based approaches in signal processing.Firstly, discrete-time linear models such as AR, MA and ARMA models, their properties and their limitations are introduced. In addition, sinusoidal models are addressed.Secondly, estimation approaches based on least squares methods and instrumental variable techniques are presented.Finally, the book deals with optimal filters, i.e. Wiener and Kalman filtering, and adaptive filters such as the RLS, the LMS and the

  4. ADAPTATION PROCESS TO CLIMATE CHANGE IN AGRICULTURE- AN EMPIRICAL STUDY

    Directory of Open Access Journals (Sweden)

    Ghulam Mustafa

    2017-10-01

    Full Text Available Climatic variations affect agriculture in a process with no known end means. Adaptations help to reduce the adverse impacts of climate change. Unfortunately, adaptation has never been considered as a process. Current study empirically identified the adaptation process and its different stages. Moreover, little is known about the farm level adaptation strategies and their determinants. The study in hand found farm level adaptation strategies and determinants of these strategies. The study identified three stages of adaptation i.e. perception, intention and adaptation. It was found that 71.4% farmers perceived about climate change, 58.5% intended to adapt while 40.2% actually adapted. The study further explored that farmers do adaptations through changing crop variety (56.3%, changing planting dates (44.6%, tree plantation (37.5%, increase/conserve irrigation (39.3% and crop diversification (49.2%. The adaptation strategies used by farmers were autonomous and mostly determined perception to climate change. It was also noted that the adaptation strategies move in a circular process and once they are adapted they remained adapted for a longer period of time. Some constraints slow the adaptation process so; we recommend farmers should be given price incentives to speed-up this process.

  5. Extracellular signal-regulated protein kinases 1 and 2 activation by addictive drugs: a signal toward pathological adaptation.

    Science.gov (United States)

    Pascoli, Vincent; Cahill, Emma; Bellivier, Frank; Caboche, Jocelyne; Vanhoutte, Peter

    2014-12-15

    Addiction is a chronic and relapsing psychiatric disorder that is thought to occur in vulnerable individuals. Synaptic plasticity evoked by drugs of abuse in the so-called neuronal circuits of reward has been proposed to underlie behavioral adaptations that characterize addiction. By increasing dopamine in the striatum, addictive drugs alter the balance of dopamine and glutamate signals converging onto striatal medium-sized spiny neurons (MSNs) and activate intracellular events involved in long-term behavioral alterations. Our laboratory contributed to the identification of salient molecular changes induced by administration of addictive drugs to rodents. We pioneered the observation that a common feature of addictive drugs is to activate, by a double tyrosine/threonine phosphorylation, the extracellular signal-regulated kinases 1 and 2 (ERK1/2) in the striatum, which control a plethora of substrates, some of them being critically involved in cocaine-mediated molecular and behavioral adaptations. Herein, we review how the interplay between dopamine and glutamate signaling controls cocaine-induced ERK1/2 activation in MSNs. We emphasize the key role of N-methyl-D-aspartate receptor potentiation by D1 receptor to trigger ERK1/2 activation and its subsequent nuclear translocation where it modulates both epigenetic and genetic processes engaged by cocaine. We discuss how cocaine-induced long-term synaptic and structural plasticity of MSNs, as well as behavioral adaptations, are influenced by ERK1/2-controlled targets. We conclude that a better knowledge of molecular mechanisms underlying ERK1/2 activation by drugs of abuse and/or its role in long-term neuronal plasticity in the striatum may provide a new route for therapeutic treatment in addiction. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  6. Intelligent Adaptation Process for Case Based Systems

    International Nuclear Information System (INIS)

    Nassar, A.M.; Mohamed, A.H.; Mohamed, A.H.

    2014-01-01

    Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field

  7. EMD self-adaptive selecting relevant modes algorithm for FBG spectrum signal

    Science.gov (United States)

    Chen, Yong; Wu, Chun-ting; Liu, Huan-lin

    2017-07-01

    Noise may reduce the demodulation accuracy of fiber Bragg grating (FBG) sensing signal so as to affect the quality of sensing detection. Thus, the recovery of a signal from observed noisy data is necessary. In this paper, a precise self-adaptive algorithm of selecting relevant modes is proposed to remove the noise of signal. Empirical mode decomposition (EMD) is first used to decompose a signal into a set of modes. The pseudo modes cancellation is introduced to identify and eliminate false modes, and then the Mutual Information (MI) of partial modes is calculated. MI is used to estimate the critical point of high and low frequency components. Simulation results show that the proposed algorithm estimates the critical point more accurately than the traditional algorithms for FBG spectral signal. While, compared to the similar algorithms, the signal noise ratio of the signal can be improved more than 10 dB after processing by the proposed algorithm, and correlation coefficient can be increased by 0.5, so it demonstrates better de-noising effect.

  8. Unique portable signal acquisition/processing station

    International Nuclear Information System (INIS)

    Garron, R.D.; Azevedo, S.G.

    1983-01-01

    At Lawrence Livermore National Laboratory, there are experimental applications requiring digital signal acquisition as well as data reduction and analysis. A prototype Signal Acquisition/Processing Station (SAPS) has been constructed and is currently undergoing tests. The system employs an LSI-11/23 computer with Data Translation analog-to-digital hardware. SAPS is housed in a roll-around cart which has been designed to withstand most subtle EMI/RFI environments. A user-friendly menu allows a user to access powerful data acquisition packages with a minimum of training. The software architecture of SAPS involves two operating systems, each being transparent to the user. Since this is a general purpose workstation with several units being utilized, an emphasis on low cost, reliability, and maintenance was stressed during conception and design. The system is targeted for mid-range frequency data acquisition; between a data logger and a transient digitizer

  9. Integrated Circuits for Analog Signal Processing

    CERN Document Server

    2013-01-01

      This book presents theory, design methods and novel applications for integrated circuits for analog signal processing.  The discussion covers a wide variety of active devices, active elements and amplifiers, working in voltage mode, current mode and mixed mode.  This includes voltage operational amplifiers, current operational amplifiers, operational transconductance amplifiers, operational transresistance amplifiers, current conveyors, current differencing transconductance amplifiers, etc.  Design methods and challenges posed by nanometer technology are discussed and applications described, including signal amplification, filtering, data acquisition systems such as neural recording, sensor conditioning such as biomedical implants, actuator conditioning, noise generators, oscillators, mixers, etc.   Presents analysis and synthesis methods to generate all circuit topologies from which the designer can select the best one for the desired application; Includes design guidelines for active devices/elements...

  10. Adaptive Traffic Signal Control: Deep Reinforcement Learning Algorithm with Experience Replay and Target Network

    OpenAIRE

    Gao, Juntao; Shen, Yulong; Liu, Jia; Ito, Minoru; Shiratori, Norio

    2017-01-01

    Adaptive traffic signal control, which adjusts traffic signal timing according to real-time traffic, has been shown to be an effective method to reduce traffic congestion. Available works on adaptive traffic signal control make responsive traffic signal control decisions based on human-crafted features (e.g. vehicle queue length). However, human-crafted features are abstractions of raw traffic data (e.g., position and speed of vehicles), which ignore some useful traffic information and lead t...

  11. A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors

    Directory of Open Access Journals (Sweden)

    Hengwei Li

    2007-02-01

    Full Text Available In this paper, an approach is presented to detect faint signals with strong noises in sensors by stochastic resonance (SR. We adopt the power spectrum as the evaluation tool of SR, which can be obtained by the fast Fourier transform (FFT. Furthermore, we introduce the adaptive filtering scheme to realize signal processing automatically. The key of the scheme is how to adjust the barrier height to satisfy the optimal condition of SR in the presence of any input. For the given input signal, we present an operable procedure to execute the adjustment scheme. An example utilizing one audio sensor to detect the fault information from the power supply is given. Simulation results show that th

  12. Adaptive Fourier decomposition based R-peak detection for noisy ECG Signals.

    Science.gov (United States)

    Ze Wang; Chi Man Wong; Feng Wan

    2017-07-01

    An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.

  13. Digital signal processing at GEND's data center

    International Nuclear Information System (INIS)

    Jackson, J.E.

    1977-01-01

    The conversion and recording of analog signals in digital form has been an active element in the manufacturing operations of the General Electric Neutron Devices Department (GEND) since 1966. The first computerized data system for these digitized waveforms was implemented at GEND's data center approximately two years later during 1968. The evolution and integration of these two activities at GEND are addressed in this paper. Beginning with the tester--data center interface, emphasis is placed on previous approaches, current capabilities, near-term trends, and future requirements. The digitizing process has developed into a firmly established set of hardware and associated software techniques which has proven itself as an accurate, reliable procedure for capturing waveform characteristics. The most important aspect of this process is the recent trend toward increased sampling rates and a greater number of digitized parameters per operation. The combined effect is a tremendous increase in output data volumes. Since digital signal processing carries the potential for significant contributions to manufacturing quality and reliability, as well as engineering design and development, increased activity in this area appears extremely desirable. 11 figures

  14. Digital Signal Processing for Optical Coherent Communication Systems

    DEFF Research Database (Denmark)

    Zhang, Xu

    spectrum narrowing tolerance 112-Gb/s DP-QPSK optical coherent systems using digital adaptive equalizer. The demonstrated results show that off-line DSP algorithms are able to reduce the bit error rate (BER) penalty induced by signal spectrum narrowing. Third, we also investigate bi...... wavelength division multiplex (U-DWDM) optical coherent systems based on 10-Gbaud QPSK. We report U-DWDM 1.2-Tb/s QPSK coherent system achieving spectral efficiency of 4.0-bit/s/Hz. In the experimental demonstration, digital decision feed back equalizer (DFE) algorithms and a finite impulse response (FIR......In this thesis, digital signal processing (DSP) algorithms are studied to compensate for physical layer impairments in optical fiber coherent communication systems. The physical layer impairments investigated in this thesis include optical fiber chromatic dispersion, polarization demultiplexing...

  15. OPTIMAL SIGNAL PROCESSING METHODS IN GPR

    Directory of Open Access Journals (Sweden)

    Saeid Karamzadeh

    2014-01-01

    Full Text Available In the past three decades, a lot of various applications of Ground Penetrating Radar (GPR took place in real life. There are important challenges of this radar in civil applications and also in military applications. In this paper, the fundamentals of GPR systems will be covered and three important signal processing methods (Wavelet Transform, Matched Filter and Hilbert Huang will be compared to each other in order to get most accurate information about objects which are in subsurface or behind the wall.

  16. Power systems signal processing for smart grids

    CERN Document Server

    Ribeiro, Paulo Fernando; Ribeiro, Paulo Márcio; Cerqueira, Augusto Santiago

    2013-01-01

    With special relation to smart grids, this book provides clear and comprehensive explanation of how Digital Signal Processing (DSP) and Computational Intelligence (CI) techniques can be applied to solve problems in the power system. Its unique coverage bridges the gap between DSP, electrical power and energy engineering systems, showing many different techniques applied to typical and expected system conditions with practical power system examples. Surveying all recent advances on DSP for power systems, this book enables engineers and researchers to understand the current state of the art a

  17. Ultrafast Optical Signal Processing with Bragg Structures

    Directory of Open Access Journals (Sweden)

    Yikun Liu

    2017-05-01

    Full Text Available The phase, amplitude, speed, and polarization, in addition to many other properties of light, can be modulated by photonic Bragg structures. In conjunction with nonlinearity and quantum effects, a variety of ensuing micro- or nano-photonic applications can be realized. This paper reviews various optical phenomena in several exemplary 1D Bragg gratings. Important examples are resonantly absorbing photonic structures, chirped Bragg grating, and cholesteric liquid crystals; their unique operation capabilities and key issues are considered in detail. These Bragg structures are expected to be used in wide-spread applications involving light field modulations, especially in the rapidly advancing field of ultrafast optical signal processing.

  18. Fourier transforms in radar and signal processing

    CERN Document Server

    Brandwood, David

    2011-01-01

    Fourier transforms are used widely, and are of particular value in the analysis of single functions and combinations of functions found in radar and signal processing. Still, many problems that could have been tackled by using Fourier transforms may have gone unsolved because they require integration that is difficult and tedious. This newly revised and expanded edition of a classic Artech House book provides you with an up-to-date, coordinated system for performing Fourier transforms on a wide variety of functions. Along numerous updates throughout the book, the Second Edition includes a crit

  19. Three-dimensional image signals: processing methods

    Science.gov (United States)

    Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru

    2010-11-01

    Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

  20. BURAR: Detection and signal processing capabilities

    International Nuclear Information System (INIS)

    Ghica, Daniela; Radulian, Mircea; Popa, Mihaela

    2004-01-01

    Since July 2002, a new seismic monitoring station, the Bucovina Seismic Array (BURAR), has been installed in the northern part of Romania, in a joint effort of the Air Force Technical Applications Center, USA, and the National Institute for Earth Physics (NIEP), Romania. The array consists of 10 seismic sensors (9 short-period and one broad band) located in boreholes and distributed in a 5 x 5 km area. At present, the seismic data are continuously recorded by BURAR and transmitted in real-time to the Romanian National Data Centre (ROM N DC), at Bucharest and to the National Data Center of USA, in Florida. The statistical analysis for the seismic information gathered at ROM N DC by the BURAR in the August 2002 - December 2003 time interval points out a much better efficiency of the BURAR system in detecting teleseismic events and local events occurred in the N-NE part of Romanian territory, in comparison with the actual Romanian Telemetered Network. Furthermore, the BURAR monitoring system has proven to be an important source of reliable data for NIEP efforts in elaborating of the seismic bulletins. Signal processing capability of the system provides useful information in order to improve the location of the local seismic events, using the array beamforming facility. This method increases significantly the signal-to-noise ratio of the seismic signal by summing up the coherent signals from the array components. In this way, eventual source nucleation phases can be detected. At the same time, using the slowness and backazimuth estimations by f-k analysis, locations for the seismic events can be performed based only on the information recorded by the BURAR array, acting like a single seismic station recording system. Additionally, f-k analysis techniques are useful in the local site effects estimation and interpretation of the local geological structure. (authors)

  1. Adapted diffusion processes for effective forging dies

    Science.gov (United States)

    Paschke, H.; Nienhaus, A.; Brunotte, K.; Petersen, T.; Siegmund, M.; Lippold, L.; Weber, M.; Mejauschek, M.; Landgraf, P.; Braeuer, G.; Behrens, B.-A.; Lampke, T.

    2018-05-01

    Hot forging is an effective production method producing safety relevant parts with excellent mechanical properties. The economic efficiency directly depends on the occurring wear of the tools, which limits service lifetime. Several approaches of the presenting research group aim at minimizing the wear caused by interacting mechanical and thermal loads by using enhanced nitriding technology. Thus, by modifying the surface zone layer it is possible to create a resistance against thermal softening provoking plastic deformation and pronounced abrasive wear. As a disadvantage, intensely nitrided surfaces may possibly include the risk of increased crack sensitivity and therefore feature the chipping of material at the treated surface. Recent projects (evaluated in several industrial applications) show the high technological potential of adapted treatments: A first approach evaluated localized treatments by preventing areas from nitrogen diffusion with applied pastes or other coverages. Now, further ideas are to use this principle to structure the surface with differently designed patterns generating smaller ductile zones beneath nitrided ones. The selection of suitable designs is subject to certain geo-metrical requirements though. The intention of this approach is to prevent the formation and propagation of cracks under thermal shock conditions. Analytical characterization methods for crack sensitivity of surface zone layers and an accurate system of testing rigs for thermal shock conditions verified the treatment concepts. Additionally, serial forging tests using adapted testing geometries and finally, tests in the industrial production field were performed. Besides stabilizing the service lifetime and decreasing specific wear mechanisms caused by thermal influences, the crack behavior was influenced positively. This leads to a higher efficiency of the industrial production process and enables higher output in forging campaigns of industrial partners.

  2. The Urban Adaptation and Adaptation Process of Urban Migrant Children: A Qualitative Study

    Science.gov (United States)

    Liu, Yang; Fang, Xiaoyi; Cai, Rong; Wu, Yang; Zhang, Yaofang

    2009-01-01

    This article employs qualitative research methods to explore the urban adaptation and adaptation processes of Chinese migrant children. Through twenty-one in-depth interviews with migrant children, the researchers discovered: The participant migrant children showed a fairly high level of adaptation to the city; their process of urban adaptation…

  3. Nonlinear signal processing using neural networks: Prediction and system modelling

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

    The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

  4. A novel approach for SEMG signal classification with adaptive local binary patterns.

    Science.gov (United States)

    Ertuğrul, Ömer Faruk; Kaya, Yılmaz; Tekin, Ramazan

    2016-07-01

    Feature extraction plays a major role in the pattern recognition process, and this paper presents a novel feature extraction approach, adaptive local binary pattern (aLBP). aLBP is built on the local binary pattern (LBP), which is an image processing method, and one-dimensional local binary pattern (1D-LBP). In LBP, each pixel is compared with its neighbors. Similarly, in 1D-LBP, each data in the raw is judged against its neighbors. 1D-LBP extracts feature based on local changes in the signal. Therefore, it has high a potential to be employed in medical purposes. Since, each action or abnormality, which is recorded in SEMG signals, has its own pattern, and via the 1D-LBP these (hidden) patterns may be detected. But, the positions of the neighbors in 1D-LBP are constant depending on the position of the data in the raw. Also, both LBP and 1D-LBP are very sensitive to noise. Therefore, its capacity in detecting hidden patterns is limited. To overcome these drawbacks, aLBP was proposed. In aLBP, the positions of the neighbors and their values can be assigned adaptively via the down-sampling and the smoothing coefficients. Therefore, the potential to detect (hidden) patterns, which may express an illness or an action, is really increased. To validate the proposed feature extraction approach, two different datasets were employed. Achieved accuracies by the proposed approach were higher than obtained results by employed popular feature extraction approaches and the reported results in the literature. Obtained accuracy results were brought out that the proposed method can be employed to investigate SEMG signals. In summary, this work attempts to develop an adaptive feature extraction scheme that can be utilized for extracting features from local changes in different categories of time-varying signals.

  5. Adaptive Filtering for Non-Gaussian Processes

    DEFF Research Database (Denmark)

    Kidmose, Preben

    2000-01-01

    A new stochastic gradient robust filtering method, based on a non-linear amplitude transformation, is proposed. The method requires no a priori knowledge of the characteristics of the input signals and it is insensitive to the signals distribution and to the stationarity of the signals. A simulat...

  6. Active voltammetric microsensors with neural signal processing.

    Energy Technology Data Exchange (ETDEWEB)

    Vogt, M. C.

    1998-12-11

    Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical ''signatures'' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration, the calibration, sensing, and processing methods of these active voltammetric microsensors can

  7. Active voltammetric microsensors with neural signal processing

    Science.gov (United States)

    Vogt, Michael C.; Skubal, Laura R.

    1999-02-01

    Many industrial and environmental processes, including bioremediation, would benefit from the feedback and control information provided by a local multi-analyte chemical sensor. For most processes, such a sensor would need to be rugged enough to be placed in situ for long-term remote monitoring, and inexpensive enough to be fielded in useful numbers. The multi-analyte capability is difficult to obtain from common passive sensors, but can be provided by an active device that produces a spectrum-type response. Such new active gas microsensor technology has been developed at Argonne National Laboratory. The technology couples an electrocatalytic ceramic-metallic (cermet) microsensor with a voltammetric measurement technique and advanced neural signal processing. It has been demonstrated to be flexible, rugged, and very economical to produce and deploy. Both narrow interest detectors and wide spectrum instruments have been developed around this technology. Much of this technology's strength lies in the active measurement technique employed. The technique involves applying voltammetry to a miniature electrocatalytic cell to produce unique chemical 'signatures' from the analytes. These signatures are processed with neural pattern recognition algorithms to identify and quantify the components in the analyte. The neural signal processing allows for innovative sampling and analysis strategies to be employed with the microsensor. In most situations, the whole response signature from the voltammogram can be used to identify, classify, and quantify an analyte, without dissecting it into component parts. This allows an instrument to be calibrated once for a specific gas or mixture of gases by simple exposure to a multi-component standard rather than by a series of individual gases. The sampled unknown analytes can vary in composition or in concentration; the calibration, sensing, and processing methods of these active voltammetric microsensors can detect, recognize, and

  8. Uniform, optimal signal processing of mapped deep-sequencing data.

    Science.gov (United States)

    Kumar, Vibhor; Muratani, Masafumi; Rayan, Nirmala Arul; Kraus, Petra; Lufkin, Thomas; Ng, Huck Hui; Prabhakar, Shyam

    2013-07-01

    Despite their apparent diversity, many problems in the analysis of high-throughput sequencing data are merely special cases of two general problems, signal detection and signal estimation. Here we adapt formally optimal solutions from signal processing theory to analyze signals of DNA sequence reads mapped to a genome. We describe DFilter, a detection algorithm that identifies regulatory features in ChIP-seq, DNase-seq and FAIRE-seq data more accurately than assay-specific algorithms. We also describe EFilter, an estimation algorithm that accurately predicts mRNA levels from as few as 1-2 histone profiles (R ∼0.9). Notably, the presence of regulatory motifs in promoters correlates more with histone modifications than with mRNA levels, suggesting that histone profiles are more predictive of cis-regulatory mechanisms. We show by applying DFilter and EFilter to embryonic forebrain ChIP-seq data that regulatory protein identification and functional annotation are feasible despite tissue heterogeneity. The mathematical formalism underlying our tools facilitates integrative analysis of data from virtually any sequencing-based functional profile.

  9. BURAR: Detection and signal processing capabilities

    International Nuclear Information System (INIS)

    Ghica, Daniela; Radulian, Mircea; Popa, Mihaela

    2004-01-01

    Since July 2002, a new seismic monitoring station, the Bucovina Seismic Array (BURAR), has been installed in the northern part of Romania, in a joint effort of the Air Force Technical Applications Center, USA, and the National Institute for Earth Physics (NIEP), Romania. The array consists of 10 seismic sensors (9 short-period and one broad band) located in boreholes and distributed in a 5 x 5 km 2 area. At present, the seismic data are continuously recorded by BURAR and transmitted in real-time to the Romanian National Data Centre (ROM N DC), in Bucharest and to the National Data Center of USA, in Florida. The statistical analysis for the seismic information gathered at ROM N DC by the BURAR in the August 2002 - December 2003 time interval points out a much better efficiency of the BURAR system in detecting teleseismic events and local events occurred in the N-NE part of Romanian territory, in comparison with the actual Romanian Telemetered Network. Furthermore, the BURAR monitoring system has proven to be an important source of reliable data for NIEP efforts in issuing the seismic bulletins. Signal processing capability of the system provides useful information in order to improve the location of the local seismic events, using the array beamforming procedure. This method increases significantly the signal-to-noise ratio by summing up the coherent signals from the array components. In this way, possible source nucleation phases can be detected. At the same time, using the slowness and back azimuth estimations by f-k analysis, locations for the seismic events can be established based only on the information recorded by the BURAR array, acting like a single seismic station recording system. (authors)

  10. Signal processing issues in reflection tomography

    Science.gov (United States)

    Cadalli, Nail

    2001-12-01

    This dissertation focuses on signal modeling and processing issues of the following problems in reflection tomography: synthetic aperture radar (SAR) imaging of a runway and surroundings from an aircraft approaching for landing, acoustic imaging of objects buried in soil, and lidar imaging of underwater objects. The highly squinted geometry of runway imaging necessitates the incorporation of wavefront curvature into the signal model. We investigate the feasibility of using the wavenumber-domain (ω - k) SAR inversion algorithm, which models the actual curvature of the wavefront, for runway imaging. We demonstrate the aberrations that the algorithm can produce when the squint angle is close to 90° and show that high-quality reconstruction is still possible provided that the interpolation is performed accurately enough, which can be achieved by increasing the temporal sampling rate. We compare the performance with that of a more general inversion method (GIM) that solves the measurement equation directly. The performances of both methods are comparable in the noise- free case. Being inherently robust to noise, GIM produces superior results in the noisy case. We also present a solution to the left-right ambiguity of runway imaging using interferometric processing. In imaging of objects buried in soil, we pursue an acoustic approach primarily for detection and imaging of cultural artifacts. We have developed a mathematical model and associated computer software in order to simulate the signals acquired by the actual experimental system, and a bistatic SAR-type algorithm for reconstruction. In the reconstructions from simulated data, objects were detectable, but near-field objects suffered from shifts and smears. To account for wavefront curvature, we formulated processing of the simulated data using the 3-D version of the monostatic ω - k algorithm. In lidar imaging of underwater objects, we formulate the problem as a 3-D tomographic reconstruction problem. We have

  11. Network measures for characterising team adaptation processes

    NARCIS (Netherlands)

    Barth, S.K.; Schraagen, J.M.C.; Schmettow, M.

    2015-01-01

    The aim of this study was to advance the conceptualisation of team adaptation by applying social network analysis (SNA) measures in a field study of a paediatric cardiac surgical team adapting to changes in task complexity and ongoing dynamic complexity. Forty surgical procedures were observed by

  12. A quantitative formulation of the dynamic behaviour of adaptation processes to ionizing radiation

    International Nuclear Information System (INIS)

    Pfandler, S.

    1999-12-01

    The discovery of adaptation processes in cells (i.e., increased resistance to effects of a challenge dose administered after a lower adapting dose) has fuelled the debate on possible cellular processes relevant for low dose exposures. However, numerous experiments on radioadaptive response do not provide a clear picture of the nature of adaptive response and the conditions under which it occurs. This work proposes a model that succeeds in modelling data obtained from various experiments on radioadaptation. The model assumes impaired DNA integrity as triggering signal for induction of adaptation. Induction of adaptive response is seen as two-phase process. First, ionizing radiation induces radicals by water radiolysis which give rise to specific DNA lesions. On the other hand, these lesions must be perceived and, in a way, processed by the cell, thereby creating the final signal necessary for the comprehensive adaptive response. This processing occurs through some event in S-phase and can be halted by local conformational changes of chromatin induced by ionizing radiation. Thus, the model assumes two counteracting processes that have to be balanced for the triggering signal of adaptation to occur, each of them related to different target volumes. This work comprises mathematical treatment of radical formation, DNA lesion induction and inhibition of local initiation of replication which finally provides functions that quantify the reduction of double strand breaks introduced by challenge doses in adapted cells as compared to non-adapted cells. Non-linear regression analyses based upon data from experiments on radioadaptation yield regression curves which describe existing data satisfactorily. Thus, it corroborates the existence of adaptive response as, in principle, universal feature of cells and specifies conditions which favor development of radioadaptation. (author)

  13. Signal Processing for Improved Wireless Receiver Performance

    DEFF Research Database (Denmark)

    Christensen, Lars P.B.

    2007-01-01

    This thesis is concerned with signal processing for improving the performance of wireless communication receivers for well-established cellular networks such as the GSM/EDGE and WCDMA/HSPA systems. The goal of doing so, is to improve the end-user experience and/or provide a higher system capacity...... by allowing an increased reuse of network resources. To achieve this goal, one must first understand the nature of the problem and an introduction is therefore provided. In addition, the concept of graph-based models and approximations for wireless communications is introduced along with various Belief...... Propagation (BP) methods for detecting the transmitted information, including the Turbo principle. Having established a framework for the research, various approximate detection schemes are discussed. First, the general form of linear detection is presented and it is argued that this may be preferable...

  14. Mathematical SETI Statistics, Signal Processing, Space Missions

    CERN Document Server

    Maccone, Claudio

    2012-01-01

    This book introduces the Statistical Drake Equation where, from a simple product of seven positive numbers, the Drake Equation is turned into the product of seven positive random variables. The mathematical consequences of this transformation are demonstrated and it is proven that the new random variable N for the number of communicating civilizations in the Galaxy must follow the lognormal probability distribution when the number of factors in the Drake equation is allowed to increase at will. Mathematical SETI also studies the proposed FOCAL (Fast Outgoing Cyclopean Astronomical Lens) space mission to the nearest Sun Focal Sphere at 550 AU and describes its consequences for future interstellar precursor missions and truly interstellar missions. In addition the author shows how SETI signal processing may be dramatically improved by use of the Karhunen-Loève Transform (KLT) rather than Fast Fourier Transform (FFT). Finally, he describes the efforts made to persuade the United Nations to make the central part...

  15. A simple approach to digital signal processing

    CERN Document Server

    Marven, Craig

    1996-01-01

    A readable, understandable introduction to DSP for professionals and students alike . . . This practical guide is a welcome alternative to more complicated introductions to DSP. It assumes no prior DSP experience and takes the reader step-by-step through the most basic signal processing concepts to more complex functions and devices, including sampling, filtering, frequency transforms, data compression, and even DSP design decisions. The guide provides clear, concise explanations and examples, while keeping mathematics to a minimum, to help develop a fundamental understanding of DSP. Other features include: * An extensive resource bibliography of more advanced DSP books. * An example of a typical DSP system development cycle, including tool descriptions. * A complete glossary of DSP-related acronyms Whether you're a working engineer looking into DSP for the first time or an undergraduate struggling to comprehend the subject, this engaging introduction provides easy access to the basic knowledge that will l...

  16. Signals, systems, transforms, and digital signal processing with Matlab

    CERN Document Server

    Corinthios, Michael

    2009-01-01

    Continuous-Time and Discrete-Time Signals and SystemsIntroductionContinuous-Time SignalsPeriodic FunctionsUnit Step FunctionGraphical Representation of FunctionsEven and Odd Parts of a FunctionDirac-Delta ImpulseBasic Properties of the Dirac-Delta ImpulseOther Important Properties of the ImpulseContinuous-Time SystemsCausality, StabilityExamples of Electrical Continuous-Time SystemsMechanical SystemsTransfer Function and Frequency ResponseConvolution and CorrelationA Right-Sided and a Left-Sided FunctionConvolution with an Impulse and Its DerivativesAdditional Convolution PropertiesCorrelation FunctionProperties of the Correlation FunctionGraphical InterpretationCorrelation of Periodic FunctionsAverage, Energy and Power of Continuous-Time SignalsDiscrete-Time SignalsPeriodicityDifference EquationsEven/Odd DecompositionAverage Value, Energy and Power SequencesCausality, StabilityProblemsAnswers to Selected ProblemsFourier Series ExpansionTrigonometric Fourier SeriesExponential Fourier SeriesExponential versus ...

  17. Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal

    Directory of Open Access Journals (Sweden)

    Shanzhi Xu

    2018-02-01

    Full Text Available The recorded electroencephalography (EEG signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

  18. Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

    Science.gov (United States)

    Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

    2018-02-26

    The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

  19. A Hybrid Fuzzy Genetic Algorithm for an Adaptive Traffic Signal System

    Directory of Open Access Journals (Sweden)

    S. M. Odeh

    2015-01-01

    Full Text Available This paper presents a hybrid algorithm that combines Fuzzy Logic Controller (FLC and Genetic Algorithms (GAs and its application on a traffic signal system. FLCs have been widely used in many applications in diverse areas, such as control system, pattern recognition, signal processing, and forecasting. They are, essentially, rule-based systems, in which the definition of these rules and fuzzy membership functions is generally based on verbally formulated rules that overlap through the parameter space. They have a great influence over the performance of the system. On the other hand, the Genetic Algorithm is a metaheuristic that provides a robust search in complex spaces. In this work, it has been used to adapt the decision rules of FLCs that define an intelligent traffic signal system, obtaining a higher performance than a classical FLC-based control. The simulation results yielded by the hybrid algorithm show an improvement of up to 34% in the performance with respect to a standard traffic signal controller, Conventional Traffic Signal Controller (CTC, and up to 31% in the comparison with a traditional logic controller, FLC.

  20. On Organizational Adaptation via Dynamic Process Selection

    National Research Council Canada - National Science Library

    Handley, Holly A; Levis, Alexander H

    2000-01-01

    .... An executable organizational model composed of individual models of a five stage interacting decision maker is used to evaluate the effectiveness of the different adaptation strategies on organizational performance...

  1. Modular and Adaptive Control of Sound Processing

    Science.gov (United States)

    van Nort, Douglas

    parameters. In this view, desired gestural dynamics and sonic response are achieved through modular construction of mapping layers that are themselves subject to parametric control. Complementing this view of the design process, the work concludes with an approach in which the creation of gestural control/sound dynamics are considered in the low-level of the underlying sound model. The result is an adaptive system that is specialized to noise-based transformations that are particularly relevant in an electroacoustic music context. Taken together, these different approaches to design and evaluation result in a unified framework for creation of an instrumental system. The key point is that this framework addresses the influence that mapping structure and control dynamics have on the perceived feel of the instrument. Each of the results illustrate this using either top-down or bottom-up approaches that consider musical control context, thereby pointing to the greater potential for refined sonic articulation that can be had by combining them in the design process.

  2. IEEE International Workshop on Machine Learning for Signal Processing: Preface

    DEFF Research Database (Denmark)

    Tao, Jianhua

    The 21st IEEE International Workshop on Machine Learning for Signal Processing will be held in Beijing, China, on September 18–21, 2011. The workshop series is the major annual technical event of the IEEE Signal Processing Society's Technical Committee on Machine Learning for Signal Processing...

  3. The influence of negative stimulus features on conflict adaption:Evidence from fluency of processing

    Directory of Open Access Journals (Sweden)

    Julia eFritz

    2015-02-01

    Full Text Available Cognitive control enables adaptive behavior in a dynamically changing environment. In this context, one prominent adaptation effect is the sequential conflict adjustment, i.e. the observation of reduced response interference on trials following conflict trials. Increasing evidence suggests that such response conflicts are registered as aversive signals. So far, however, the functional role of this aversive signal for conflict adaptation to occur has not been put to test directly. In two experiments, the affective valence of conflict stimuli was manipulated by fluency of processing (stimulus contrast. Experiment 1 used a flanker interference task, Experiment 2 a color-word Stroop task. In both experiments, conflict adaptation effects were only present in fluent, but absent in disfluent trials. Results thus speak against the simple idea that any aversive stimulus feature is suited to promote specific conflict adjustments. Two alternative but not mutually exclusive accounts, namely resource competition and adaptation-by-motivation, will be discussed.

  4. Perceptual Coding of Audio Signals Using Adaptive Time-Frequency Transform

    Directory of Open Access Journals (Sweden)

    Umapathy Karthikeyan

    2007-01-01

    Full Text Available Wide band digital audio signals have a very high data-rate associated with them due to their complex nature and demand for high-quality reproduction. Although recent technological advancements have significantly reduced the cost of bandwidth and miniaturized storage facilities, the rapid increase in the volume of digital audio content constantly compels the need for better compression algorithms. Over the years various perceptually lossless compression techniques have been introduced, and transform-based compression techniques have made a significant impact in recent years. In this paper, we propose one such transform-based compression technique, where the joint time-frequency (TF properties of the nonstationary nature of the audio signals were exploited in creating a compact energy representation of the signal in fewer coefficients. The decomposition coefficients were processed and perceptually filtered to retain only the relevant coefficients. Perceptual filtering (psychoacoustics was applied in a novel way by analyzing and performing TF specific psychoacoustics experiments. An added advantage of the proposed technique is that, due to its signal adaptive nature, it does not need predetermined segmentation of audio signals for processing. Eight stereo audio signal samples of different varieties were used in the study. Subjective (mean opinion score—MOS listening tests were performed and the subjective difference grades (SDG were used to compare the performance of the proposed coder with MP3, AAC, and HE-AAC encoders. Compression ratios in the range of 8 to 40 were achieved by the proposed technique with subjective difference grades (SDG ranging from –0.53 to –2.27.

  5. Perceptual Coding of Audio Signals Using Adaptive Time-Frequency Transform

    Directory of Open Access Journals (Sweden)

    Karthikeyan Umapathy

    2007-08-01

    Full Text Available Wide band digital audio signals have a very high data-rate associated with them due to their complex nature and demand for high-quality reproduction. Although recent technological advancements have significantly reduced the cost of bandwidth and miniaturized storage facilities, the rapid increase in the volume of digital audio content constantly compels the need for better compression algorithms. Over the years various perceptually lossless compression techniques have been introduced, and transform-based compression techniques have made a significant impact in recent years. In this paper, we propose one such transform-based compression technique, where the joint time-frequency (TF properties of the nonstationary nature of the audio signals were exploited in creating a compact energy representation of the signal in fewer coefficients. The decomposition coefficients were processed and perceptually filtered to retain only the relevant coefficients. Perceptual filtering (psychoacoustics was applied in a novel way by analyzing and performing TF specific psychoacoustics experiments. An added advantage of the proposed technique is that, due to its signal adaptive nature, it does not need predetermined segmentation of audio signals for processing. Eight stereo audio signal samples of different varieties were used in the study. Subjective (mean opinion score—MOS listening tests were performed and the subjective difference grades (SDG were used to compare the performance of the proposed coder with MP3, AAC, and HE-AAC encoders. Compression ratios in the range of 8 to 40 were achieved by the proposed technique with subjective difference grades (SDG ranging from –0.53 to –2.27.

  6. Wavelet-Based Signal Processing of Electromagnetic Pulse Generated Waveforms

    National Research Council Canada - National Science Library

    Ardolino, Richard S

    2007-01-01

    This thesis investigated and compared alternative signal processing techniques that used wavelet-based methods instead of traditional frequency domain methods for processing measured electromagnetic pulse (EMP) waveforms...

  7. Neutron coincidence counting with digital signal processing

    International Nuclear Information System (INIS)

    Bagi, Janos; Dechamp, Luc; Dransart, Pascal; Dzbikowicz, Zdzislaw; Dufour, Jean-Luc; Holzleitner, Ludwig; Huszti, Joseph; Looman, Marc; Marin Ferrer, Montserrat; Lambert, Thierry; Peerani, Paolo; Rackham, Jamie; Swinhoe, Martyn; Tobin, Steve; Weber, Anne-Laure; Wilson, Mark

    2009-01-01

    Neutron coincidence counting is a widely adopted nondestructive assay (NDA) technique used in nuclear safeguards to measure the mass of nuclear material in samples. Nowadays, most neutron-counting systems are based on the original-shift-register technology, like the (ordinary or multiplicity) Shift-Register Analyser. The analogue signal from the He-3 tubes is processed by an amplifier/single channel analyser (SCA) producing a train of TTL pulses that are fed into an electronic unit that performs the time- correlation analysis. Following the suggestion of the main inspection authorities (IAEA, Euratom and the French Ministry of Industry), several research laboratories have started to study and develop prototypes of neutron-counting systems with PC-based processing. Collaboration in this field among JRC, IRSN and LANL has been established within the framework of the ESARDA-NDA working group. Joint testing campaigns have been performed in the JRC PERLA laboratory, using different equipment provided by the three partners. One area of development is the use of high-speed PCs and pulse acquisition electronics that provide a time stamp (LIST-Mode Acquisition) for every digital pulse. The time stamp data can be processed directly during acquisition or saved on a hard disk. The latter method has the advantage that measurement data can be analysed with different values for parameters like predelay and gate width, without repeating the acquisition. Other useful diagnostic information, such as die-away time and dead time, can also be extracted from this stored data. A second area is the development of 'virtual instruments.' These devices, in which the pulse-processing system can be embedded in the neutron counter itself and sends counting data to a PC, can give increased data-acquisition speeds. Either or both of these developments could give rise to the next generation of instrumentation for improved practical neutron-correlation measurements. The paper will describe the

  8. arXiv Signal coupling to embedded pitch adapters in silicon sensors

    CERN Document Server

    Artuso, M.; Bezshyiko, I.; Blusk, S.; Bruendler, R.; Bugiel, S.; Dasgupta, R.; Dendek, A.; Dey, B.; Ely, S.; Lionetto, F.; Petruzzo, M.; Polyakov, I.; Rudolph, M.; Schindler, H.; Steinkamp, O.; Stone, S.

    2018-01-01

    We have examined the effects of embedded pitch adapters on signal formation in n-substrate silicon microstrip sensors with data from beam tests and simulation. According to simulation, the presence of the pitch adapter metal layer changes the electric field inside the sensor, resulting in slowed signal formation on the nearby strips and a pick-up effect on the pitch adapter. This can result in an inefficiency to detect particles passing through the pitch adapter region. All these effects have been observed in the beam test data.

  9. Signal Processing Model for Radiation Transport

    Energy Technology Data Exchange (ETDEWEB)

    Chambers, D H

    2008-07-28

    This note describes the design of a simplified gamma ray transport model for use in designing a sequential Bayesian signal processor for low-count detection and classification. It uses a simple one-dimensional geometry to describe the emitting source, shield effects, and detector (see Fig. 1). At present, only Compton scattering and photoelectric absorption are implemented for the shield and the detector. Other effects may be incorporated in the future by revising the expressions for the probabilities of escape and absorption. Pair production would require a redesign of the simulator to incorporate photon correlation effects. The initial design incorporates the physical effects that were present in the previous event mode sequence simulator created by Alan Meyer. The main difference is that this simulator transports the rate distributions instead of single photons. Event mode sequences and other time-dependent photon flux sequences are assumed to be marked Poisson processes that are entirely described by their rate distributions. Individual realizations can be constructed from the rate distribution using a random Poisson point sequence generator.

  10. Closed orbit feedback with digital signal processing

    International Nuclear Information System (INIS)

    Chung, Y.; Kirchman, J.; Lenkszus, F.

    1994-01-01

    The closed orbit feedback experiment conducted on the SPEAR using the singular value decomposition (SVD) technique and digital signal processing (DSP) is presented. The beam response matrix, defined as beam motion at beam position monitor (BPM) locations per unit kick by corrector magnets, was measured and then analyzed using SVD. Ten BPMs, sixteen correctors, and the eight largest SVD eigenvalues were used for closed orbit correction. The maximum sampling frequency for the closed loop feedback was measured at 37 Hz. Using the proportional and integral (PI) control algorithm with the gains Kp = 3 and K I = 0.05 and the open-loop bandwidth corresponding to 1% of the sampling frequency, a correction bandwidth (-3 dB) of approximately 0.8 Hz was achieved. Time domain measurements showed that the response time of the closed loop feedback system for 1/e decay was approximately 0.25 second. This result implies ∼ 100 Hz correction bandwidth for the planned beam position feedback system for the Advanced Photon Source storage ring with the projected 4-kHz sampling frequency

  11. Selecting Informative Features of the Helicopter and Aircraft Acoustic Signals in the Adaptive Autonomous Information Systems for Recognition

    Directory of Open Access Journals (Sweden)

    V. K. Hohlov

    2017-01-01

    Full Text Available The article forms the rationale for selecting the informative features of the helicopter and aircraft acoustic signals to solve a problem of their recognition and shows that the most informative ones are the counts of extrema in the energy spectra of the input signals, which represent non-centered random variables. An apparatus of the multiple initial regression coefficients was selected as a mathematical tool of research. The application of digital re-circulators with positive and negative feedbacks, which have the comb-like frequency characteristics, solves the problem of selecting informative features. A distinguishing feature of such an approach is easy agility of the comb frequency characteristics just through the agility of a delay value of digital signal in the feedback circuit. Adding an adaptation block to the selection block of the informative features enables us to ensure the invariance of used informative feature and counts of local extrema of the spectral power density to the airspeed of a helicopter. The paper gives reasons for the principle of adaptation and the structure of the adaptation block. To form the discriminator characteristics are used the cross-correlation statistical characteristics of the quadrature components of acoustic signal realizations, obtained by Hilbert transform. The paper proposes to provide signal recognition using a regression algorithm that allows handling the non-centered informative features and using a priori information about coefficients of initial regression of signal and noise.The simulation in Matlab Simulink has shown that selected informative features of signals in regressive processing of signal realizations of 0.5 s duration have good separability, and based on a set of 100 acoustic signal realizations in each class in full-scale conditions, has proved ensuring a correct recognition probability of 0.975, at least. The considered principles of informative features selection and adaptation can

  12. A systematic process for adaptive concept exploration

    Science.gov (United States)

    Nixon, Janel Nicole

    several common challenges to the creation of quantitative modeling and simulation environments. Namely, a greater number of alternative solutions imply a greater number of design variables as well as larger ranges on those variables. This translates to a high-dimension combinatorial problem. As the size and dimensionality of the solution space gets larger, the number of physically impossible solutions within that space greatly increases. Thus, the ratio of feasible design space to infeasible space decreases, making it much harder to not only obtain a good quantitative sample of the space, but to also make sense of that data. This is especially the case in the early stages of design, where it is not practical to dedicate a great deal of resources to performing thorough, high-fidelity analyses on all the potential solutions. To make quantitative analyses feasible in these early stages of design, a method is needed that allows for a relatively sparse set of information to be collected quickly and efficiently, and yet, that information needs to be meaningful enough with which to base a decision. The method developed to address this need uses a Systematic Process for Adaptive Concept Exploration (SPACE). In the SPACE method, design space exploration occurs in a sequential fashion; as data is acquired, the sampling scheme adapts to the specific problem at hand. Previously gathered data is used to make inferences about the nature of the problem so that future samples can be taken from the more interesting portions of the design space. Furthermore, the SPACE method identifies those analyses that have significant impacts on the relationships being modeled, so that effort can be focused on acquiring only the most pertinent information. The SPACE method uses a four-part sampling scheme to efficiently uncover the parametric relationships between the design variables and responses. Step 1 aims to identify the location of infeasible space within the region of interest using an initial

  13. An introduction to audio content analysis applications in signal processing and music informatics

    CERN Document Server

    Lerch, Alexander

    2012-01-01

    "With the proliferation of digital audio distribution over digital media, audio content analysis is fast becoming a requirement for designers of intelligent signal-adaptive audio processing systems. Written by a well-known expert in the field, this book provides quick access to different analysis algorithms and allows comparison between different approaches to the same task, making it useful for newcomers to audio signal processing and industry experts alike. A review of relevant fundamentals in audio signal processing, psychoacoustics, and music theory, as well as downloadable MATLAB files are also included"--

  14. An adaptive management process for forest soil conservation.

    Science.gov (United States)

    Michael P. Curran; Douglas G. Maynard; Ronald L. Heninger; Thomas A. Terry; Steven W. Howes; Douglas M. Stone; Thomas Niemann; Richard E. Miller; Robert F. Powers

    2005-01-01

    Soil disturbance guidelines should be based on comparable disturbance categories adapted to specific local soil conditions, validated by monitoring and research. Guidelines, standards, and practices should be continually improved based on an adaptive management process, which is presented in this paper. Core components of this process include: reliable monitoring...

  15. Molecular Signals and Skeletal Muscle Adaptation to Exercise

    Directory of Open Access Journals (Sweden)

    Mark Wilson

    2013-09-01

    Full Text Available The phenotypic plasticity of skeletal muscle affords a considerable degree of adaptability not seen in other bodily tissues. The mechanical properties of skeletal muscle are highly dependent on loading conditions. The extent of skeletal muscle plasticity is distinctly highlighted by a loss of muscle mass, or atrophy, after a period of reduced weight-bearing activity, for example during periods of extended bed rest, space flight and in spinal cord injury. On the other hand, increased mechanical loading, or resistance training, induces muscle growth, or hypertrophy. Endurance exercise performance is also dependent on the adaptability of skeletal muscle, especially muscles that contribute to posture, locomotion and the mechanics of breathing.  However, the molecular pathways governing skeletal muscle adaptations are yet to be satisfactorily delineated and require further investigation. Researchers in the areas of exercise physiology, physiotherapy and sports medicine are endeavoring to translate experimental knowledge into effective, innovative treatments and regimens in order to improve physical performance and health in both elite athletes and the general community. The efficacy of the translation of molecular biological paradigms in experimental exercise physiology has long been underappreciated. Indeed, molecular biology tools can now be used to answer questions regarding skeletal muscle adaptation in response to exercise and provide new frameworks to improve physical performance. Furthermore, transgenic animal models, knockout animal models and in vivo studies provide tools to test questions concerned with how exercise initiates adaptive changes in gene expression. In light of these perceived deficiencies, an attempt is made here to elucidate the molecular mechanisms of skeletal muscle adaptation to exercise. An examination will be made of the functional capacity of skeletal muscle to respond to a variety of exercise conditions, namely

  16. Molecular Signals and Skeletal Muscle Adaptation to Exercise

    Directory of Open Access Journals (Sweden)

    Mark Wilson

    2013-08-01

    Full Text Available The phenotypic plasticity of skeletal muscle affords a considerable degree of adaptability not seen in other bodily tissues. The mechanical properties of skeletal muscle are highly dependent on loading conditions. The extent of skeletal muscle plasticity is distinctly highlighted by a loss of muscle mass, or atrophy, after a period of reduced weight-bearing activity, for example during periods of extended bed rest, space flight and in spinal cord injury. On the other hand, increased mechanical loading, or resistance training, induces muscle growth, or hypertrophy. Endurance exercise performance is also dependent on the adaptability of skeletal muscle, especially muscles that contribute to posture, locomotion and the mechanics of breathing. However, the molecular pathways governing skeletal muscle adaptations are yet to be satisfactorily delineated and require further investigation. Researchers in the areas of exercise physiology, physiotherapy and sports medicine are endeavoring to translate experimental knowledge into effective, innovative treatments and regimens in order to improve physical performance and health in both elite athletes and the general community. The efficacy of the translation of molecular biological paradigms in experimental exercise physiology has long been underappreciated. Indeed, molecular biology tools can now be used to answer questions regarding skeletal muscle adaptation in response to exercise and provide new frameworks to improve physical performance. Furthermore, transgenic animal models, knockout animal models and in vivo studies provide tools to test questions concerned with how exercise initiates adaptive changes in gene expression. In light of these perceived deficiencies, an attempt is made here to elucidate the molecular mechanisms of skeletal muscle adaptation to exercise. An examination will be made of the functional capacity of skeletal muscle to respond to a variety of exercise conditions, namely

  17. Silicon Photonics for Signal Processing of Tbit/s Serial Data Signals

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Ji, Hua; Galili, Michael

    2012-01-01

    In this paper, we describe our recent work on signal processing of terabit per second optical serial data signals using pure silicon waveguides. We employ nonlinear optical signal processing in nanoengineered silicon waveguides to perform demultiplexing and optical waveform sampling of 1.28-Tbit/...

  18. Microwave signal processing with photorefractive dynamic holography

    Science.gov (United States)

    Fotheringham, Edeline B.

    Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that

  19. Signal processing for liquid ionization calorimeters

    International Nuclear Information System (INIS)

    Cleland, W.E.; Stern, E.G.

    1992-01-01

    We present the results of a study of the effects of thermal and pileup noise in liquid ionization calorimeters operating in a high luminosity calorimeters operating in a high luminosity environment. The method of optimal filtering of multiply-sampled signals which may be used to improve the timing and amplitude resolution of calorimeter signals is described, and its implications for signal shaping functions are examined. The dependence of the time and amplitude resolution on the relative strength of the pileup and thermal noise, which varies with such parameters as luminosity, rapidity and calorimeter cell size, is examined

  20. Knee joint vibroarthrographic signal processing and analysis

    CERN Document Server

    Wu, Yunfeng

    2015-01-01

    This book presents the cutting-edge technologies of knee joint vibroarthrographic signal analysis for the screening and detection of knee joint injuries. It describes a number of effective computer-aided methods for analysis of the nonlinear and nonstationary biomedical signals generated by complex physiological mechanics. This book also introduces several popular machine learning and pattern recognition algorithms for biomedical signal classifications. The book is well-suited for all researchers looking to better understand knee joint biomechanics and the advanced technology for vibration arthrometry. Dr. Yunfeng Wu is an Associate Professor at the School of Information Science and Technology, Xiamen University, Xiamen, Fujian, China.

  1. Adaptive Process Management with ADEPT2

    NARCIS (Netherlands)

    Reichert, M.U.; Rinderle, S.B.; Kreher, U; Dadam, P.

    2005-01-01

    This demo paper describes core functions of the ADEPT2 process management system. In the ADEPT project we have been working on the design and implementation of a next generation process management software. Based on a conceptual framework for dynamic process changes, on novel process support

  2. Electrical measurement, signal processing, and displays

    CERN Document Server

    Webster, John G

    2003-01-01

    ELECTROMAGNETIC VARIABLES MEASUREMENTVoltage MeasurementCurrent Measurement Power Measurement Power Factor Measurement Phase Measurement Energy Measurement Electrical Conductivity and Resistivity Charge Measurement Capacitance and Capacitance Measurements Permittivity Measurement Electric Field Strength Magnetic Field Measurement Permeability and Hysteresis MeasurementInductance Measurement Immittance MeasurementQ Factor Measurement Distortion Measurement Noise Measurement.Microwave Measurement SIGNAL PROCESSINGAmplifiers and Signal ConditionersModulation Filters Spectrum Analysis and Correlat

  3. Sonar waveforms for reverberation rejection, Part IV: Adaptive processing.

    NARCIS (Netherlands)

    IJsselmuide, S.P. van; Deruaz, L.; Been, R.; Doisy, Y.; Beerens, S.P.

    2002-01-01

    For littoral ASW, reverberation is a big problem and rejection of reverberation is of utmost importance. The influence of the transmitted signal on the signal to reverberation ratio has been presented in three preceding papers. In this paper, the influence of improved signal processing on the

  4. An Adaptive Traffic Signal Control in a Connected Vehicle Environment: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Peng Jing

    2017-08-01

    Full Text Available In the last few years, traffic congestion has become a growing concern due to increasing vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic signal control systems cannot adjust the timing pattern depending on road traffic demand. This results in excessive delays for road users. Adaptive traffic signal control in a connected vehicle environment has shown a powerful ability to effectively alleviate urban traffic congestions to achieve desirable objectives (e.g., delay minimization. Connected vehicle technology, as an emerging technology, is a mobile data platform that enables the real-time data exchange among vehicles and between vehicles and infrastructure. Although several reviews about traffic signal control or connected vehicles have been written, a systemic review of adaptive traffic signal control in a connected vehicle environment has not been made. Twenty-six eligible studies searched from six databases constitute the review. A quality evaluation was established based on previous research instruments and applied to the current review. The purpose of this paper is to critically review the existing methods of adaptive traffic signal control in a connected vehicle environment and to compare the advantages or disadvantages of those methods. Further, a systematic framework on connected vehicle based adaptive traffic signal control is summarized to support the future research. Future research is needed to develop more efficient and generic adaptive traffic signal control methods in a connected vehicle environment.

  5. Adaptation of signal transduction and muscle proteome in trained horses

    NARCIS (Netherlands)

    Ginneken, Mireille Maria Elisabeth van

    2006-01-01

    In the present thesis the localization and activation of signaling proteins, known from human studies, in equine muscle were investigated under conditions of rest, after an acute bout of exercise and before and after a period of (intensified) training. Proteins of interest (protein kinase C (PKC),

  6. Adaptive constructive processes and the future of memory

    OpenAIRE

    Schacter, Daniel L.

    2012-01-01

    Memory serves critical functions in everyday life, but is also prone to error. This article examines adaptive constructive processes, which play a functional role in memory and cognition but can also produce distortions, errors, or illusions. The article describes several types of memory errors that are produced by adaptive constructive processes, and focuses in particular on the process of imagining or simulating events that might occur in one’s personal future. Simulating future events reli...

  7. Adaptive Algorithms for Automated Processing of Document Images

    Science.gov (United States)

    2011-01-01

    ABSTRACT Title of dissertation: ADAPTIVE ALGORITHMS FOR AUTOMATED PROCESSING OF DOCUMENT IMAGES Mudit Agrawal, Doctor of Philosophy, 2011...2011 4. TITLE AND SUBTITLE Adaptive Algorithms for Automated Processing of Document Images 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...ALGORITHMS FOR AUTOMATED PROCESSING OF DOCUMENT IMAGES by Mudit Agrawal Dissertation submitted to the Faculty of the Graduate School of the University

  8. Quantum Dot Devices for Optical Signal Processing

    DEFF Research Database (Denmark)

    Chen, Yaohui

    and the continuum. Additional to the conventional time-domain modeling scheme, a small-signal perturbation analysis has been used to assist the investigation of harmonic modulation properties. The static properties of quantum dot devices, for example high saturation power, have been quantitatively analyzed....... Additional to the static linear amplication properties, we focus on exploring the gain dynamics on the time scale ranging from sub-picosecond to nanosecond. In terms of optical signals that have been investigated, one is the simple sinusoidally modulated optical carrier with a typical modulation frequency....... We also investigate the gain dynamics in the presence of pulsed signals, in particular the steady gain response to a periodic pulse trains with various time periods. Additional to the analysis of high speed patterning free amplication up to 150-200 Gb/s in quantum dot semiconductor optical ampliers...

  9. Proceedings of IEEE Machine Learning for Signal Processing Workshop XV

    DEFF Research Database (Denmark)

    Larsen, Jan

    These proceedings contains refereed papers presented at the Fifteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP’2005), held in Mystic, Connecticut, USA, September 28-30, 2005. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP) organized...... by the NNSP Technical Committee of the IEEE Signal Processing Society. The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized...... by the Machine Learning for Signal Processing Technical Committee with sponsorship of the IEEE Signal Processing Society. Following the practice started two years ago, the bound volume of the proceedings is going to be published by IEEE following the Workshop, and we are pleased to offer to conference attendees...

  10. Low Rate Transmission of Video Signals Using Adaptive Delta Modulation.

    Science.gov (United States)

    1983-08-15

    903-80-C-0476 / . PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT, TASK AREA & WORK UNIT NUMBERS Research Foundation of CUNY on...transmitted phase, for the demodulation of the signal. AM is presently being used to transmit multilevel * symbols by vestigial or single sideband...34: Vestigial Sideband -- Duobinary 3600 4-Phase + AM 4800" 4-Phase + AM * Vestigial Sideband 8-PSK 7200 Phase and Amplitude Modulation 9600 Phase anl

  11. Construction of large signaling pathways using an adaptive perturbation approach with phosphoproteomic data.

    Science.gov (United States)

    Melas, Ioannis N; Mitsos, Alexander; Messinis, Dimitris E; Weiss, Thomas S; Rodriguez, Julio-Saez; Alexopoulos, Leonidas G

    2012-04-01

    Construction of large and cell-specific signaling pathways is essential to understand information processing under normal and pathological conditions. On this front, gene-based approaches offer the advantage of large pathway exploration whereas phosphoproteomic approaches offer a more reliable view of pathway activities but are applicable to small pathway sizes. In this paper, we demonstrate an experimentally adaptive approach to construct large signaling pathways from phosphoproteomic data within a 3-day time frame. Our approach--taking advantage of the fast turnaround time of the xMAP technology--is carried out in four steps: (i) screen optimal pathway inducers, (ii) select the responsive ones, (iii) combine them in a combinatorial fashion to construct a phosphoproteomic dataset, and (iv) optimize a reduced generic pathway via an Integer Linear Programming formulation. As a case study, we uncover novel players and their corresponding pathways in primary human hepatocytes by interrogating the signal transduction downstream of 81 receptors of interest and constructing a detailed model for the responsive part of the network comprising 177 species (of which 14 are measured) and 365 interactions.

  12. Trends in Machine Learning for Signal Processing

    DEFF Research Database (Denmark)

    Adali, Tulay; Miller, David J.; Diamantaras, Konstantinos I.

    2011-01-01

    By putting the accent on learning from the data and the environment, the Machine Learning for SP (MLSP) Technical Committee (TC) provides the essential bridge between the machine learning and SP communities. While the emphasis in MLSP is on learning and data-driven approaches, SP defines the main...... applications of interest, and thus the constraints and requirements on solutions, which include computational efficiency, online adaptation, and learning with limited supervision/reference data....

  13. Poisson pre-processing of nonstationary photonic signals: Signals with equality between mean and variance.

    Science.gov (United States)

    Poplová, Michaela; Sovka, Pavel; Cifra, Michal

    2017-01-01

    Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

  14. Adaptive Constructive Processes and the Future of Memory

    Science.gov (United States)

    Schacter, Daniel L.

    2012-01-01

    Memory serves critical functions in everyday life but is also prone to error. This article examines adaptive constructive processes, which play a functional role in memory and cognition but can also produce distortions, errors, and illusions. The article describes several types of memory errors that are produced by adaptive constructive processes…

  15. Adaptive Memory: Is Survival Processing Special?

    Science.gov (United States)

    Nairne, James S.; Pandeirada, Josefa N. S.

    2008-01-01

    Do the operating characteristics of memory continue to bear the imprints of ancestral selection pressures? Previous work in our laboratory has shown that human memory may be specially tuned to retain information processed in terms of its survival relevance. A few seconds of survival processing in an incidental learning context can produce recall…

  16. Adaptive process triage system cannot identify patients with gastrointestinal perforation

    DEFF Research Database (Denmark)

    Bohm, Aske Mathias; Tolstrup, Mai-Britt; Gögenur, Ismail

    2017-01-01

    INTRODUCTION: Adaptive process triage (ADAPT) is a triage tool developed to assess the severity and address the priority of emergency patients. In 2009-2011, ADAPT was the most frequently used triage system in Denmark. Until now, no Danish triage system has been evaluated based on a selective group...... triaged as green or yellow had a GIP that was not identified by the triage system. CONCLUSION: ADAPT is incapable of identifying one of the most critically ill patient groups in need of emergency abdominal surgery. FUNDING: none. TRIAL REGISTRATION: HEH-2013-034 I-Suite: 02336....

  17. Signal Conditioning An Introduction to Continuous Wave Communication and Signal Processing

    CERN Document Server

    Das, Apurba

    2012-01-01

    "Signal Conditioning” is a comprehensive introduction to electronic signal processing. The book presents the mathematical basics including the implications of various transformed domain representations in signal synthesis and analysis in an understandable and lucid fashion and illustrates the theory through many applications and examples from communication systems. The ease to learn is supported by well-chosen exercises which give readers the flavor of the subject. Supplementary electronic materials available on http://extras.springer.com including MATLAB codes illuminating applications in the domain of one dimensional electrical signal processing, image processing and speech processing. The book is an introduction for students with a basic understanding in engineering or natural sciences.

  18. All-optical signal processing data communication and storage applications

    CERN Document Server

    Eggleton, Benjamin

    2015-01-01

    This book provides a comprehensive review of the state-of-the art of optical signal processing technologies and devices. It presents breakthrough solutions for enabling a pervasive use of optics in data communication and signal storage applications. It presents presents optical signal processing as solution to overcome the capacity crunch in communication networks. The book content ranges from the development of innovative materials and devices, such as graphene and slow light structures, to the use of nonlinear optics for secure quantum information processing and overcoming the classical Shannon limit on channel capacity and microwave signal processing. Although it holds the promise for a substantial speed improvement, today’s communication infrastructure optics remains largely confined to the signal transport layer, as it lags behind electronics as far as signal processing is concerned. This situation will change in the near future as the tremendous growth of data traffic requires energy efficient and ful...

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

    Science.gov (United States)

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

    2014-05-09

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

  20. Development of an Ontology-Directed Signal Processing Toolbox

    Energy Technology Data Exchange (ETDEWEB)

    Stephen W. Lang

    2011-05-27

    This project was focused on the development of tools for the automatic configuration of signal processing systems. The goal is to develop tools that will be useful in a variety of Government and commercial areas and useable by people who are not signal processing experts. In order to get the most benefit from signal processing techniques, deep technical expertise is often required in order to select appropriate algorithms, combine them into a processing chain, and tune algorithm parameters for best performance on a specific problem. Therefore a significant benefit would result from the assembly of a toolbox of processing algorithms that has been selected for their effectiveness in a group of related problem areas, along with the means to allow people who are not signal processing experts to reliably select, combine, and tune these algorithms to solve specific problems. Defining a vocabulary for problem domain experts that is sufficiently expressive to drive the configuration of signal processing functions will allow the expertise of signal processing experts to be captured in rules for automated configuration. In order to test the feasibility of this approach, we addressed a lightning classification problem, which was proposed by DOE as a surrogate for problems encountered in nuclear nonproliferation data processing. We coded a toolbox of low-level signal processing algorithms for extracting features of RF waveforms, and demonstrated a prototype tool for screening data. We showed examples of using the tool for expediting the generation of ground-truth metadata, for training a signal recognizer, and for searching for signals with particular characteristics. The public benefits of this approach, if successful, will accrue to Government and commercial activities that face the same general problem - the development of sensor systems for complex environments. It will enable problem domain experts (e.g. analysts) to construct signal and image processing chains without

  1. Robust digital processing of speech signals

    CERN Document Server

    Kovacevic, Branko; Veinović, Mladen; Marković, Milan

    2017-01-01

    This book focuses on speech signal phenomena, presenting a robustification of the usual speech generation models with regard to the presumed types of excitation signals, which is equivalent to the introduction of a class of nonlinear models and the corresponding criterion functions for parameter estimation. Compared to the general class of nonlinear models, such as various neural networks, these models possess good properties of controlled complexity, the option of working in “online” mode, as well as a low information volume for efficient speech encoding and transmission. Providing comprehensive insights, the book is based on the authors’ research, which has already been published, supplemented by additional texts discussing general considerations of speech modeling, linear predictive analysis and robust parameter estimation.

  2. SIGNAL PROCESSING UTILIZING RADIO FREQUENCY PHOTONICS

    Science.gov (United States)

    2017-09-07

    has many advantages over these electronic counterparts. The ability to cover larger bandwidths, immunity to electromagnetic interference, low weight...is unlimited. 4.1 RF Photonics Sampling with Electronic ADCs Figure 7 shows a photonic sampling scheme. The amplitude of the pulses from a laser are...modified by the RF signal to be sampled. The pulses are time demultiplexed and passed to multiple ADCs. The hybrid configuration combines parallel

  3. Signal processing for distributed readout using TESs

    International Nuclear Information System (INIS)

    Smith, Stephen J.; Whitford, Chris H.; Fraser, George W.

    2006-01-01

    We describe optimal filtering algorithms for determining energy and position resolution in position-sensitive Transition Edge Sensor (TES) Distributed Read-Out Imaging Devices (DROIDs). Improved algorithms, developed using a small-signal finite-element model, are based on least-squares minimisation of the total noise power in the correlated dual TES DROID. Through numerical simulations we show that significant improvements in energy and position resolution are theoretically possible over existing methods

  4. Adaptive multiscale processing for contrast enhancement

    Science.gov (United States)

    Laine, Andrew F.; Song, Shuwu; Fan, Jian; Huda, Walter; Honeyman, Janice C.; Steinbach, Barbara G.

    1993-07-01

    This paper introduces a novel approach for accomplishing mammographic feature analysis through overcomplete multiresolution representations. We show that efficient representations may be identified from digital mammograms within a continuum of scale space and used to enhance features of importance to mammography. Choosing analyzing functions that are well localized in both space and frequency, results in a powerful methodology for image analysis. We describe methods of contrast enhancement based on two overcomplete (redundant) multiscale representations: (1) Dyadic wavelet transform (2) (phi) -transform. Mammograms are reconstructed from transform coefficients modified at one or more levels by non-linear, logarithmic and constant scale-space weight functions. Multiscale edges identified within distinct levels of transform space provide a local support for enhancement throughout each decomposition. We demonstrate that features extracted from wavelet spaces can provide an adaptive mechanism for accomplishing local contrast enhancement. We suggest that multiscale detection and local enhancement of singularities may be effectively employed for the visualization of breast pathology without excessive noise amplification.

  5. Collective Mindfulness in Post-implementation IS Adaptation Processes

    DEFF Research Database (Denmark)

    Aanestad, Margun; Jensen, Tina Blegind

    2016-01-01

    identify the way in which the organizational capability we call "collective mindfulness" was achieved. Being aware of how to practically achieve collective mindfulness, managers may be able to better facilitate mindful handling of post-implementation IS adaptation processes....

  6. STAR Performance with SPEAR (Signal Processing Electronic Attack RFIC)

    Science.gov (United States)

    2017-03-01

    re about 6 x ains duplicate e implemente ifferences. A d signal from t first mixer sta ange. The LN etween noise e of a strong a on-chip balu icro...amplifiers filter is embed signal before f lumped com onics in the pr ly 1 x 1 (mm)2 adaptive p signal (in ultaneous h. anufacture whole off... ted circuit. s part of a in Global e die will el receiver ter; (iv) an -to-parallel 7 (mm)2 the same d by the low noise he antenna ge

  7. Behavioral training promotes multiple adaptive processes following acute hearing loss.

    Science.gov (United States)

    Keating, Peter; Rosenior-Patten, Onayomi; Dahmen, Johannes C; Bell, Olivia; King, Andrew J

    2016-03-23

    The brain possesses a remarkable capacity to compensate for changes in inputs resulting from a range of sensory impairments. Developmental studies of sound localization have shown that adaptation to asymmetric hearing loss can be achieved either by reinterpreting altered spatial cues or by relying more on those cues that remain intact. Adaptation to monaural deprivation in adulthood is also possible, but appears to lack such flexibility. Here we show, however, that appropriate behavioral training enables monaurally-deprived adult humans to exploit both of these adaptive processes. Moreover, cortical recordings in ferrets reared with asymmetric hearing loss suggest that these forms of plasticity have distinct neural substrates. An ability to adapt to asymmetric hearing loss using multiple adaptive processes is therefore shared by different species and may persist throughout the lifespan. This highlights the fundamental flexibility of neural systems, and may also point toward novel therapeutic strategies for treating sensory disorders.

  8. Application of wavelet transform in seismic signal processing

    International Nuclear Information System (INIS)

    Ghasemi, M. R.; Mohammadzadeh, A.; Salajeghe, E.

    2005-01-01

    Wavelet transform is a new tool for signal analysis which can perform a simultaneous signal time and frequency representations. Under Multi Resolution Analysis, one can quickly determine details for signals and their properties using Fast Wavelet Transform algorithms. In this paper, for a better physical understanding of a signal and its basic algorithms, Multi Resolution Analysis together with wavelet transforms in a form of Digital Signal Processing will be discussed. For a Seismic Signal Processing, sets of Orthonormal Daubechies Wavelets are suggested. when dealing with the application of wavelets in SSP, one may discuss about denoising from the signal and data compression existed in the signal, which is important in seismic signal data processing. Using this techniques, EL-Centro and Nagan signals were remodeled with a 25% of total points, resulted in a satisfactory results with an acceptable error drift. Thus a total of 1559 and 2500 points for EL-centro and Nagan seismic curves each, were reduced to 389 and 625 points respectively, with a very reasonable error drift, details of which are recorded in the paper. Finally, the future progress in signal processing, based on wavelet theory will be appointed

  9. Artificial intelligence applied to process signal analysis

    Science.gov (United States)

    Corsberg, Dan

    1988-01-01

    Many space station processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect of the human/machine interface is the analysis and display of process information. Human operators can be overwhelmed by large clusters of alarms that inhibit their ability to diagnose and respond to a disturbance. Using artificial intelligence techniques and a knowledge base approach to this problem, the power of the computer can be used to filter and analyze plant sensor data. This will provide operators with a better description of the process state. Once a process state is recognized, automatic action could be initiated and proper system response monitored.

  10. Streamlining digital signal processing a tricks of the trade guidebook

    CERN Document Server

    2012-01-01

    Streamlining Digital Signal Processing, Second Edition, presents recent advances in DSP that simplify or increase the computational speed of common signal processing operations and provides practical, real-world tips and tricks not covered in conventional DSP textbooks. It offers new implementations of digital filter design, spectrum analysis, signal generation, high-speed function approximation, and various other DSP functions. It provides:Great tips, tricks of the trade, secrets, practical shortcuts, and clever engineering solutions from seasoned signal processing professionalsAn assortment.

  11. Sensory Processing Subtypes in Autism: Association with Adaptive Behavior

    Science.gov (United States)

    Lane, Alison E.; Young, Robyn L.; Baker, Amy E. Z.; Angley, Manya T.

    2010-01-01

    Children with autism are frequently observed to experience difficulties in sensory processing. This study examined specific patterns of sensory processing in 54 children with autistic disorder and their association with adaptive behavior. Model-based cluster analysis revealed three distinct sensory processing subtypes in autism. These subtypes…

  12. Functional Dual Adaptive Control with Recursive Gaussian Process Model

    International Nuclear Information System (INIS)

    Prüher, Jakub; Král, Ladislav

    2015-01-01

    The paper deals with dual adaptive control problem, where the functional uncertainties in the system description are modelled by a non-parametric Gaussian process regression model. Current approaches to adaptive control based on Gaussian process models are severely limited in their practical applicability, because the model is re-adjusted using all the currently available data, which keeps growing with every time step. We propose the use of recursive Gaussian process regression algorithm for significant reduction in computational requirements, thus bringing the Gaussian process-based adaptive controllers closer to their practical applicability. In this work, we design a bi-criterial dual controller based on recursive Gaussian process model for discrete-time stochastic dynamic systems given in an affine-in-control form. Using Monte Carlo simulations, we show that the proposed controller achieves comparable performance with the full Gaussian process-based controller in terms of control quality while keeping the computational demands bounded. (paper)

  13. Innovative signal processing for Johnson Noise thermometry

    Energy Technology Data Exchange (ETDEWEB)

    Ezell, N. Dianne Bull [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Britton, Jr, Charles L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Roberts, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2016-07-01

    This report summarizes the newly developed algorithm that subtracted the Electromagnetic Interference (EMI). The EMI performance is very important to this measurement because any interference in the form on pickup from external signal sources from such as fluorescent lighting ballasts, motors, etc. can skew the measurement. Two methods of removing EMI were developed and tested at various locations. This report also summarizes the testing performed at different facilities outside Oak Ridge National Laboratory using both EMI removal techniques. The first EMI removal technique reviewed in previous milestone reports and therefore this report will detail the second method.

  14. Signal processing for underclad crack sizing

    International Nuclear Information System (INIS)

    Shankar, R.; Lane, S.S.; Paradiso, T.J.; Quinn, J.R.

    1985-01-01

    The techniques developed in this work provide a means of sizing underclad cracks and quality control methods for assessing the accuracy of the data. Data were collected with a minicomputer (LSI 11-02), a transient recorder (Biomaton 8100) and anti-aliasing filter. Three techniques were developed: the calibration curve, phase velocity and epicentral. The phase reversal characteristic in the data is a strong indication of the nature of the signal source. That is, cracks are clearly seperable from two isolated inclusions on the basis of observed phase reversal. These methods have been implemented on a computer and appear to provide an accurate rapid method to discriminate and size underclad cracks

  15. Subspace Signal Processing in Structured Noise

    Science.gov (United States)

    1990-12-01

    1.7 Motivation for the Model ....... ........................... 8 1.8 E x am p les...S). We do not require that H be orthogonal to S. * 1.7 Motivation for the Model The linear model is quite versatile in terms of the types of signals...cross terms zero, we choose . = (SHs)- mS~u’ (3.69) This implies that = Ps4 , (3.70) and S t s (3.71) : = Ps . RPs -. The last step is to maximize

  16. Quaternion Fourier transforms for signal and image processing

    CERN Document Server

    Ell, Todd A; Sangwine, Stephen J

    2014-01-01

    Based on updates to signal and image processing technology made in the last two decades, this text examines the most recent research results pertaining to Quaternion Fourier Transforms. QFT is a central component of processing color images and complex valued signals. The book's attention to mathematical concepts, imaging applications, and Matlab compatibility render it an irreplaceable resource for students, scientists, researchers, and engineers.

  17. All-optical signal processing for optical packet switching networks

    NARCIS (Netherlands)

    Liu, Y.; Hill, M.T.; Calabretta, N.; Tangdiongga, E.; Geldenhuys, R.; Zhang, S.; Li, Z.; Waardt, de H.; Khoe, G.D.; Dorren, H.J.S.; Iftekharuddin, K.M.; awwal, A.A.S.

    2005-01-01

    We discuss how all-optical signal processing might play a role in future all-optical packet switched networks. We introduce a concept of optical packet switches that employ entirely all-optical signal processing technology. The optical packet switch is made out of three functional blocks: the

  18. Motion-compensated processing of image signals

    NARCIS (Netherlands)

    2010-01-01

    In a motion-compensated processing of images, input images are down-scaled (scl) to obtain down-scaled images, the down-scaled images are subjected to motion- compensated processing (ME UPC) to obtain motion-compensated images, the motion- compensated images are up-scaled (sc2) to obtain up-scaled

  19. Proceedings of IEEE Machine Learning for Signal Processing Workshop XVI

    DEFF Research Database (Denmark)

    Larsen, Jan

    These proceedings contains refereed papers presented at the sixteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP'2006), held in Maynooth, Co. Kildare, Ireland, September 6-8, 2006. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP......). The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized by the Machine Learning for Signal Processing Technical Committee...... the same standard as the printed version and facilitates the reading and searching of the papers. The field of machine learning has matured considerably in both methodology and real-world application domains and has become particularly important for solution of problems in signal processing. As reflected...

  20. Bone Adaptation as an Evolutionary Process

    DEFF Research Database (Denmark)

    Bagge, Mette

    1998-01-01

    . The memory of past loadings is included in themodel to account for the delay in the bone response from the loadchanges. The remodeling rate equation is derived from the structuraloptimization task of maximizing the stiffness in each time step. Additional informationscan be extracted from the optimization...... process; the remodelingequilibrium parameter where no apposition or resorption takes place is defined asthe element optimality conditions and the optimal design is used as aninitial design for the onset ofthe remodeling simulation. Some examples of boneadaptation resulting from load changes is given....

  1. Membrane transporters mediating root signalling and adaptive responses to oxygen deprivation and soil flooding.

    Science.gov (United States)

    Shabala, Sergey; Shabala, Lana; Barcelo, Juan; Poschenrieder, Charlotte

    2014-10-01

    This review provides a comprehensive assessment of a previously unexplored topic: elucidating the role that plasma- and organelle-based membrane transporters play in plant-adaptive responses to flooding. We show that energy availability and metabolic shifts under hypoxia and anoxia are critical in regulating membrane-transport activity. We illustrate the high tissue and time dependence of this regulation, reveal the molecular identity of transporters involved and discuss the modes of their regulation. We show that both reduced oxygen availability and accumulation of transition metals in flooded roots result in a reduction in the cytosolic K(+) pool, ultimately determining the cell's fate and transition to programmed cell death (PCD). This process can be strongly affected by hypoxia-induced changes in the amino acid pool profile and, specifically, ϒ-amino butyric acid (GABA) accumulation. It is suggested that GABA plays an important regulatory role, allowing plants to proceed with H2 O2 signalling to activate a cascade of genes that mediate plant adaptation to flooding while at the same time, preventing the cell from entering a 'suicide program'. We conclude that progress in crop breeding for flooding tolerance can only be achieved by pyramiding the numerous physiological traits that confer efficient energy maintenance, cytosolic ion homeostasis, and reactive oxygen species (ROS) control and detoxification. © 2014 John Wiley & Sons Ltd.

  2. Nuclear pulse signal processing technique based on blind deconvolution method

    International Nuclear Information System (INIS)

    Hong Pengfei; Yang Lei; Fu Tingyan; Qi Zhong; Li Dongcang; Ren Zhongguo

    2012-01-01

    In this paper, we present a method for measurement and analysis of nuclear pulse signal, with which pile-up signal is removed, the signal baseline is restored, and the original signal is obtained. The data acquisition system includes FPGA, ADC and USB. The FPGA controls the high-speed ADC to sample the signal of nuclear radiation, and the USB makes the ADC work on the Slave FIFO mode to implement high-speed transmission status. Using the LabVIEW, it accomplishes online data processing of the blind deconvolution algorithm and data display. The simulation and experimental results demonstrate advantages of the method. (authors)

  3. All-optical signal processing of OTDM and OFDM signals based on time-domain Optical Fourier Transformation

    DEFF Research Database (Denmark)

    Clausen, Anders; Guan, Pengyu; Mulvad, Hans Christian Hansen

    2014-01-01

    All-optical time-domain Optical Fourier Transformation utilised for signal processing of ultra-high-speed OTDM signals and OFDM signals will be presented.......All-optical time-domain Optical Fourier Transformation utilised for signal processing of ultra-high-speed OTDM signals and OFDM signals will be presented....

  4. Live longer on MARS: a yeast paradigm of mitochondrial adaptive ROS signaling in aging

    Directory of Open Access Journals (Sweden)

    Gerald S. Shadel

    2014-04-01

    Full Text Available Adaptive responses to stress, including hormesis, have been implicated in longevity, but their mechanisms and out comes are not fully understood. Here, I briefly summarize a longevity mechanism elucidated in the budding yeast chronological lifespan model by which Mitochondrial Adaptive ROS Signaling (MARS promotes beneficial epigenetic and metabolic remodeling. The potential relevance of MARS to the human disease Ataxia-Telangiectasia and as a potential anti-aging target is discussed.

  5. Domain requirements for the Dock adapter protein in growth- cone signaling

    OpenAIRE

    Rao, Yong; Zipursky, S. Lawrence

    1998-01-01

    Tyrosine phosphorylation has been implicated in growth-cone guidance through genetic, biochemical, and pharmacological studies. Adapter proteins containing src homology 2 (SH2) domains and src homology 3 (SH3) domains provide a means of linking guidance signaling through phosphotyrosine to downstream effectors regulating growth-cone motility. The Drosophila adapter, Dreadlocks (Dock), the homolog of mammalian Nck containing three N-terminal SH3 domains and a single SH2 domain, is highly speci...

  6. Ultra-Fast Optical Signal Processing in Nonlinear Silicon Waveguides

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Galili, Michael; Pu, Minhao

    2011-01-01

    We describe recent demonstrations of exploiting highly nonlinear silicon nanowires for processing Tbit/s optical data signals. We perform demultiplexing and optical waveform sampling of 1.28 Tbit/s and wavelength conversion of 640 Gbit/s data signals.......We describe recent demonstrations of exploiting highly nonlinear silicon nanowires for processing Tbit/s optical data signals. We perform demultiplexing and optical waveform sampling of 1.28 Tbit/s and wavelength conversion of 640 Gbit/s data signals....

  7. Psychosocial intervention effects on adaptation, disease course and biobehavioral processes in cancer.

    Science.gov (United States)

    Antoni, Michael H

    2013-03-01

    A diagnosis of cancer and subsequent treatments place demands on psychological adaptation. Behavioral research suggests the importance of cognitive, behavioral, and social factors in facilitating adaptation during active treatment and throughout cancer survivorship, which forms the rationale for the use of many psychosocial interventions in cancer patients. This cancer experience may also affect physiological adaptation systems (e.g., neuroendocrine) in parallel with psychological adaptation changes (negative affect). Changes in adaptation may alter tumor growth-promoting processes (increased angiogenesis, migration and invasion, and inflammation) and tumor defense processes (decreased cellular immunity) relevant for cancer progression and the quality of life of cancer patients. Some evidence suggests that psychosocial intervention can improve psychological and physiological adaptation indicators in cancer patients. However, less is known about whether these interventions can influence tumor activity and tumor growth-promoting processes and whether changes in these processes could explain the psychosocial intervention effects on recurrence and survival documented to date. Documenting that psychosocial interventions can modulate molecular activities (e.g., transcriptional indicators of cell signaling) that govern tumor promoting and tumor defense processes on the one hand, and clinical disease course on the other is a key challenge for biobehavioral oncology research. This mini-review will summarize current knowledge on psychological and physiological adaptation processes affected throughout the stress of the cancer experience, and the effects of psychosocial interventions on psychological adaptation, cancer disease progression, and changes in stress-related biobehavioral processes that may mediate intervention effects on clinical cancer outcomes. Very recent intervention work in breast cancer will be used to illuminate emerging trends in molecular probes of

  8. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

    Science.gov (United States)

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

    2016-03-14

    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

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

    Science.gov (United States)

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

    2015-10-23

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

  10. Persymmetric Adaptive Detectors of Subspace Signals in Homogeneous and Partially Homogeneous Clutter

    Directory of Open Access Journals (Sweden)

    Ding Hao

    2015-08-01

    Full Text Available In the field of adaptive radar detection, an effective strategy to improve the detection performance is to exploit the structural information of the covariance matrix, especially in the case of insufficient reference cells. Thus, in this study, the problem of detecting multidimensional subspace signals is discussed by considering the persymmetric structure of the clutter covariance matrix, which implies that the covariance matrix is persymmetric about its cross diagonal. Persymmetric adaptive detectors are derived on the basis of the one-step principle as well as the two-step Generalized Likelihood Ratio Test (GLRT in homogeneous and partially homogeneous clutter. The proposed detectors consider the structural information of the covariance matrix at the design stage. Simulation results suggest performance improvement compared with existing detectors when reference cells are insufficient. Moreover, the detection performance is assessed with respect to the effects of the covariance matrix, signal subspace dimension, and mismatched performance of signal subspace as well as signal fluctuations.

  11. All-optical signal processing and regeneration

    DEFF Research Database (Denmark)

    Wolfson, David

    2001-01-01

    of a detailed large-signal model. An important parameter for SOA-based gates is the input power dynamic range (IPDR) as it determines the cascadability of the devices. Guidelines on how to maximise the IPDR are therefore established. Important trends are that short SOAs with low confinement factors and a low...... is discussed and two approaches are described and demonstrated experimentally. The first solution is based on a dual-stage converter employing an XGM-converter in the first stage and an IWC in the second stage. An assessment of the dual-stage converter at 20 Gbit/s shows an insertion penalty of -1.5 d......B. The second approach is based on a dual-order mode (DOMO) MZI and a detailed investigation at 10 Gbit/s is presented. In addition, a conversion scheme that exhibits excellent transmission and speed performance will be described and evaluated at 10 Gbit/s. Besides wavelength conversion, IWCs are also...

  12. Modeling of processes of an adaptive business management

    Directory of Open Access Journals (Sweden)

    Karev Dmitry Vladimirovich

    2011-04-01

    Full Text Available On the basis of the analysis of systems of adaptive management board business proposed the original version of the real system of adaptive management, the basis of which used dynamic recursive model cash flow forecast and real data. Proposed definitions and the simulation of scales and intervals of model time in the control system, as well as the thresholds observations and conditions of changing (correction of the administrative decisions. The process of adaptive management is illustrated on the basis proposed by the author of the script of development of business.

  13. Optical microphone with fiber Bragg grating and signal processing techniques

    Science.gov (United States)

    Tosi, Daniele; Olivero, Massimo; Perrone, Guido

    2008-06-01

    In this paper, we discuss the realization of an optical microphone array using fiber Bragg gratings as sensing elements. The wavelength shift induced by acoustic waves perturbing the sensing Bragg grating is transduced into an intensity modulation. The interrogation unit is based on a fixed-wavelength laser source and - as receiver - a photodetector with proper amplification; the system has been implemented using devices for standard optical communications, achieving a low-cost interrogator. One of the advantages of the proposed approach is that no voltage-to-strain calibration is required for tracking dynamic shifts. The optical sensor is complemented by signal processing tools, including a data-dependent frequency estimator and adaptive filters, in order to improve the frequency-domain analysis and mitigate the effects of disturbances. Feasibility and performances of the optical system have been tested measuring the output of a loudspeaker. With this configuration, the sensor is capable of correctly detecting sounds up to 3 kHz, with a frequency response that exhibits a top sensitivity within the range 200-500 Hz; single-frequency input sounds inducing an axial strain higher than ~10nɛ are correctly detected. The repeatability range is ~0.1%. The sensor has also been applied for the detection of pulsed stimuli generated from a metronome.

  14. Digital Signal Processing For Low Bit Rate TV Image Codecs

    Science.gov (United States)

    Rao, K. R.

    1987-06-01

    In view of the 56 KBPS digital switched network services and the ISDN, low bit rate codecs for providing real time full motion color video are under various stages of development. Some companies have already brought the codecs into the market. They are being used by industry and some Federal Agencies for video teleconferencing. In general, these codecs have various features such as multiplexing audio and data, high resolution graphics, encryption, error detection and correction, self diagnostics, freezeframe, split video, text overlay etc. To transmit the original color video on a 56 KBPS network requires bit rate reduction of the order of 1400:1. Such a large scale bandwidth compression can be realized only by implementing a number of sophisticated,digital signal processing techniques. This paper provides an overview of such techniques and outlines the newer concepts that are being investigated. Before resorting to the data compression techniques, various preprocessing operations such as noise filtering, composite-component transformation and horizontal and vertical blanking interval removal are to be implemented. Invariably spatio-temporal subsampling is achieved by appropriate filtering. Transform and/or prediction coupled with motion estimation and strengthened by adaptive features are some of the tools in the arsenal of the data reduction methods. Other essential blocks in the system are quantizer, bit allocation, buffer, multiplexer, channel coding etc.

  15. Deep Learning in Visual Computing and Signal Processing

    OpenAIRE

    Xie, Danfeng; Zhang, Lei; Bai, Li

    2017-01-01

    Deep learning is a subfield of machine learning, which aims to learn a hierarchy of features from input data. Nowadays, researchers have intensively investigated deep learning algorithms for solving challenging problems in many areas such as image classification, speech recognition, signal processing, and natural language processing. In this study, we not only review typical deep learning algorithms in computer vision and signal processing but also provide detailed information on how to apply...

  16. An Adaptive Traffic Signal Control in a Connected Vehicle Environment: A Systematic Review

    OpenAIRE

    Peng Jing; Hao Huang; Long Chen

    2017-01-01

    In the last few years, traffic congestion has become a growing concern due to increasing vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic signal control systems cannot adjust the timing pattern depending on road traffic demand. This results in excessive delays for road users. Adaptive traffic signal control in a connected vehicle environment has shown a powerful ability to effectively alleviate u...

  17. Grating geophone signal processing based on wavelet transform

    Science.gov (United States)

    Li, Shuqing; Zhang, Huan; Tao, Zhifei

    2008-12-01

    Grating digital geophone is designed based on grating measurement technique benefiting averaging-error effect and wide dynamic range to improve weak signal detected precision. This paper introduced the principle of grating digital geophone and its post signal processing system. The signal acquisition circuit use Atmega 32 chip as core part and display the waveform on the Labwindows through the RS232 data link. Wavelet transform is adopted this paper to filter the grating digital geophone' output signal since the signal is unstable. This data processing method is compared with the FIR filter that widespread use in current domestic. The result indicates that the wavelet algorithm has more advantages and the SNR of seismic signal improve obviously.

  18. Adapting the unified software development process for user interface development

    NARCIS (Netherlands)

    Obrenovic, Z.; Starcevic, D.

    2006-01-01

    In this paper we describe how existing software developing processes, such as Rational Unified Process, can be adapted in order to allow disciplined and more efficient development of user interfaces. The main objective of this paper is to demonstrate that standard modeling environments, based on the

  19. ADAPTIVE CONTEXT PROCESSING IN ON-LINE HANDWRITTEN CHARACTER RECOGNITION

    NARCIS (Netherlands)

    Iwayama, N.; Ishigaki, K.

    2004-01-01

    We propose a new approach to context processing in on-line handwritten character recognition (OLCR). Based on the observation that writers often repeat the strings that they input, we take the approach of adaptive context processing. (ACP). In ACP, the strings input by a writer are automatically

  20. Signal Processing of Underwater Acoustic Waves

    Science.gov (United States)

    1969-11-01

    for the interest they have shown in the work and for many helpful discussions. The book was supported by Naval Ship Systems Corn- mand tinder ...inclination of the ray. The relationship is such that for the maximum values of dnldz just quoted radius of 0ectromapnetic ray 2,0 radius of acoustic... relationship for the angles, in, of the geometric ray, and carry out the limiting process as h -- 0. Show that when the velocity func- tion c(z) is

  1. Signal processing for mobile communications handbook

    CERN Document Server

    Ibnkahla, Mohamed

    2004-01-01

    INTRODUCTIONSignal Processing for Future Mobile Communications Systems: Challenges and Perspectives; Quazi Mehbubar Rahman and Mohamed IbnkahlaCHANNEL MODELING AND ESTIMATIONMultipath Propagation Models for Broadband Wireless Systems; Andreas F. Molisch and Fredrik TufvessonModeling and Estimation of Mobile Channels; Jitendra K. TugnaitMobile Satellite Channels: Statistical Models and Performance Analysis; Giovanni E. Corazza, Alessandro Vanelli-Coralli, Raffaella Pedone, and Massimo NeriMobile Velocity Estimation for Wireless Communications; Bouchra Senadji, Ghazem Azemi, and Boualem Boashash

  2. Physics-based signal processing algorithms for micromachined cantilever arrays

    Science.gov (United States)

    Candy, James V; Clague, David S; Lee, Christopher L; Rudd, Robert E; Burnham, Alan K; Tringe, Joseph W

    2013-11-19

    A method of using physics-based signal processing algorithms for micromachined cantilever arrays. The methods utilize deflection of a micromachined cantilever that represents the chemical, biological, or physical element being detected. One embodiment of the method comprises the steps of modeling the deflection of the micromachined cantilever producing a deflection model, sensing the deflection of the micromachined cantilever and producing a signal representing the deflection, and comparing the signal representing the deflection with the deflection model.

  3. Signal Processing in Medical Ultrasound B-mode Imaging

    International Nuclear Information System (INIS)

    Song, Tai Kyong

    2000-01-01

    Ultrasonic imaging is the most widely used modality among modern imaging device for medical diagnosis and the system performance has been improved dramatically since early 90's due to the rapid advances in DSP performance and VLSI technology that made it possible to employ more sophisticated algorithms. This paper describes 'main stream' digital signal processing functions along with the associated implementation considerations in modern medical ultrasound imaging systems. Topics covered include signal processing methods for resolution improvement, ultrasound imaging system architectures, roles and necessity of the applications of DSP and VLSI technology in the development of the medical ultrasound imaging systems, and array signal processing techniques for ultrasound focusing

  4. Discrete random signal processing and filtering primer with Matlab

    CERN Document Server

    Poularikas, Alexander D

    2013-01-01

    Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering.Numerous Useful Examples, Problems, and Solutions - An Extensive and Powerful ReviewWritten for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offe

  5. Modeling laser velocimeter signals as triply stochastic Poisson processes

    Science.gov (United States)

    Mayo, W. T., Jr.

    1976-01-01

    Previous models of laser Doppler velocimeter (LDV) systems have not adequately described dual-scatter signals in a manner useful for analysis and simulation of low-level photon-limited signals. At low photon rates, an LDV signal at the output of a photomultiplier tube is a compound nonhomogeneous filtered Poisson process, whose intensity function is another (slower) Poisson process with the nonstationary rate and frequency parameters controlled by a random flow (slowest) process. In the present paper, generalized Poisson shot noise models are developed for low-level LDV signals. Theoretical results useful in detection error analysis and simulation are presented, along with measurements of burst amplitude statistics. Computer generated simulations illustrate the difference between Gaussian and Poisson models of low-level signals.

  6. Surface light scattering: integrated technology and signal processing

    DEFF Research Database (Denmark)

    Lading, L.; Dam-Hansen, C.; Rasmussen, E.

    1997-01-01

    systems representing increasing levels of integration are considered. It is demonstrated that efficient signal and data processing can be achieved by evaluation of the statistics of the derivative of the instantaneous phase of the detector signal. (C) 1997 Optical Society of America....

  7. Distortions caused by the signal processing in analog AM modulators

    International Nuclear Information System (INIS)

    Njau, E.C.

    1988-08-01

    Complete analytical expressions for distortions caused by signal processing in analog AM modulators are developed. The salient features in these expressions are shown to be consistent with displays of actual spectra of AM signals. Finally suggestions are given on how the distortions may be practically minimized. (author). 6 refs, 3 figs

  8. Adaptive endpoint detection of seismic signal based on auto-correlated function

    International Nuclear Information System (INIS)

    Fan Wanchun; Shi Ren

    2001-01-01

    Based on the analysis of auto-correlation function, the notion of the distance between auto-correlation function was quoted, and the characterization of the noise and the signal with noise were discussed by using the distance. Then, the method of auto- adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low signal with noise ratio circumstance

  9. Nuclear pulse signal processing techniques based on blind deconvolution method

    International Nuclear Information System (INIS)

    Hong Pengfei; Yang Lei; Qi Zhong; Meng Xiangting; Fu Yanyan; Li Dongcang

    2012-01-01

    This article presents a method of measurement and analysis of nuclear pulse signal, the FPGA to control high-speed ADC measurement of nuclear radiation signals and control the high-speed transmission status of the USB to make it work on the Slave FIFO mode, using the LabVIEW online data processing and display, using the blind deconvolution method to remove the accumulation of signal acquisition, and to restore the nuclear pulse signal with a transmission speed, real-time measurements show that the advantages. (authors)

  10. Explicit and implicit processes in behavioural adaptation to road width.

    Science.gov (United States)

    Lewis-Evans, Ben; Charlton, Samuel G

    2006-05-01

    The finding that drivers may react to safety interventions in a way that is contrary to what was intended is the phenomenon of behavioural adaptation. This phenomenon has been demonstrated across various safety interventions and has serious implications for road safety programs the world over. The present research used a driving simulator to assess behavioural adaptation in drivers' speed and lateral displacement in response to manipulations of road width. Of interest was whether behavioural adaptation would occur and whether we could determine whether it was the result of explicit, conscious decisions or implicit perceptual processes. The results supported an implicit, zero perceived risk model of behavioural adaptation with reduced speeds on a narrowed road accompanied by increased ratings of risk and a marked inability of the participants to identify that any change in road width had occurred.

  11. Software for biomedical engineering signal processing laboratory experiments.

    Science.gov (United States)

    Tompkins, Willis J; Wilson, J

    2009-01-01

    In the early 1990's we developed a special computer program called UW DigiScope to provide a mechanism for anyone interested in biomedical digital signal processing to study the field without requiring any other instrument except a personal computer. There are many digital filtering and pattern recognition algorithms used in processing biomedical signals. In general, students have very limited opportunity to have hands-on access to the mechanisms of digital signal processing. In a typical course, the filters are designed non-interactively, which does not provide the student with significant understanding of the design constraints of such filters nor their actual performance characteristics. UW DigiScope 3.0 is the first major update since version 2.0 was released in 1994. This paper provides details on how the new version based on MATLAB! works with signals, including the filter design tool that is the programming interface between UW DigiScope and processing algorithms.

  12. Measuring methods, registration and signal processing for magnetic field research

    International Nuclear Information System (INIS)

    Nagiello, Z.

    1981-01-01

    Some measuring methods and signal processing systems based on analogue and digital technics, which have been applied in magnetic field research using magnetometers with ferromagnetic transducers, are presented. (author)

  13. Array signal processing in the NASA Deep Space Network

    Science.gov (United States)

    Pham, Timothy T.; Jongeling, Andre P.

    2004-01-01

    In this paper, we will describe the benefits of arraying and past as well as expected future use of this application. The signal processing aspects of array system are described. Field measurements via actual tracking spacecraft are also presented.

  14. Hybrid digital signal processing and neural networks applications in PWRs

    International Nuclear Information System (INIS)

    Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

    1991-01-01

    Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications

  15. 4th International Conference on Communications, Signal Processing, and Systems

    CERN Document Server

    Mu, Jiasong; Wang, Wei; Zhang, Baoju

    2016-01-01

    This book brings together papers presented at the 4th International Conference on Communications, Signal Processing, and Systems, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from Communications, Signal Processing and Systems, this book is aimed at undergraduate and graduate students in Electrical Engineering, Computer Science and Mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD, DOE, etc).

  16. Analogue Signal Processing: Collected Papers 1994-95

    DEFF Research Database (Denmark)

    1996-01-01

    This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of Electronics Institute, Technical University of Denmark, in 1994 and 1995.......This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of Electronics Institute, Technical University of Denmark, in 1994 and 1995....

  17. Analogue Signal Processing: Collected Papers 1996-97

    DEFF Research Database (Denmark)

    1997-01-01

    This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of the Department of Information Technology, Technical University of Denmark, in 1996 and 1997.......This document is a collection of the papers presented at international conferences and in international journals by the analogue signal processing group of the Department of Information Technology, Technical University of Denmark, in 1996 and 1997....

  18. Time reversal signal processing in acoustic emission testing

    Czech Academy of Sciences Publication Activity Database

    Převorovský, Zdeněk; Krofta, Josef; Kober, Jan; Dvořáková, Zuzana; Chlada, Milan; Dos Santos, S.

    2014-01-01

    Roč. 19, č. 12 (2014) ISSN 1435-4934. [European Conference on Non-Destructive Testing (ECNDT 2014) /11./. Praha, 06.10.2014-10.10.2014] Institutional support: RVO:61388998 Keywords : acoustic emission (AE) * ultrasonic testing (UT) * signal processing * source location * time reversal acoustic s * acoustic emission * signal processing and transfer Subject RIV: BI - Acoustic s http://www.ndt.net/events/ECNDT2014/app/content/Slides/637_Prevorovsky.pdf

  19. Recent Advancements in Semiconductor-based Optical Signal Processing

    DEFF Research Database (Denmark)

    Nielsen, M L; Mørk, Jesper

    2006-01-01

    Significant advancements in technology and basic understanding of device physics are bringing optical signal processing closer to a commercial breakthrough. In this paper we describe the main challenges in high-speed SOA-based switching.......Significant advancements in technology and basic understanding of device physics are bringing optical signal processing closer to a commercial breakthrough. In this paper we describe the main challenges in high-speed SOA-based switching....

  20. High-speed optical signal processing using time lenses

    DEFF Research Database (Denmark)

    Galili, Michael; Hu, Hao; Guan, Pengyu

    2015-01-01

    This paper will discuss time lenses and their broad range of applications. A number of recent demonstrations of complex high-speed optical signal processing using time lenses will be outlined with focus on the operating principle.......This paper will discuss time lenses and their broad range of applications. A number of recent demonstrations of complex high-speed optical signal processing using time lenses will be outlined with focus on the operating principle....

  1. Ultrafast optical signal processing using semiconductor quantum dot amplifiers

    DEFF Research Database (Denmark)

    Berg, Tommy Winther; Mørk, Jesper

    2002-01-01

    The linear and nonlinear properties of quantum dot amplifiers are discussed on the basis of an extensive theoretical model. These devices show great potential for linear amplification as well as ultrafast signal processing.......The linear and nonlinear properties of quantum dot amplifiers are discussed on the basis of an extensive theoretical model. These devices show great potential for linear amplification as well as ultrafast signal processing....

  2. Linear signal processing using silicon micro-ring resonators

    DEFF Research Database (Denmark)

    Peucheret, Christophe; Ding, Yunhong; Ou, Haiyan

    2012-01-01

    We review our recent achievements on the use of silicon micro-ring resonators for linear optical signal processing applications, including modulation format conversion, phase-to-intensity modulation conversion and waveform shaping.......We review our recent achievements on the use of silicon micro-ring resonators for linear optical signal processing applications, including modulation format conversion, phase-to-intensity modulation conversion and waveform shaping....

  3. Registration and processing of acoustic signal in rock drilling

    Directory of Open Access Journals (Sweden)

    Futó Jozef

    2002-03-01

    Full Text Available For the determination of an effective rock disintegration for a given tool and rock type it is needed to define an optimal disintegration regime. Optimisation of the disintegration process by drilling denotes the finding out an appropriate couple of input parameters of disintegration, i.e. the thrust and revolutions for a quasi-equal rock environment. The disintegration process can be optimised to reach the maximum immediate drilling rate, to reach the minimum specific disintegration energy or to reach the maximum ratio of immediate drilling rate and specific disintegration energy. For the determination of the optimal thrust and revolutions it is needed to monitor the disintegration process. Monitoring of the disintegration process in real conditions is complicated by unfavourable factors, such as the presence of water, dust, vibrations etc. Following our present experience in the monitoring of drilling or full-profile driving, we try to replace the monitoring of input values by monitoring of the scanned acoustic signal. This method of monitoring can extend the optimisation of disintegration process in the technical practice. Its advantage consists in the registration of one acoustic signal by an appropriate microphone. Monitoring of acoustic signal is used also in monitoring of metal machining by milling and turning jobs. The research results of scanning of the acoustic signal in machining of metals are encouraging. Acoustic signal can be processed by different statistical parameters. The paper decribes some results of monitoring of the acoustic signal in rock disintegration on the drilling stand of the Institute of Geotechnics SAS in Košice. The acoustic signal has been registered and processed in no-load run of electric motor, in no-load run of electric motor with a drilling fluid, and in the Ruskov andesite drilling. Registration and processing of the acoustic signal is solved as a part of the research grant task within the basic research

  4. A Computer- Based Digital Signal Processing for Nuclear Scintillator Detectors

    International Nuclear Information System (INIS)

    Ashour, M.A.; Abo Shosha, A.M.

    2000-01-01

    In this paper, a Digital Signal Processing (DSP) Computer-based system for the nuclear scintillation signals with exponential decay is presented. The main objective of this work is to identify the characteristics of the acquired signals smoothly, this can be done by transferring the signal environment from random signal domain to deterministic domain using digital manipulation techniques. The proposed system consists of two major parts. The first part is the high performance data acquisition system (DAQ) that depends on a multi-channel Logic Scope. Which is interfaced with the host computer through the General Purpose Interface Board (GPIB) Ver. IEEE 488.2. Also, a Graphical User Interface (GUI) has been designed for this purpose using the graphical programming facilities. The second of the system is the DSP software Algorithm which analyses, demonstrates, monitoring these data to obtain the main characteristics of the acquired signals; the amplitude, the pulse count, the pulse width, decay factor, and the arrival time

  5. A Study on Signal Group Processing of AUTOSAR COM Module

    International Nuclear Information System (INIS)

    Lee, Jeong-Hwan; Hwang, Hyun Yong; Han, Tae Man; Ahn, Yong Hak

    2013-01-01

    In vehicle, there are many ECU(Electronic Control Unit)s, and ECUs are connected to networks such as CAN, LIN, FlexRay, and so on. AUTOSAR COM(Communication) which is a software platform of AUTOSAR(AUTomotive Open System ARchitecture) in the international industry standards of automotive electronic software processes signals and signal groups for data communications between ECUs. Real-time and reliability are very important for data communications in the vehicle. Therefore, in this paper, we analyze functions of signals and signal groups used in COM, and represent that functions of signal group are more efficient than signals in real-time data synchronization and network resource usage between the sender and receiver.

  6. A Study on Signal Group Processing of AUTOSAR COM Module

    Science.gov (United States)

    Lee, Jeong-Hwan; Hwang, Hyun Yong; Han, Tae Man; Ahn, Yong Hak

    2013-06-01

    In vehicle, there are many ECU(Electronic Control Unit)s, and ECUs are connected to networks such as CAN, LIN, FlexRay, and so on. AUTOSAR COM(Communication) which is a software platform of AUTOSAR(AUTomotive Open System ARchitecture) in the international industry standards of automotive electronic software processes signals and signal groups for data communications between ECUs. Real-time and reliability are very important for data communications in the vehicle. Therefore, in this paper, we analyze functions of signals and signal groups used in COM, and represent that functions of signal group are more efficient than signals in real-time data synchronization and network resource usage between the sender and receiver.

  7. Digital signal processing for He3 proportional counter

    International Nuclear Information System (INIS)

    Zeynalov, Sh.S.; Ahmadov, Q.S.

    2010-01-01

    Full text : Data acquisition systems for nuclear spectroscopy have traditionally been based on systems with analog shaping amplifiers followed by analog-to-digital converters. Recently, however, new systems based on digital signal processing make possible to replace the analog shaping and timing circuitry the numerical algorithms to derive properties of the pulse such as its amplitude. DSP is a fully numerical analysis of the detector pulse signals and this technique demonstrates significant advantages over analog systems in some circumstances. From a mathematical point of view, one can consider the signal evolution from the detector to the ADC as a sequence of transformations that can be described by precisely defined mathematical expressions. Digital signal processing with ADCs has the possibility to utilize further information on the signal pulses from radiation detectors. In the experiment each step of the signal generation in the 3He filled proportional counter was described using digital signal processing techniques (DSP). The electronic system has consisted of a detector, a preamplifier and a digital oscilloscope. The pulses from the detector were digitized using a digital storage oscilloscope. This oscilloscope allowed signal digitization with accuracy of 8 bit (256 levels) and with frequency of up to 5 * 10 8 samples/s. As a neutron source was used Cf-252. To obtain detector output current pulse I(t) created by the motions of the ions/electrons pairs was written an algorithm which can easily be programmed using modern computer programming languages.

  8. Applying advanced digital signal processing techniques in industrial radioisotopes applications

    International Nuclear Information System (INIS)

    Mahmoud, H.K.A.E.

    2012-01-01

    Radioisotopes can be used to obtain signals or images in order to recognize the information inside the industrial systems. The main problems of using these techniques are the difficulty of identification of the obtained signals or images and the requirement of skilled experts for the interpretation process of the output data of these applications. Now, the interpretation of the output data from these applications is performed mainly manually, depending heavily on the skills and the experience of trained operators. This process is time consuming and the results typically suffer from inconsistency and errors. The objective of the thesis is to apply the advanced digital signal processing techniques for improving the treatment and the interpretation of the output data from the different Industrial Radioisotopes Applications (IRA). This thesis focuses on two IRA; the Residence Time Distribution (RTD) measurement and the defect inspection of welded pipes using a gamma source (gamma radiography). In RTD measurement application, this thesis presents methods for signal pre-processing and modeling of the RTD signals. Simulation results have been presented for two case studies. The first case study is a laboratory experiment for measuring the RTD in a water flow rig. The second case study is an experiment for measuring the RTD in a phosphate production unit. The thesis proposes an approach for RTD signal identification in the presence of noise. In this approach, after signal processing, the Mel Frequency Cepstral Coefficients (MFCCs) and polynomial coefficients are extracted from the processed signal or from one of its transforms. The Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), and Discrete Sine Transform (DST) have been tested and compared for efficient feature extraction. Neural networks have been used for matching of the extracted features. Furthermore, the Power Density Spectrum (PDS) of the RTD signal has been also used instead of the discrete

  9. Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals

    Science.gov (United States)

    Miles, Jeffrey Hilton

    2015-01-01

    A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.

  10. Decoding Signal Processing at the Single-Cell Level

    Energy Technology Data Exchange (ETDEWEB)

    Wiley, H. Steven

    2017-12-01

    The ability of cells to detect and decode information about their extracellular environment is critical to generating an appropriate response. In multicellular organisms, cells must decode dozens of signals from their neighbors and extracellular matrix to maintain tissue homeostasis while still responding to environmental stressors. How cells detect and process information from their surroundings through a surprisingly limited number of signal transduction pathways is one of the most important question in biology. Despite many decades of research, many of the fundamental principles that underlie cell signal processing remain obscure. However, in this issue of Cell Systems, Gillies et al present compelling evidence that the early response gene circuit can act as a linear signal integrator, thus providing significant insight into how cells handle fluctuating signals and noise in their environment.

  11. Digital signal processing in power system protection and control

    CERN Document Server

    Rebizant, Waldemar; Wiszniewski, Andrzej

    2011-01-01

    Digital Signal Processing in Power System Protection and Control bridges the gap between the theory of protection and control and the practical applications of protection equipment. Understanding how protection functions is crucial not only for equipment developers and manufacturers, but also for their users who need to install, set and operate the protection devices in an appropriate manner. After introductory chapters related to protection technology and functions, Digital Signal Processing in Power System Protection and Control presents the digital algorithms for signal filtering, followed

  12. Signal Processing, Pattern Formation and Adaptation in Neural Oscillators

    Science.gov (United States)

    2016-11-29

    rhythmic patterns. As such, our models are appropriate for describing various phenomena in the auditory system, including critical nonlinear...several distinct intrinsic behaviors available near a Hopf bifurcation or a Bautin (a.k.a. double limit cycle) bifurcation. Stability analysis shows...example the perception of pitch at event timescales (Meddis & O’Mard, 2006) and the perception of pulse and meter at rhythmic timescales (Large

  13. Robust Adaptive Signal Processing Methods for Heterogeneous Radar Clutter Scenarios

    National Research Council Canada - National Science Library

    Rangaswamy, Muralidhar; Lin, Freeman C; Gerlach, Karl R

    2004-01-01

    .... Specifically, we present the performance of the normalized matched filter test in a background of disturbance consisting of clutter having a covariance matrix with known structure and unknown scaling...

  14. The Signal Validation method of Digital Process Instrumentation System on signal conditioner for SMART

    International Nuclear Information System (INIS)

    Moon, Hee Gun; Park, Sang Min; Kim, Jung Seon; Shon, Chang Ho; Park, Heui Youn; Koo, In Soo

    2005-01-01

    The function of PIS(Process Instrumentation System) for SMART is to acquire the process data from sensor or transmitter. The PIS consists of signal conditioner, A/D converter, DSP(Digital Signal Process) and NIC(Network Interface Card). So, It is fully digital system after A/D converter. The PI cabinet and PDAS(Plant Data Acquisition System) in commercial plant is responsible for data acquisition of the sensor or transmitter include RTD, TC, level, flow, pressure and so on. The PDAS has the software that processes each sensor data and PI cabinet has the signal conditioner, which is need for maintenance and test. The signal conditioner has the potentiometer to adjust the span and zero for test and maintenance. The PIS of SMART also has the signal conditioner which has the span and zero adjust same as the commercial plant because the signal conditioner perform the signal condition for AD converter such as 0∼10Vdc. But, To adjust span and zero is manual test and calibration. So, This paper presents the method of signal validation and calibration, which is used by digital feature in SMART. There are I/E(current to voltage), R/E(resistor to voltage), F/E(frequency to voltage), V/V(voltage to voltage). Etc. In this paper show only the signal validation and calibration about I/E converter that convert level, pressure, flow such as 4∼20mA into signal for AD conversion such as 0∼10Vdc

  15. Blood oxygenation level dependent signal and neuronal adaptation to optogenetic and sensory stimulation in somatosensory cortex in awake animals.

    Science.gov (United States)

    Aksenov, Daniil P; Li, Limin; Miller, Michael J; Wyrwicz, Alice M

    2016-11-01

    The adaptation of neuronal responses to stimulation, in which a peak transient response is followed by a sustained plateau, has been well-studied. The blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal has also been shown to exhibit adaptation on a longer time scale. However, some regions such as the visual and auditory cortices exhibit significant BOLD adaptation, whereas other such as the whisker barrel cortex may not adapt. In the sensory cortex a combination of thalamic inputs and intracortical activity drives hemodynamic changes, although the relative contributions of these components are not entirely understood. The aim of this study is to assess the role of thalamic inputs vs. intracortical processing in shaping BOLD adaptation during stimulation in the somatosensory cortex. Using simultaneous fMRI and electrophysiology in awake rabbits, we measured BOLD, local field potentials (LFPs), single- and multi-unit activity in the cortex during whisker and optogenetic stimulation. This design allowed us to compare BOLD and haemodynamic responses during activation of the normal thalamocortical sensory pathway (i.e., both inputs and intracortical activity) vs. the direct optical activation of intracortical circuitry alone. Our findings show that whereas LFP and multi-unit (MUA) responses adapted, neither optogenetic nor sensory stimulation produced significant BOLD adaptation. We observed for both paradigms a variety of excitatory and inhibitory single unit responses. We conclude that sensory feed-forward thalamic inputs are not primarily responsible for shaping BOLD adaptation to stimuli; but the single-unit results point to a role in this behaviour for specific excitatory and inhibitory neuronal sub-populations, which may not correlate with aggregate neuronal activity. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  16. Removing Background Noise with Phased Array Signal Processing

    Science.gov (United States)

    Podboy, Gary; Stephens, David

    2015-01-01

    Preliminary results are presented from a test conducted to determine how well microphone phased array processing software could pull an acoustic signal out of background noise. The array consisted of 24 microphones in an aerodynamic fairing designed to be mounted in-flow. The processing was conducted using Functional Beam forming software developed by Optinav combined with cross spectral matrix subtraction. The test was conducted in the free-jet of the Nozzle Acoustic Test Rig at NASA GRC. The background noise was produced by the interaction of the free-jet flow with the solid surfaces in the flow. The acoustic signals were produced by acoustic drivers. The results show that the phased array processing was able to pull the acoustic signal out of the background noise provided the signal was no more than 20 dB below the background noise level measured using a conventional single microphone equipped with an aerodynamic forebody.

  17. Biomedical signal acquisition, processing and transmission using smartphone

    International Nuclear Information System (INIS)

    Roncagliolo, Pablo; Arredondo, Luis; Gonzalez, AgustIn

    2007-01-01

    This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home

  18. Biomedical signal acquisition, processing and transmission using smartphone

    Energy Technology Data Exchange (ETDEWEB)

    Roncagliolo, Pablo [Department of Electronics, Universidad Tecnica Federico Santa Maria, Casilla 110-V, ValparaIso (Chile); Arredondo, Luis [Department of Biomedical Engineering, Universidad de ValparaIso, Casilla 123-V, ValparaIso (Chile); Gonzalez, AgustIn [Department of Electronics, Universidad Tecnica Federico Santa MarIa, Casilla 110-V, ValparaIso (Chile)

    2007-11-15

    This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home.

  19. Mathematical principles of signal processing Fourier and wavelet analysis

    CERN Document Server

    Brémaud, Pierre

    2002-01-01

    Fourier analysis is one of the most useful tools in many applied sciences. The recent developments of wavelet analysis indicates that in spite of its long history and well-established applications, the field is still one of active research. This text bridges the gap between engineering and mathematics, providing a rigorously mathematical introduction of Fourier analysis, wavelet analysis and related mathematical methods, while emphasizing their uses in signal processing and other applications in communications engineering. The interplay between Fourier series and Fourier transforms is at the heart of signal processing, which is couched most naturally in terms of the Dirac delta function and Lebesgue integrals. The exposition is organized into four parts. The first is a discussion of one-dimensional Fourier theory, including the classical results on convergence and the Poisson sum formula. The second part is devoted to the mathematical foundations of signal processing - sampling, filtering, digital signal proc...

  20. Methods and systems for the processing of physiological signals

    International Nuclear Information System (INIS)

    Cosnac, B. de; Gariod, R.; Max, J.; Monge, V.

    1975-01-01

    This note is a general survey of the processing of physiological signals. After an introduction about electrodes and their limitations, the physiological nature of the main signals are shortly recalled. Different methods (signal averaging, spectral analysis, shape morphological analysis) are described as applications to the fields of magnetocardiography, electro-encephalography, cardiography, electronystagmography. As for processing means (single portable instruments and programmable), they are described through the example of application to rheography and to the Plurimat'S general system. As a conclusion the methods of signal processing are dominated by the morphological analysis of curves and by the necessity of a more important introduction of the statistical classification. As for the instruments, microprocessors will appear but specific operators linked to computer will certainly grow [fr

  1. Biomedical signal acquisition, processing and transmission using smartphone

    Science.gov (United States)

    Roncagliolo, Pablo; Arredondo, Luis; González, Agustín

    2007-11-01

    This article describes technical aspects involved in the programming of a system of acquisition, processing and transmission of biomedical signals by using mobile devices. This task is aligned with the permanent development of new technologies for the diagnosis and sickness treatment, based on the feasibility of measuring continuously different variables as electrocardiographic signals, blood pressure, oxygen concentration, pulse or simply temperature. The contribution of this technology is settled on its portability and low cost, which allows its massive use. Specifically this work analyzes the feasibility of acquisition and the processing of signals from a standard smartphone. Work results allow to state that nowadays these equipments have enough processing capacity to execute signals acquisition systems. These systems along with external servers make it possible to imagine a near future where the possibility of making continuous measures of biomedical variables will not be restricted only to hospitals but will also begin to be more frequently used in the daily life and at home.

  2. High-speed optical coherence tomography signal processing on GPU

    International Nuclear Information System (INIS)

    Li Xiqi; Shi Guohua; Zhang Yudong

    2011-01-01

    The signal processing speed of spectral domain optical coherence tomography (SD-OCT) has become a bottleneck in many medical applications. Recently, a time-domain interpolation method was proposed. This method not only gets a better signal-to noise ratio (SNR) but also gets a faster signal processing time for the SD-OCT than the widely used zero-padding interpolation method. Furthermore, the re-sampled data is obtained by convoluting the acquired data and the coefficients in time domain. Thus, a lot of interpolations can be performed concurrently. So, this interpolation method is suitable for parallel computing. An ultra-high optical coherence tomography signal processing can be realized by using graphics processing unit (GPU) with computer unified device architecture (CUDA). This paper will introduce the signal processing steps of SD-OCT on GPU. An experiment is performed to acquire a frame SD-OCT data (400A-linesx2048 pixel per A-line) and real-time processed the data on GPU. The results show that it can be finished in 6.208 milliseconds, which is 37 times faster than that on Central Processing Unit (CPU).

  3. Signals and Systems in Biomedical Engineering Signal Processing and Physiological Systems Modeling

    CERN Document Server

    Devasahayam, Suresh R

    2013-01-01

    The use of digital signal processing is ubiquitous in the field of physiology and biomedical engineering. The application of such mathematical and computational tools requires a formal or explicit understanding of physiology. Formal models and analytical techniques are interlinked in physiology as in any other field. This book takes a unitary approach to physiological systems, beginning with signal measurement and acquisition, followed by signal processing, linear systems modelling, and computer simulations. The signal processing techniques range across filtering, spectral analysis and wavelet analysis. Emphasis is placed on fundamental understanding of the concepts as well as solving numerical problems. Graphs and analogies are used extensively to supplement the mathematics. Detailed models of nerve and muscle at the cellular and systemic levels provide examples for the mathematical methods and computer simulations. Several of the models are sufficiently sophisticated to be of value in understanding real wor...

  4. Classification of EEG Signals using adaptive weighted distance nearest neighbor algorithm

    Directory of Open Access Journals (Sweden)

    E. Parvinnia

    2014-01-01

    Full Text Available Electroencephalogram (EEG signals are often used to diagnose diseases such as seizure, alzheimer, and schizophrenia. One main problem with the recorded EEG samples is that they are not equally reliable due to the artifacts at the time of recording. EEG signal classification algorithms should have a mechanism to handle this issue. It seems that using adaptive classifiers can be useful for the biological signals such as EEG. In this paper, a general adaptive method named weighted distance nearest neighbor (WDNN is applied for EEG signal classification to tackle this problem. This classification algorithm assigns a weight to each training sample to control its influence in classifying test samples. The weights of training samples are used to find the nearest neighbor of an input query pattern. To assess the performance of this scheme, EEG signals of thirteen schizophrenic patients and eighteen normal subjects are analyzed for the classification of these two groups. Several features including, fractal dimension, band power and autoregressive (AR model are extracted from EEG signals. The classification results are evaluated using Leave one (subject out cross validation for reliable estimation. The results indicate that combination of WDNN and selected features can significantly outperform the basic nearest-neighbor and the other methods proposed in the past for the classification of these two groups. Therefore, this method can be a complementary tool for specialists to distinguish schizophrenia disorder.

  5. Signaling and Adaptation Modulate the Dynamics of the Photosensoric Complex of Natronomonas pharaonis.

    Directory of Open Access Journals (Sweden)

    Philipp S Orekhov

    2015-10-01

    Full Text Available Motile bacteria and archaea respond to chemical and physical stimuli seeking optimal conditions for survival. To this end transmembrane chemo- and photoreceptors organized in large arrays initiate signaling cascades and ultimately regulate the rotation of flagellar motors. To unravel the molecular mechanism of signaling in an archaeal phototaxis complex we performed coarse-grained molecular dynamics simulations of a trimer of receptor/transducer dimers, namely NpSRII/NpHtrII from Natronomonas pharaonis. Signaling is regulated by a reversible methylation mechanism called adaptation, which also influences the level of basal receptor activation. Mimicking two extreme methylation states in our simulations we found conformational changes for the transmembrane region of NpSRII/NpHtrII which resemble experimentally observed light-induced changes. Further downstream in the cytoplasmic domain of the transducer the signal propagates via distinct changes in the dynamics of HAMP1, HAMP2, the adaptation domain and the binding region for the kinase CheA, where conformational rearrangements were found to be subtle. Overall these observations suggest a signaling mechanism based on dynamic allostery resembling models previously proposed for E. coli chemoreceptors, indicating similar properties of signal transduction for archaeal photoreceptors and bacterial chemoreceptors.

  6. Research in adaptive management: working relations and the research process.

    Science.gov (United States)

    Amanda C. Graham; Linda E. Kruger

    2002-01-01

    This report analyzes how a small group of Forest Service scientists participating in efforts to implement adaptive management approach working relations, and how they understand and apply the research process. Nine scientists completed a questionnaire to assess their preferred mode of thinking (the Herrmann Brain Dominance Instrument), engaged in a facilitated...

  7. Dissociating Face Identity and Facial Expression Processing Via Visual Adaptation

    Directory of Open Access Journals (Sweden)

    Hong Xu

    2012-10-01

    Full Text Available Face identity and facial expression are processed in two distinct neural pathways. However, most of the existing face adaptation literature studies them separately, despite the fact that they are two aspects from the same face. The current study conducted a systematic comparison between these two aspects by face adaptation, investigating how top- and bottom-half face parts contribute to the processing of face identity and facial expression. A real face (sad, “Adam” and its two size-equivalent face parts (top- and bottom-half were used as the adaptor in separate conditions. For face identity adaptation, the test stimuli were generated by morphing Adam's sad face with another person's sad face (“Sam”. For facial expression adaptation, the test stimuli were created by morphing Adam's sad face with his neutral face and morphing the neutral face with his happy face. In each trial, after exposure to the adaptor, observers indicated the perceived face identity or facial expression of the following test face via a key press. They were also tested in a baseline condition without adaptation. Results show that the top- and bottom-half face each generated a significant face identity aftereffect. However, the aftereffect by top-half face adaptation is much larger than that by the bottom-half face. On the contrary, only the bottom-half face generated a significant facial expression aftereffect. This dissociation of top- and bottom-half face adaptation suggests that face parts play different roles in face identity and facial expression. It thus provides further evidence for the distributed systems of face perception.

  8. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  9. General purpose graphic processing unit implementation of adaptive pulse compression algorithms

    Science.gov (United States)

    Cai, Jingxiao; Zhang, Yan

    2017-07-01

    This study introduces a practical approach to implement real-time signal processing algorithms for general surveillance radar based on NVIDIA graphical processing units (GPUs). The pulse compression algorithms are implemented using compute unified device architecture (CUDA) libraries such as CUDA basic linear algebra subroutines and CUDA fast Fourier transform library, which are adopted from open source libraries and optimized for the NVIDIA GPUs. For more advanced, adaptive processing algorithms such as adaptive pulse compression, customized kernel optimization is needed and investigated. A statistical optimization approach is developed for this purpose without needing much knowledge of the physical configurations of the kernels. It was found that the kernel optimization approach can significantly improve the performance. Benchmark performance is compared with the CPU performance in terms of processing accelerations. The proposed implementation framework can be used in various radar systems including ground-based phased array radar, airborne sense and avoid radar, and aerospace surveillance radar.

  10. Ebola Virus Altered Innate and Adaptive Immune Response Signalling Pathways: Implications for Novel Therapeutic Approaches.

    Science.gov (United States)

    Kumar, Anoop

    2016-01-01

    Ebola virus (EBOV) arise attention for their impressive lethality by the poor immune response and high inflammatory reaction in the patients. It causes a severe hemorrhagic fever with case fatality rates of up to 90%. The mechanism underlying this lethal outcome is poorly understood. In 2014, a major outbreak of Ebola virus spread amongst several African countries, including Leone, Sierra, and Guinea. Although infections only occur frequently in Central Africa, but the virus has the potential to spread globally. Presently, there is no vaccine or treatment is available to counteract Ebola virus infections due to poor understanding of its interaction with the immune system. Accumulating evidence indicates that the virus actively alters both innate and adaptive immune responses and triggers harmful inflammatory responses. In the literature, some reports have shown that alteration of immune signaling pathways could be due to the ability of EBOV to interfere with dendritic cells (DCs), which link innate and adaptive immune responses. On the other hand, some reports have demonstrated that EBOV, VP35 proteins act as interferon antagonists. So, how the Ebola virus altered the innate and adaptive immune response signaling pathways is still an open question for the researcher to be explored. Thus, in this review, I try to summarize the mechanisms of the alteration of innate and adaptive immune response signaling pathways by Ebola virus which will be helpful for designing effective drugs or vaccines against this lethal infection. Further, potential targets, current treatment and novel therapeutic approaches have also been discussed.

  11. Magnetic MIMO Signal Processing and Optimization for Wireless Power Transfer

    Science.gov (United States)

    Yang, Gang; Moghadam, Mohammad R. Vedady; Zhang, Rui

    2017-06-01

    In magnetic resonant coupling (MRC) enabled multiple-input multiple-output (MIMO) wireless power transfer (WPT) systems, multiple transmitters (TXs) each with one single coil are used to enhance the efficiency of simultaneous power transfer to multiple single-coil receivers (RXs) by constructively combining their induced magnetic fields at the RXs, a technique termed "magnetic beamforming". In this paper, we study the optimal magnetic beamforming design in a multi-user MIMO MRC-WPT system. We introduce the multi-user power region that constitutes all the achievable power tuples for all RXs, subject to the given total power constraint over all TXs as well as their individual peak voltage and current constraints. We characterize each boundary point of the power region by maximizing the sum-power deliverable to all RXs subject to their minimum harvested power constraints. For the special case without the TX peak voltage and current constraints, we derive the optimal TX current allocation for the single-RX setup in closed-form as well as that for the multi-RX setup. In general, the problem is a non-convex quadratically constrained quadratic programming (QCQP), which is difficult to solve. For the case of one single RX, we show that the semidefinite relaxation (SDR) of the problem is tight. For the general case with multiple RXs, based on SDR we obtain two approximate solutions by applying time-sharing and randomization, respectively. Moreover, for practical implementation of magnetic beamforming, we propose a novel signal processing method to estimate the magnetic MIMO channel due to the mutual inductances between TXs and RXs. Numerical results show that our proposed magnetic channel estimation and adaptive beamforming schemes are practically effective, and can significantly improve the power transfer efficiency and multi-user performance trade-off in MIMO MRC-WPT systems.

  12. Adaptation.

    Science.gov (United States)

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  13. Signal processing techniques for sodium boiling noise detection

    International Nuclear Information System (INIS)

    1989-05-01

    At the Specialists' Meeting on Sodium Boiling Detection organized by the International Working Group on Fast Reactors (IWGFR) of the International Atomic Energy Agency at Chester in the United Kingdom in 1981 various methods of detecting sodium boiling were reported. But, it was not possible to make a comparative assessment of these methods because the signal condition in each experiment was different from others. That is why participants of this meeting recommended that a benchmark test should be carried out in order to evaluate and compare signal processing methods for boiling detection. Organization of the Co-ordinated Research Programme (CRP) on signal processing techniques for sodium boiling noise detection was also recommended at the 16th meeting of the IWGFR. The CRP on Signal Processing Techniques for Sodium Boiling Noise Detection was set up in 1984. Eight laboratories from six countries have agreed to participate in this CRP. The overall objective of the programme was the development of reliable on-line signal processing techniques which could be used for the detection of sodium boiling in an LMFBR core. During the first stage of the programme a number of existing processing techniques used by different countries have been compared and evaluated. In the course of further work, an algorithm for implementation of this sodium boiling detection system in the nuclear reactor will be developed. It was also considered that the acoustic signal processing techniques developed for boiling detection could well make a useful contribution to other acoustic applications in the reactor. This publication consists of two parts. Part I is the final report of the co-ordinated research programme on signal processing techniques for sodium boiling noise detection. Part II contains two introductory papers and 20 papers presented at four research co-ordination meetings since 1985. A separate abstract was prepared for each of these 22 papers. Refs, figs and tabs

  14. Tunable signal processing in synthetic MAP kinase cascades.

    Science.gov (United States)

    O'Shaughnessy, Ellen C; Palani, Santhosh; Collins, James J; Sarkar, Casim A

    2011-01-07

    The flexibility of MAPK cascade responses enables regulation of a vast array of cell fate decisions, but elucidating the mechanisms underlying this plasticity is difficult in endogenous signaling networks. We constructed insulated mammalian MAPK cascades in yeast to explore how intrinsic and extrinsic perturbations affect the flexibility of these synthetic signaling modules. Contrary to biphasic dependence on scaffold concentration, we observe monotonic decreases in signal strength as scaffold concentration increases. We find that augmenting the concentration of sequential kinases can enhance ultrasensitivity and lower the activation threshold. Further, integrating negative regulation and concentration variation can decouple ultrasensitivity and threshold from the strength of the response. Computational analyses show that cascading can generate ultrasensitivity and that natural cascades with different kinase concentrations are innately biased toward their distinct activation profiles. This work demonstrates that tunable signal processing is inherent to minimal MAPK modules and elucidates principles for rational design of synthetic signaling systems. Copyright © 2011 Elsevier Inc. All rights reserved.

  15. Real-time digital signal processing fundamentals, implementations and applications

    CERN Document Server

    Kuo, Sen M; Tian, Wenshun

    2013-01-01

    Combines both the DSP principles and real-time implementations and applications, and now updated with the new eZdsp USB Stick, which is very low cost, portable and widely employed at many DSP labs. Real-Time Digital Signal Processing introduces fundamental digital signal processing (DSP) principles and will be updated to include the latest DSP applications, introduce new software development tools and adjust the software design process to reflect the latest advances in the field. In the 3rd edition of the book, the key aspect of hands-on experiments will be enhanced to make the DSP principle

  16. LEOS 2002: summer electronics and signal processing symposium

    International Nuclear Information System (INIS)

    Karadzhinov, Ljupcho; Ivanovski, Zoran

    2002-01-01

    LEOS 2002 was the first Macedonian symposium on electronics and signal processing. It was organized in recognition to a growing need to exchange the research results as well as to raise competent discussions among different research groups from both academic and industrial environment in Macedonia. The topics covered in this meeting were defined by the IEEE experts as follows: Power Electronics, Industrial Electronics, Signal Processing, Image and Video Processing, Instrumentation and Measurements, Engineering in Medicine and Biology, Electron Devices and Automatic Control. Papers were mainly from Macedonia, but there was one invited lecture

  17. The study of image processing of parallel digital signal processor

    International Nuclear Information System (INIS)

    Liu Jie

    2000-01-01

    The author analyzes the basic characteristic of parallel DSP (digital signal processor) TMS320C80 and proposes related optimized image algorithm and the parallel processing method based on parallel DSP. The realtime for many image processing can be achieved in this way

  18. All-Optical Signal Processing using Silicon Devices

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Pu, Minhao; Ding, Yunhong

    2014-01-01

    This paper presents an overview of recent wo rk on the use of silicon waveguides for processing optical data signals. We will describe ultra-fast, ultra-broadband, polarisation-insensitive and phase-sensitive applications including processing of spectrally-efficient data formats and optical phase...

  19. Nonlinear Silicon Photonic Signal Processing Devices for Future Optical Networks

    Directory of Open Access Journals (Sweden)

    Cosimo Lacava

    2017-01-01

    Full Text Available In this paper, we present a review on silicon-based nonlinear devices for all optical nonlinear processing of complex telecommunication signals. We discuss some recent developments achieved by our research group, through extensive collaborations with academic partners across Europe, on optical signal processing using silicon-germanium and amorphous silicon based waveguides as well as novel materials such as silicon rich silicon nitride and tantalum pentoxide. We review the performance of four wave mixing wavelength conversion applied on complex signals such as Differential Phase Shift Keying (DPSK, Quadrature Phase Shift Keying (QPSK, 16-Quadrature Amplitude Modulation (QAM and 64-QAM that dramatically enhance the telecom signal spectral efficiency, paving the way to next generation terabit all-optical networks.

  20. Investigation of signal models and methods for evaluating structures of processing telecommunication information exchange systems under acoustic noise conditions

    Science.gov (United States)

    Kropotov, Y. A.; Belov, A. A.; Proskuryakov, A. Y.; Kolpakov, A. A.

    2018-05-01

    The paper considers models and methods for estimating signals during the transmission of information messages in telecommunication systems of audio exchange. One-dimensional probability distribution functions that can be used to isolate useful signals, and acoustic noise interference are presented. An approach to the estimation of the correlation and spectral functions of the parameters of acoustic signals is proposed, based on the parametric representation of acoustic signals and the components of the noise components. The paper suggests an approach to improving the efficiency of interference cancellation and highlighting the necessary information when processing signals from telecommunications systems. In this case, the suppression of acoustic noise is based on the methods of adaptive filtering and adaptive compensation. The work also describes the models of echo signals and the structure of subscriber devices in operational command telecommunications systems.

  1. The mathematical theory of signal processing and compression-designs

    Science.gov (United States)

    Feria, Erlan H.

    2006-05-01

    The mathematical theory of signal processing, named processor coding, will be shown to inherently arise as the computational time dual of Shannon's mathematical theory of communication which is also known as source coding. Source coding is concerned with signal source memory space compression while processor coding deals with signal processor computational time compression. Their combination is named compression-designs and referred as Conde in short. A compelling and pedagogically appealing diagram will be discussed highlighting Conde's remarkable successful application to real-world knowledge-aided (KA) airborne moving target indicator (AMTI) radar.

  2. cAMP signaling in skeletal muscle adaptation: hypertrophy, metabolism, and regeneration

    Science.gov (United States)

    Stewart, Randi

    2012-01-01

    Among organ systems, skeletal muscle is perhaps the most structurally specialized. The remarkable subcellular architecture of this tissue allows it to empower movement with instructions from motor neurons. Despite this high degree of specialization, skeletal muscle also has intrinsic signaling mechanisms that allow adaptation to long-term changes in demand and regeneration after acute damage. The second messenger adenosine 3′,5′-monophosphate (cAMP) not only elicits acute changes within myofibers during exercise but also contributes to myofiber size and metabolic phenotype in the long term. Strikingly, sustained activation of cAMP signaling leads to pronounced hypertrophic responses in skeletal myofibers through largely elusive molecular mechanisms. These pathways can promote hypertrophy and combat atrophy in animal models of disorders including muscular dystrophy, age-related atrophy, denervation injury, disuse atrophy, cancer cachexia, and sepsis. cAMP also participates in muscle development and regeneration mediated by muscle precursor cells; thus, downstream signaling pathways may potentially be harnessed to promote muscle regeneration in patients with acute damage or muscular dystrophy. In this review, we summarize studies implicating cAMP signaling in skeletal muscle adaptation. We also highlight ligands that induce cAMP signaling and downstream effectors that are promising pharmacological targets. PMID:22354781

  3. A soft-core processor architecture optimised for radar signal processing applications

    CSIR Research Space (South Africa)

    Broich, R

    2013-12-01

    Full Text Available -performance soft-core processing architecture is proposed. To develop such a processing architecture, data and signal-flow characteristics of common radar signal processing algorithms are analysed. Each algorithm is broken down into signal processing...

  4. Static Mapping of Functional Programs: An Example in Signal Processing

    Directory of Open Access Journals (Sweden)

    Jack B. Dennis

    1996-01-01

    Full Text Available Complex signal-processing problems are naturally described by compositions of program modules that process streams of data. In this article we discuss how such compositions may be analyzed and mapped onto multiprocessor computers to effectively exploit the massive parallelism of these applications. The methods are illustrated with an example of signal processing for an optical surveillance problem. Program transformation and analysis are used to construct a program description tree that represents the given computation as an acyclic interconnection of stream-processing modules. Each module may be mapped to a set of threads run on a group of processing elements of a target multiprocessor. Performance is considered for two forms of multiprocessor architecture, one based on conventional DSP technology and the other on a multithreaded-processing element design.

  5. Fractional Processes and Fractional-Order Signal Processing Techniques and Applications

    CERN Document Server

    Sheng, Hu; Qiu, TianShuang

    2012-01-01

    Fractional processes are widely found in science, technology and engineering systems. In Fractional Processes and Fractional-order Signal Processing, some complex random signals, characterized by the presence of a heavy-tailed distribution or non-negligible dependence between distant observations (local and long memory), are introduced and examined from the ‘fractional’ perspective using simulation, fractional-order modeling and filtering and realization of fractional-order systems. These fractional-order signal processing (FOSP) techniques are based on fractional calculus, the fractional Fourier transform and fractional lower-order moments. Fractional Processes and Fractional-order Signal Processing: • presents fractional processes of fixed, variable and distributed order studied as the output of fractional-order differential systems; • introduces FOSP techniques and the fractional signals and fractional systems point of view; • details real-world-application examples of FOSP techniques to demonstr...

  6. An adaptive synchronization strategy based on active control for demodulating message hidden in chaotic signals

    International Nuclear Information System (INIS)

    Tang Fang

    2008-01-01

    In the field of secure communication, it is very important to demodulate the message hidden in chaotic signals. In this paper, an adaptive synchronization strategy based on active control is proposed, which is used to design an active controller and an appropriate adaptive demodulator at the receiver to recover the transmitted message hidden in chaotic signals of a drive system. Based on Lyapunov stability theory, it is shown that the transmitted message can be theoretically recovered by using the proposed strategy. Numerical simulations based on the Chua's circuit are also presented to verify the effectiveness of the proposed strategy. In addition, it is shown via simulations that, by increasing the gain of the active controller the message error caused by the external noise and the discontinuous property of the message can be reduced

  7. Domain requirements for the Dock adapter protein in growth- cone signaling.

    Science.gov (United States)

    Rao, Y; Zipursky, S L

    1998-03-03

    Tyrosine phosphorylation has been implicated in growth-cone guidance through genetic, biochemical, and pharmacological studies. Adapter proteins containing src homology 2 (SH2) domains and src homology 3 (SH3) domains provide a means of linking guidance signaling through phosphotyrosine to downstream effectors regulating growth-cone motility. The Drosophila adapter, Dreadlocks (Dock), the homolog of mammalian Nck containing three N-terminal SH3 domains and a single SH2 domain, is highly specialized for growth-cone guidance. In this paper, we demonstrate that Dock can couple signals in either an SH2-dependent or an SH2-independent fashion in photoreceptor (R cell) growth cones, and that Dock displays different domain requirements in different neurons.

  8. Multi-Model Adaptive Fuzzy Controller for a CSTR Process

    Directory of Open Access Journals (Sweden)

    Shubham Gogoria

    2015-09-01

    Full Text Available Continuous Stirred Tank Reactors are intensively used to control exothermic reactions in chemical industries. It is a very complex multi-variable system with non-linear characteristics. This paper deals with linearization of the mathematical model of a CSTR Process. Multi model adaptive fuzzy controller has been designed to control the reactor concentration and temperature of CSTR process. This method combines the output of multiple Fuzzy controllers, which are operated at various operating points. The proposed solution is a straightforward implementation of Fuzzy controller with gain scheduler to control the linearly inseparable parameters of a highly non-linear process.

  9. Application of optical processing to adaptive phased array radar

    Science.gov (United States)

    Carroll, C. W.; Vijaya Kumar, B. V. K.

    1988-01-01

    The results of the investigation of the applicability of optical processing to Adaptive Phased Array Radar (APAR) data processing will be summarized. Subjects that are covered include: (1) new iterative Fourier transform based technique to determine the array antenna weight vector such that the resulting antenna pattern has nulls at desired locations; (2) obtaining the solution of the optimal Wiener weight vector by both iterative and direct methods on two laboratory Optical Linear Algebra Processing (OLAP) systems; and (3) an investigation of the effects of errors present in OLAP systems on the solution vectors.

  10. 2015 International Conference on Machine Learning and Signal Processing

    CERN Document Server

    Woo, Wai; Sulaiman, Hamzah; Othman, Mohd; Saat, Mohd

    2016-01-01

    This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15–17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learni...

  11. Detectors and signal processing for high-energy physics

    International Nuclear Information System (INIS)

    Rehak, P.

    1981-01-01

    Basic principles of the particle detection and signal processing for high-energy physics experiments are presented. It is shown that the optimum performance of a properly designed detector system is not limited by incidental imperfections, but solely by more fundamental limitations imposed by the quantum nature and statistical behavior of matter. The noise sources connected with the detection and signal processing are studied. The concepts of optimal filtering and optimal detector/amplifying device matching are introduced. Signal processing for a liquid argon calorimeter is analyzed in some detail. The position detection in gas counters is studied. Resolution in drift chambers for the drift coordinate measurement as well as the second coordinate measurement is discussed

  12. Digital signal processing for wireless communication using Matlab

    CERN Document Server

    Gopi, E S

    2016-01-01

    This book examines signal processing techniques used in wireless communication illustrated by using the Matlab program. The author discusses these techniques as they relate to Doppler spread; delay spread; Rayleigh and Rician channel modeling; rake receiver; diversity techniques; MIMO and OFDM -based transmission techniques; and array signal processing. Related topics such as detection theory, link budget, multiple access techniques, and spread spectrum are also covered.   ·         Illustrates signal processing techniques involved in wireless communication using Matlab ·         Discusses multiple access techniques such as Frequency division multiple access, Time division multiple access, and Code division multiple access ·         Covers band pass modulation techniques such as Binary phase shift keying, Differential phase shift keying, Quadrature phase shift keying, Binary frequency shift keying, Minimum shift keying, and Gaussian minimum shift keying.

  13. Frames and operator theory in analysis and signal processing

    CERN Document Server

    Larson, David R; Nashed, Zuhair; Nguyen, Minh Chuong; Papadakis, Manos

    2008-01-01

    This volume contains articles based on talks presented at the Special Session Frames and Operator Theory in Analysis and Signal Processing, held in San Antonio, Texas, in January of 2006. Recently, the field of frames has undergone tremendous advancement. Most of the work in this field is focused on the design and construction of more versatile frames and frames tailored towards specific applications, e.g., finite dimensional uniform frames for cellular communication. In addition, frames are now becoming a hot topic in mathematical research as a part of many engineering applications, e.g., matching pursuits and greedy algorithms for image and signal processing. Topics covered in this book include: Application of several branches of analysis (e.g., PDEs; Fourier, wavelet, and harmonic analysis; transform techniques; data representations) to industrial and engineering problems, specifically image and signal processing. Theoretical and applied aspects of frames and wavelets. Pure aspects of operator theory empha...

  14. Digital signal processing for He3 proportional counter

    International Nuclear Information System (INIS)

    Ahmadov, Q.S.; Institute of Radiation Problems, ANAS, Baku

    2011-01-01

    Full text: Data acquisition systems for nuclear spectroscopy have traditionally been based on systems with analog shaping amplifiers followed by analog-to-digital converters. Recently, however, new systems based on digital signal processing allow us to replace the analog shaping and timing circuitry the numerical algorithms to derive properties of the pulse such as its amplitude. DSP is a fully numerical analysis of the detector pulse signals and this technique demonstrates significant advantages over analog systems in some circumstances. From a mathematical point of view, one can consider the signal evolution from the detector to the ADC as a sequence of transformations that can be described by precisely defined mathematical expressions.Digital signal processing with ADCs has the possibility to utilize further information on the signal pulses from radiation detectors [1] [2]. In the experiment each step of the signal generation in the 3He filled proportional counter was described using digital signal processing techniques (DSP). The electronic system has consisted of a detector, a preamplifier and a digital oscilloscope. The pulses from the detector were digitized using a OTSZS-02 (250USB)-4 digital storage oscilloscope from ZAO R UDNEV-SHILYAYEV . This oscilloscope allowed signal digitization with accuracy of 8 bit(256 levels) and with frequency of up to 5.10''8 samples/s. As a neutron source was used Cf-252.To obtain detector output current pulse I(t) created by the motions of the ions/electrons pairs was written an algorithm which can easily be programmed using modern computer programming languages

  15. Digital signal processing algorithms for nuclear particle spectroscopy

    International Nuclear Information System (INIS)

    Zejnalova, O.; Zejnalov, Sh.; Hambsch, F.J.; Oberstedt, S.

    2007-01-01

    Digital signal processing algorithms for nuclear particle spectroscopy are described along with a digital pile-up elimination method applicable to equidistantly sampled detector signals pre-processed by a charge-sensitive preamplifier. The signal processing algorithms are provided as recursive one- or multi-step procedures which can be easily programmed using modern computer programming languages. The influence of the number of bits of the sampling analogue-to-digital converter on the final signal-to-noise ratio of the spectrometer is considered. Algorithms for a digital shaping-filter amplifier, for a digital pile-up elimination scheme and for ballistic deficit correction were investigated using a high purity germanium detector. The pile-up elimination method was originally developed for fission fragment spectroscopy using a Frisch-grid back-to-back double ionization chamber and was mainly intended for pile-up elimination in case of high alpha-radioactivity of the fissile target. The developed pile-up elimination method affects only the electronic noise generated by the preamplifier. Therefore the influence of the pile-up elimination scheme on the final resolution of the spectrometer is investigated in terms of the distance between pile-up pulses. The efficiency of the developed algorithms is compared with other signal processing schemes published in literature

  16. Single photon laser altimeter simulator and statistical signal processing

    Science.gov (United States)

    Vacek, Michael; Prochazka, Ivan

    2013-05-01

    Spaceborne altimeters are common instruments onboard the deep space rendezvous spacecrafts. They provide range and topographic measurements critical in spacecraft navigation. Simultaneously, the receiver part may be utilized for Earth-to-satellite link, one way time transfer, and precise optical radiometry. The main advantage of single photon counting approach is the ability of processing signals with very low signal-to-noise ratio eliminating the need of large telescopes and high power laser source. Extremely small, rugged and compact microchip lasers can be employed. The major limiting factor, on the other hand, is the acquisition time needed to gather sufficient volume of data in repetitive measurements in order to process and evaluate the data appropriately. Statistical signal processing is adopted to detect signals with average strength much lower than one photon per measurement. A comprehensive simulator design and range signal processing algorithm are presented to identify a mission specific altimeter configuration. Typical mission scenarios (celestial body surface landing and topographical mapping) are simulated and evaluated. The high interest and promising single photon altimeter applications are low-orbit (˜10 km) and low-radial velocity (several m/s) topographical mapping (asteroids, Phobos and Deimos) and landing altimetry (˜10 km) where range evaluation repetition rates of ˜100 Hz and 0.1 m precision may be achieved. Moon landing and asteroid Itokawa topographical mapping scenario simulations are discussed in more detail.

  17. An implementation of signal processing algorithms for ultrasonic NDE

    International Nuclear Information System (INIS)

    Ericsson, L.; Stepinski, T.

    1994-01-01

    Probability of detection flaws during ultrasonic pulse-echo inspection is often limited by the presence of backscattered echoes from the material structure. A digital signal processing technique for removal of this material noise, referred to as split spectrum processing (SSP), has been developed and verified using laboratory experiments during the last decade. The authors have performed recently a limited scale evaluation of various SSP techniques for ultrasonic signals acquired during the inspection of welds in austenitic steel. They have obtained very encouraging results that indicate promising capabilities of the SSP for inspection of nuclear power plants. Thus, a more extensive investigation of the technique using large amounts of ultrasonic data is motivated. This analysis should employ different combinations of materials, flaws and transducers. Due to the considerable number of ultrasonic signals required to verify the technique for future practical use, a custom-made computer software is necessary. At the request of the Swedish nuclear power industry the authors have developed such a program package. The program provides a user-friendly graphical interface and is intended for processing of B-scan data in a flexible way. Assembled in the program are a number of signal processing algorithms including traditional Split Spectrum Processing and the more recent Cut Spectrum Processing algorithm developed by them. The program and some results obtained using the various algorithms are presented in the paper

  18. Independent AMP and NAD signaling regulates C2C12 differentiation and metabolic adaptation.

    Science.gov (United States)

    Hsu, Chia George; Burkholder, Thomas J

    2016-12-01

    The balance of ATP production and consumption is reflected in adenosine monophosphate (AMP) and nicotinamide adenine dinucleotide (NAD) content and has been associated with phenotypic plasticity in striated muscle. Some studies have suggested that AMPK-dependent plasticity may be an indirect consequence of increased NAD synthesis and SIRT1 activity. The primary goal of this study was to assess the interaction of AMP- and NAD-dependent signaling in adaptation of C2C12 myotubes. Changes in myotube developmental and metabolic gene expression were compared following incubation with 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) and nicotinamide mononucleotide (NMN) to activate AMPK- and NAD-related signaling. AICAR showed no effect on NAD pool or nampt expression but significantly reduced histone H3 acetylation and GLUT1, cytochrome C oxidase subunit 2 (COX2), and MYH3 expression. In contrast, NMN supplementation for 24 h increased NAD pool by 45 % but did not reduce histone H3 acetylation nor promote mitochondrial gene expression. The combination of AMP and NAD signaling did not induce further metabolic adaptation, but NMN ameliorated AICAR-induced myotube reduction. We interpret these results as indication that AMP and NAD contribute to C2C12 differentiation and metabolic adaptation independently.

  19. Ultrasonic signal processing for sizing under-clad flaws

    International Nuclear Information System (INIS)

    Shankar, R.; Paradiso, T.J.; Lane, S.S.; Quinn, J.R.

    1985-01-01

    Ultrasonic digital data were collected from underclad cracks in sample pressure vessel specimen blocks. These blocks were weld cladded under different processes to simulate actual conditions in US Pressure Water Reactors. Each crack was represented by a flaw-echo dynamic curve which is a plot of the transducer motion on the surface as a function of the ultrasonic response into the material. Crack depth sizing was performed by identifying in the dynamic curve the crack tip diffraction signals from the upper and lower tips. This paper describes the experimental procedure, digital signal processing methods used and algorithms developed for crack depth sizing

  20. Structural health monitoring an advanced signal processing perspective

    CERN Document Server

    Chen, Xuefeng; Mukhopadhyay, Subhas

    2017-01-01

    This book highlights the latest advances and trends in advanced signal processing (such as wavelet theory, time-frequency analysis, empirical mode decomposition, compressive sensing and sparse representation, and stochastic resonance) for structural health monitoring (SHM). Its primary focus is on the utilization of advanced signal processing techniques to help monitor the health status of critical structures and machines encountered in our daily lives: wind turbines, gas turbines, machine tools, etc. As such, it offers a key reference guide for researchers, graduate students, and industry professionals who work in the field of SHM.

  1. Optical signal acquisition and processing in future accelerator diagnostics

    International Nuclear Information System (INIS)

    Jackson, G.P.; Elliott, A.

    1992-01-01

    Beam detectors such as striplines and wall current monitors rely on matched electrical networks to transmit and process beam information. Frequency bandwidth, noise immunity, reflections, and signal to noise ratio are considerations that require compromises limiting the quality of the measurement. Recent advances in fiber optics related technologies have made it possible to acquire and process beam signals in the optical domain. This paper describes recent developments in the application of these technologies to accelerator beam diagnostics. The design and construction of an optical notch filter used for a stochastic cooling system is used as an example. Conceptual ideas for future beam detectors are also presented

  2. PC add on card for processing of LSC signals

    International Nuclear Information System (INIS)

    Jadhav, S.R.; Nikhare, D.M.; Gurna, R.K.; Paulson, Molly; Kulkarni, C.P.; Vaidya, P.P.

    2001-01-01

    This paper describes PC- add on card developed at Electronics Division for processing of LSC signals. This card uses highly integrated digital and analog circuits, for entire processing of signals available from preamplifiers to get complete beta energy spectrum corresponding to coincident events in Liquid Scintillation Counting. LSC card along with High Voltage PC-add on card gives complete electronics required for LSC system. This card is also used in automatic LSC system along with interface circuits, which are used to control mechanical movements. (author)

  3. Adoption: biological and social processes linked to adaptation.

    Science.gov (United States)

    Grotevant, Harold D; McDermott, Jennifer M

    2014-01-01

    Children join adoptive families through domestic adoption from the public child welfare system, infant adoption through private agencies, and international adoption. Each pathway presents distinctive developmental opportunities and challenges. Adopted children are at higher risk than the general population for problems with adaptation, especially externalizing, internalizing, and attention problems. This review moves beyond the field's emphasis on adoptee-nonadoptee differences to highlight biological and social processes that affect adaptation of adoptees across time. The experience of stress, whether prenatal, postnatal/preadoption, or during the adoption transition, can have significant impacts on the developing neuroendocrine system. These effects can contribute to problems with physical growth, brain development, and sleep, activating cascading effects on social, emotional, and cognitive development. Family processes involving contact between adoptive and birth family members, co-parenting in gay and lesbian adoptive families, and racial socialization in transracially adoptive families affect social development of adopted children into adulthood.

  4. Processing of seismic signals from a seismometer network

    International Nuclear Information System (INIS)

    Key, F.A.; Warburton, P.J.

    1983-08-01

    A description is given of the Seismometer Network Analysis Computer (SNAC) which processes short period data from a network of seismometers (UKNET). The nine stations of the network are distributed throughout the UK and their outputs are transmitted to a control laboratory (Blacknest) where SNAC monitors the data for seismic signals. The computer gives an estimate of the source location of the detected signals and stores the waveforms. The detection logic is designed to maintain high sensitivity without excessive ''false alarms''. It is demonstrated that the system is able to detect seismic signals at an amplitude level consistent with a network of single stations and, within the limitations of signal onset time measurements made by machine, can locate the source of the seismic disturbance. (author)

  5. Crosstalk between Wnt Signaling and RNA Processing in Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Michael Bordonaro

    2013-01-01

    Full Text Available RNA processing involves a variety of processes affecting gene expression, including the removal of introns through RNA splicing, as well as 3' end processing (cleavage and polyadenylation. Alternative RNA processing is fundamentally important for gene regulation, and aberrant processing is associated with the initiation and progression of cancer. Deregulated Wnt signaling, which is the initiating event in the development of most cases of human colorectal cancer (CRC, has been linked to modified RNA processing, which may contribute to Wnt-mediated colonic carcinogenesis. Crosstalk between Wnt signaling and alternative RNA splicing with relevance to CRC includes effects on the expression of Rac1b, an alternatively spliced gene associated with tumorigenesis, which exhibits alternative RNA splicing that is influenced by Wnt activity. In addition, Tcf4, a crucial component of Wnt signaling, also exhibits alternative splicing, which is likely involved in colonic tumorigenesis. Modulation of 3' end formation, including of the Wnt target gene COX-2, also can influence the neoplastic process, with implications for CRC. While many human genes are dependent on introns and splicing for normal levels of gene expression, naturally intronless genes exist with a unique metabolism that allows for intron-independent gene expression. Effects of Wnt activity on the RNA metabolism of the intronless Wnt-target gene c-jun is a likely contributor to cancer development. Further, butyrate, a breakdown product of dietary fiber and a histone deacetylase inhibitor, upregulates Wnt activity in CRC cells, and also modulates RNA processing; therefore, the interplay between Wnt activity, the modulation of this activity by butyrate, and differential RNA metabolism in colonic cells can significantly influence tumorigenesis. Determining the role played by altered RNA processing in Wnt-mediated neoplasia may lead to novel interventions aimed at restoring normal RNA metabolism for

  6. Crosstalk between Wnt Signaling and RNA Processing in Colorectal Cancer.

    Science.gov (United States)

    Bordonaro, Michael

    2013-01-01

    RNA processing involves a variety of processes affecting gene expression, including the removal of introns through RNA splicing, as well as 3' end processing (cleavage and polyadenylation). Alternative RNA processing is fundamentally important for gene regulation, and aberrant processing is associated with the initiation and progression of cancer. Deregulated Wnt signaling, which is the initiating event in the development of most cases of human colorectal cancer (CRC), has been linked to modified RNA processing, which may contribute to Wnt-mediated colonic carcinogenesis. Crosstalk between Wnt signaling and alternative RNA splicing with relevance to CRC includes effects on the expression of Rac1b, an alternatively spliced gene associated with tumorigenesis, which exhibits alternative RNA splicing that is influenced by Wnt activity. In addition, Tcf4, a crucial component of Wnt signaling, also exhibits alternative splicing, which is likely involved in colonic tumorigenesis. Modulation of 3' end formation, including of the Wnt target gene COX-2, also can influence the neoplastic process, with implications for CRC. While many human genes are dependent on introns and splicing for normal levels of gene expression, naturally intronless genes exist with a unique metabolism that allows for intron-independent gene expression. Effects of Wnt activity on the RNA metabolism of the intronless Wnt-target gene c-jun is a likely contributor to cancer development. Further, butyrate, a breakdown product of dietary fiber and a histone deacetylase inhibitor, upregulates Wnt activity in CRC cells, and also modulates RNA processing; therefore, the interplay between Wnt activity, the modulation of this activity by butyrate, and differential RNA metabolism in colonic cells can significantly influence tumorigenesis. Determining the role played by altered RNA processing in Wnt-mediated neoplasia may lead to novel interventions aimed at restoring normal RNA metabolism for therapeutic benefit

  7. Biomechanical signals guiding stem cell cartilage engineering: from molecular adaption to tissue functionality

    Directory of Open Access Journals (Sweden)

    Y Zhang

    2016-01-01

    Full Text Available In vivo cartilage is in a state of constant mechanical stimulation. It is therefore reasonable to deduce that mechanical forces play an important role in cartilage formation. Mechanical forces, such as compression, tension, and shear force, have been widely applied for cartilage engineering; however, relatively few review papers have summarized the influence of biomechanical signals on stem cell-based neo-cartilage formation and cartilage engineering in both molecular adaption and tissue functionality. In this review, we will discuss recent progress related to the influences of substrate elasticity on stem cell chondrogenic differentiation and elucidate the potential underlying mechanisms. Aside from active sensing and responding to the extracellular environment, stem cells also could respond to various external mechanical forces, which also influence their chondrogenic capacity; this topic will be updated along with associated signaling pathways. We expect that these different regimens of biomechanical signals can be utilized to boost stem cell-based cartilage engineering and regeneration.

  8. An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification.

    Science.gov (United States)

    Li, Fangmin; Yang, Chao; Xia, Yuqing; Ma, Xiaolin; Zhang, Tao; Zhou, Zhou

    2017-11-29

    In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

  9. An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification

    Directory of Open Access Journals (Sweden)

    Fangmin Li

    2017-11-01

    Full Text Available In this paper, we propose the multiwindow Adaptive S-method (AS-method distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

  10. Robust adaptive multichannel SAR processing based on covariance matrix reconstruction

    Science.gov (United States)

    Tan, Zhen-ya; He, Feng

    2018-04-01

    With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.

  11. Signal Processing Device (SPD) for networked radiation monitoring system

    International Nuclear Information System (INIS)

    Dharmapurikar, A.; Bhattacharya, S.; Mukhopadhyay, P.K.; Sawhney, A.; Patil, R.K.

    2010-01-01

    A networked radiation and parameter monitoring system with three tier architecture is being developed. Signal Processing Device (SPD) is a second level sub-system node in the network. SPD is an embedded system which has multiple input channels and output communication interfaces. It acquires and processes data from first level parametric sensor devices, and sends to third level devices in response to request commands received from host. It also performs scheduled diagnostic operations and passes on the information to host. It supports inputs in the form of differential digital signals and analog voltage signals. SPD communicates with higher level devices over RS232/RS422/USB channels. The system has been designed with main requirements of minimal power consumption and harsh environment in radioactive plants. This paper discusses the hardware and software design details of SPD. (author)

  12. Smart signal processing for an evolving electric grid

    Science.gov (United States)

    Silva, Leandro Rodrigues Manso; Duque, Calos Augusto; Ribeiro, Paulo F.

    2015-12-01

    Electric grids are interconnected complex systems consisting of generation, transmission, distribution, and active loads, recently called prosumers as they produce and consume electric energy. Additionally, these encompass a vast array of equipment such as machines, power transformers, capacitor banks, power electronic devices, motors, etc. that are continuously evolving in their demand characteristics. Given these conditions, signal processing is becoming an essential assessment tool to enable the engineer and researcher to understand, plan, design, and operate the complex and smart electronic grid of the future. This paper focuses on recent developments associated with signal processing applied to power system analysis in terms of characterization and diagnostics. The following techniques are reviewed and their characteristics and applications discussed: active power system monitoring, sparse representation of power system signal, real-time resampling, and time-frequency (i.e., wavelets) applied to power fluctuations.

  13. Signal processing for non-destructive testing of railway tracks

    Science.gov (United States)

    Heckel, Thomas; Casperson, Ralf; Rühe, Sven; Mook, Gerhard

    2018-04-01

    Increased speed, heavier loads, altered material and modern drive systems result in an increasing number of rail flaws. The appearance of these flaws also changes continually due to the rapid change in damage mechanisms of modern rolling stock. Hence, interpretation has become difficult when evaluating non-destructive rail testing results. Due to the changed interplay between detection methods and flaws, the recorded signals may result in unclassified types of rail flaws. Methods for automatic rail inspection (according to defect detection and classification) undergo continual development. Signal processing is a key technology to master the challenge of classification and maintain resolution and detection quality, independent of operation speed. The basic ideas of signal processing, based on the Glassy-Rail-Diagram for classification purposes, are presented herein. Examples for the detection of damages caused by rolling contact fatigue also are given, and synergetic effects of combined evaluation of diverse inspection methods are shown.

  14. Myoelectric signal processing for control of powered limb prostheses.

    Science.gov (United States)

    Parker, P; Englehart, K; Hudgins, B

    2006-12-01

    Progress in myoelectric control technology has over the years been incremental, due in part to the alternating focus of the R&D between control methodology and device hardware. The technology has over the past 50 years or so moved from single muscle control of a single prosthesis function to muscle group activity control of multifunction prostheses. Central to these changes have been developments in the means of extracting information from the myoelectric signal. This paper gives an overview of the myoelectric signal processing challenge, a brief look at the challenge from an historical perspective, the state-of-the-art in myoelectric signal processing for prosthesis control, and an indication of where this field is heading. The paper demonstrates that considerable progress has been made in providing clients with useful and reliable myoelectric communication channels, and that exciting work and developments are on the horizon.

  15. Total focusing method with correlation processing of antenna array signals

    Science.gov (United States)

    Kozhemyak, O. A.; Bortalevich, S. I.; Loginov, E. L.; Shinyakov, Y. A.; Sukhorukov, M. P.

    2018-03-01

    The article proposes a method of preliminary correlation processing of a complete set of antenna array signals used in the image reconstruction algorithm. The results of experimental studies of 3D reconstruction of various reflectors using and without correlation processing are presented in the article. Software ‘IDealSystem3D’ by IDeal-Technologies was used for experiments. Copper wires of different diameters located in a water bath were used as a reflector. The use of correlation processing makes it possible to obtain more accurate reconstruction of the image of the reflectors and to increase the signal-to-noise ratio. The experimental results were processed using an original program. This program allows varying the parameters of the antenna array and sampling frequency.

  16. Guidelines for Affective Signal Processing (ASP): From lab to life

    NARCIS (Netherlands)

    van den Broek, Egon; Janssen, Joris H.; Westerink, Joyce H.D.M.; Cohn, J.; Nijholt, Antinus; Pantic, Maja

    2009-01-01

    This article presents the rationale behind ACII2009’s special session: Guidelines for Affective Signal Processing (ASP): From lab to life. Although affect is embraced by both science and engineering, its recognition has not reached a satisfying level. Through a concise overview of ASP and the

  17. Fast optical signal processing in high bit rate OTDM systems

    DEFF Research Database (Denmark)

    Poulsen, Henrik Nørskov; Jepsen, Kim Stokholm; Clausen, Anders

    1998-01-01

    As all-optical signal processing is maturing, optical time division multiplexing (OTDM) has also gained interest for simple networking in high capacity backbone networks. As an example of a network scenario we show an OTDM bus interconnecting another OTDM bus, a single high capacity user...

  18. Foundations of digital signal processing theory, algorithms and hardware design

    CERN Document Server

    Gaydecki, Patrick

    2005-01-01

    An excellent introductory text, this book covers the basic theoretical, algorithmic and real-time aspects of digital signal processing (DSP). Detailed information is provided on off-line, real-time and DSP programming and the reader is effortlessly guided through advanced topics such as DSP hardware design, FIR and IIR filter design and difference equation manipulation.

  19. A practicable signal processing algorithm for industrial nuclear instrument

    International Nuclear Information System (INIS)

    Tang Yaogeng; Gao Song; Yang Wujiao

    2006-01-01

    In order to reduce the statistical error and to improve dynamic performances of the industrial nuclear instrument, a practicable method of nuclear measurement signal processing is developed according to industrial nuclear measurement features. The algorithm designed is implemented with a single-chip microcomputer. The results of application in (radiation level gauge has proved the effectiveness of this method). (authors)

  20. Tutorial: Signal Processing in Brain-Computer Interfaces

    NARCIS (Netherlands)

    Garcia Molina, G.

    2010-01-01

    Research in Electroencephalogram (EEG) based Brain-Computer Interfaces (BCIs) has been considerably expanding during the last few years. Such an expansion owes to a large extent to the multidisciplinary and challenging nature of BCI research. Signal processing undoubtedly constitutes an essential

  1. Programming signal processing applications on heterogeneous wireless sensor platforms

    NARCIS (Netherlands)

    Buondonno, L.; Fortino, G.; Galzarano, S.; Giannantonio, R.; Giordano, A.; Gravina, R.; Guerrieri, A.

    2009-01-01

    This paper proposes the SPINE frameworks (SPINE1.x and SPINE2) for the programming of signal processing applications on heterogeneous wireless sensor platforms. In particular, two integrable approaches based on the proposed frameworks are described that allow to develop applications for wireless

  2. Some recent work on lattice structures for digital signal processing

    Indian Academy of Sciences (India)

    Digital signal processing (DSP); lattice structures; finite impulse ... fascinated this author for a long time, and for the known non-canonical ...... where M

  3. Multiplexing and data processing of in-core signals

    International Nuclear Information System (INIS)

    Meyer, M.

    1983-01-01

    The application of multiplexing and signal processing techniques used for reactor operation and utilisation of data from the in-core instrumentation system is described. After a brief recall about in-core instrumentation, the aims, the advantages of multiplexing are presented. One of the aims of this realization is to show the compatibity between the technologies used with a PWR environment [fr

  4. Nonlinear signal processing for ultrasonic imaging of material complexity

    Czech Academy of Sciences Publication Activity Database

    Dos Santos, S.; Vejvodová, Šárka; Převorovský, Zdeněk

    2010-01-01

    Roč. 59, č. 2 (2010), s. 108-117 ISSN 1736-6046 Institutional research plan: CEZ:AV0Z20760514 Keywords : nonlinear signal processing * TR-NEWS * symmetry analysis * DORT Subject RIV: BI - Acoustics Impact factor: 0.464, year: 2010 www.eap.ee/proceedings

  5. Signal processing in an acousto-optical spectral colorimeter

    Science.gov (United States)

    Emeljanov, Sergey P.; Kludzin, Victor V.; Kochin, Leonid B.; Medvedev, Sergey V.; Polosin, Lev L.; Sokolov, Vladimir K.

    2002-02-01

    The algorithms of spectrometer signals processing in the acousto-optical spectral colorimeter, proposed earlier are discussed. This processing is directional on distortion elimination of an optical system spectral characteristics and photoelectric transformations, and also for calculation of tristimulus coefficients X,Y,Z in an international colorimetric system of a CIE - 31 and transformation them in coordinates of recommended CIE uniform contrast systems LUV and LAB.

  6. Adaptive processes drive ecomorphological convergent evolution in antwrens (Thamnophilidae).

    Science.gov (United States)

    Bravo, Gustavo A; Remsen, J V; Brumfield, Robb T

    2014-10-01

    Phylogenetic niche conservatism (PNC) and convergence are contrasting evolutionary patterns that describe phenotypic similarity across independent lineages. Assessing whether and how adaptive processes give origin to these patterns represent a fundamental step toward understanding phenotypic evolution. Phylogenetic model-based approaches offer the opportunity not only to distinguish between PNC and convergence, but also to determine the extent that adaptive processes explain phenotypic similarity. The Myrmotherula complex in the Neotropical family Thamnophilidae is a polyphyletic group of sexually dimorphic small insectivorous forest birds that are relatively homogeneous in size and shape. Here, we integrate a comprehensive species-level molecular phylogeny of the Myrmotherula complex with morphometric and ecological data within a comparative framework to test whether phenotypic similarity is described by a pattern of PNC or convergence, and to identify evolutionary mechanisms underlying body size and shape evolution. We show that antwrens in the Myrmotherula complex represent distantly related clades that exhibit adaptive convergent evolution in body size and divergent evolution in body shape. Phenotypic similarity in the group is primarily driven by their tendency to converge toward smaller body sizes. Differences in body size and shape across lineages are associated to ecological and behavioral factors. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

  7. Adaptive Dynamic Process Scheduling on Distributed Memory Parallel Computers

    Directory of Open Access Journals (Sweden)

    Wei Shu

    1994-01-01

    Full Text Available One of the challenges in programming distributed memory parallel machines is deciding how to allocate work to processors. This problem is particularly important for computations with unpredictable dynamic behaviors or irregular structures. We present a scheme for dynamic scheduling of medium-grained processes that is useful in this context. The adaptive contracting within neighborhood (ACWN is a dynamic, distributed, load-dependent, and scalable scheme. It deals with dynamic and unpredictable creation of processes and adapts to different systems. The scheme is described and contrasted with two other schemes that have been proposed in this context, namely the randomized allocation and the gradient model. The performance of the three schemes on an Intel iPSC/2 hypercube is presented and analyzed. The experimental results show that even though the ACWN algorithm incurs somewhat larger overhead than the randomized allocation, it achieves better performance in most cases due to its adaptiveness. Its feature of quickly spreading the work helps it outperform the gradient model in performance and scalability.

  8. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

    International Nuclear Information System (INIS)

    Chao, Ming; Yuan, Yading; Rosenzweig, Kenneth E; Lo, Yeh-Chi; Wei, Jie; Li, Tianfang

    2016-01-01

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as  −0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients. (paper)

  9. Adaptation to conflict via context-driven anticipatory signals in the dorsomedial prefrontal cortex.

    Science.gov (United States)

    Horga, Guillermo; Maia, Tiago V; Wang, Pengwei; Wang, Zhishun; Marsh, Rachel; Peterson, Bradley S

    2011-11-09

    Behavioral interference elicited by competing response tendencies adapts to contextual changes. Recent nonhuman primate research suggests a key mnemonic role of distinct prefrontal cells in supporting such context-driven behavioral adjustments by maintaining conflict information across trials, but corresponding prefrontal functions have yet to be probed in humans. Using event-related functional magnetic resonance imaging, we investigated the human neural substrates of contextual adaptations to conflict. We found that a neural system comprising the rostral dorsomedial prefrontal cortex and portions of the dorsolateral prefrontal cortex specifically encodes the history of previously experienced conflict and influences subsequent adaptation to conflict on a trial-by-trial basis. This neural system became active in anticipation of stimulus onsets during preparatory periods and interacted with a second neural system engaged during the processing of conflict. Our findings suggest that a dynamic interaction between a system that represents conflict history and a system that resolves conflict underlies the contextual adaptation to conflict.

  10. Brain-computer interface signal processing at the Wadsworth Center: mu and sensorimotor beta rhythms.

    Science.gov (United States)

    McFarland, Dennis J; Krusienski, Dean J; Wolpaw, Jonathan R

    2006-01-01

    The Wadsworth brain-computer interface (BCI), based on mu and beta sensorimotor rhythms, uses one- and two-dimensional cursor movement tasks and relies on user training. This is a real-time closed-loop system. Signal processing consists of channel selection, spatial filtering, and spectral analysis. Feature translation uses a regression approach and normalization. Adaptation occurs at several points in this process on the basis of different criteria and methods. It can use either feedforward (e.g., estimating the signal mean for normalization) or feedback control (e.g., estimating feature weights for the prediction equation). We view this process as the interaction between a dynamic user and a dynamic system that coadapt over time. Understanding the dynamics of this interaction and optimizing its performance represent a major challenge for BCI research.

  11. Multi-factor models and signal processing techniques application to quantitative finance

    CERN Document Server

    Darolles, Serges; Jay, Emmanuelle

    2013-01-01

    With recent outbreaks of multiple large-scale financial crises, amplified by interconnected risk sources, a new paradigm of fund management has emerged. This new paradigm leverages "embedded" quantitative processes and methods to provide more transparent, adaptive, reliable and easily implemented "risk assessment-based" practices.This book surveys the most widely used factor models employed within the field of financial asset pricing. Through the concrete application of evaluating risks in the hedge fund industry, the authors demonstrate that signal processing techniques are an intere

  12. Generation and coherent detection of QPSK signal using a novel method of digital signal processing

    Science.gov (United States)

    Zhao, Yuan; Hu, Bingliang; He, Zhen-An; Xie, Wenjia; Gao, Xiaohui

    2018-02-01

    We demonstrate an optical quadrature phase-shift keying (QPSK) signal transmitter and an optical receiver for demodulating optical QPSK signal with homodyne detection and digital signal processing (DSP). DSP on the homodyne detection scheme is employed without locking the phase of the local oscillator (LO). In this paper, we present an extracting one-dimensional array of down-sampling method for reducing unwanted samples of constellation diagram measurement. Such a novel scheme embodies the following major advantages over the other conventional optical QPSK signal detection methods. First, this homodyne detection scheme does not need strict requirement on LO in comparison with linear optical sampling, such as having a flat spectral density and phase over the spectral support of the source under test. Second, the LabVIEW software is directly used for recovering the QPSK signal constellation without employing complex DSP circuit. Third, this scheme is applicable to multilevel modulation formats such as M-ary PSK and quadrature amplitude modulation (QAM) or higher speed signals by making minor changes.

  13. Linear and Nonlinear Impairment Compensation in Coherent Optical Transmission with Digital Signal Processing

    DEFF Research Database (Denmark)

    Porto da Silva, Edson

    Digital signal processing (DSP) has become one of the main enabling technologies for the physical layer of coherent optical communication networks. The DSP subsystems are used to implement several functionalities in the digital domain, from synchronization to channel equalization. Flexibility...... nonlinearity compensation, (II) spectral shaping, and (III) adaptive equalization. For (I), original contributions are presented to the study of the nonlinearity compensation (NLC) with digital backpropagation (DBP). Numerical and experimental performance investigations are shown for different application...... scenarios. Concerning (II), it is demonstrated how optical and electrical (digital) pulse shaping can be allied to improve the spectral confinement of a particular class of optical time-division multiplexing (OTDM) signals that can be used as a building block for fast signaling single-carrier transceivers...

  14. Algorithm-Architecture Matching for Signal and Image Processing

    CERN Document Server

    Gogniat, Guy; Morawiec, Adam; Erdogan, Ahmet

    2011-01-01

    Advances in signal and image processing together with increasing computing power are bringing mobile technology closer to applications in a variety of domains like automotive, health, telecommunication, multimedia, entertainment and many others. The development of these leading applications, involving a large diversity of algorithms (e.g. signal, image, video, 3D, communication, cryptography) is classically divided into three consecutive steps: a theoretical study of the algorithms, a study of the target architecture, and finally the implementation. Such a linear design flow is reaching its li

  15. Use of frontal lobe hemodynamics as reinforcement signals to an adaptive controller.

    Directory of Open Access Journals (Sweden)

    Marcello M DiStasio

    Full Text Available Decision-making ability in the frontal lobe (among other brain structures relies on the assignment of value to states of the animal and its environment. Then higher valued states can be pursued and lower (or negative valued states avoided. The same principle forms the basis for computational reinforcement learning controllers, which have been fruitfully applied both as models of value estimation in the brain, and as artificial controllers in their own right. This work shows how state desirability signals decoded from frontal lobe hemodynamics, as measured with near-infrared spectroscopy (NIRS, can be applied as reinforcers to an adaptable artificial learning agent in order to guide its acquisition of skills. A set of experiments carried out on an alert macaque demonstrate that both oxy- and deoxyhemoglobin concentrations in the frontal lobe show differences in response to both primarily and secondarily desirable (versus undesirable stimuli. This difference allows a NIRS signal classifier to serve successfully as a reinforcer for an adaptive controller performing a virtual tool-retrieval task. The agent's adaptability allows its performance to exceed the limits of the NIRS classifier decoding accuracy. We also show that decoding state desirabilities is more accurate when using relative concentrations of both oxyhemoglobin and deoxyhemoglobin, rather than either species alone.

  16. Signal processing for 5G algorithms and implementations

    CERN Document Server

    Luo, Fa-Long

    2016-01-01

    A comprehensive and invaluable guide to 5G technology, implementation and practice in one single volume. For all things 5G, this book is a must-read. Signal processing techniques have played the most important role in wireless communications since the second generation of cellular systems. It is anticipated that new techniques employed in 5G wireless networks will not only improve peak service rates significantly, but also enhance capacity, coverage, reliability , low-latency, efficiency, flexibility, compatibility and convergence to meet the increasing demands imposed by applications such as big data, cloud service, machine-to-machine (M2M) and mission-critical communications. This book is a comprehensive and detailed guide to all signal processing techniques employed in 5G wireless networks. Uniquely organized into four categories, New Modulation and &n sp;Coding, New Spatial Processing, New Spectrum Opportunities and New System-level Enabling Technologies, it covers everything from network architecture...

  17. A digital signal processing system for coherent laser radar

    Science.gov (United States)

    Hampton, Diana M.; Jones, William D.; Rothermel, Jeffry

    1991-01-01

    A data processing system for use with continuous-wave lidar is described in terms of its configuration and performance during the second survey mission of NASA'a Global Backscatter Experiment. The system is designed to estimate a complete lidar spectrum in real time, record the data from two lidars, and monitor variables related to the lidar operating environment. The PC-based system includes a transient capture board, a digital-signal processing (DSP) board, and a low-speed data-acquisition board. Both unprocessed and processed lidar spectrum data are monitored in real time, and the results are compared to those of a previous non-DSP-based system. Because the DSP-based system is digital it is slower than the surface-acoustic-wave signal processor and collects 2500 spectra/s. However, the DSP-based system provides complete data sets at two wavelengths from the continuous-wave lidars.

  18. Snore related signals processing in a private cloud computing system.

    Science.gov (United States)

    Qian, Kun; Guo, Jian; Xu, Huijie; Zhu, Zhaomeng; Zhang, Gongxuan

    2014-09-01

    Snore related signals (SRS) have been demonstrated to carry important information about the obstruction site and degree in the upper airway of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) patients in recent years. To make this acoustic signal analysis method more accurate and robust, big SRS data processing is inevitable. As an emerging concept and technology, cloud computing has motivated numerous researchers and engineers to exploit applications both in academic and industry field, which could have an ability to implement a huge blue print in biomedical engineering. Considering the security and transferring requirement of biomedical data, we designed a system based on private cloud computing to process SRS. Then we set the comparable experiments of processing a 5-hour audio recording of an OSAHS patient by a personal computer, a server and a private cloud computing system to demonstrate the efficiency of the infrastructure we proposed.

  19. New challenges in signal processing in astrophysics: the SKA case

    International Nuclear Information System (INIS)

    Faulkner, Andrew; Zarb-Adami, Kristian; De Vaate, Jan Geralt Bij

    2015-01-01

    Signal processing and communications are driving the latest generation of radio telescopes with major developments taking place for use on the Square Kilometre Array, SKA, the next generation low frequency radio telescope. The data rates and processing performance that can be achieved with currently available components means that concepts from the earlier days of radio astronomy, phased arrays, can be used at higher frequencies, larger bandwidths and higher numbers of beams. Indeed it has been argued that the use of dishes as a mechanical beamformer only gained strong acceptance to mitigate the processing load from phased array technology. The balance is changing and benefits in both performance and cost can be realised. In this paper we will mostly consider the signal processing implementation and control for very large phased arrays consisting of hundreds of thousands of antennas or even millions of antennas. They can use current technology for the initial deployments. These systems are very large extending to hundreds of racks with thousands of signal processing modules that link through high-speed, but commercially available data networking devices. There are major challenges to accurately calibrate the arrays, mitigate power consumption and make the system maintainable

  20. Social multimedia signals a signal processing approach to social network phenomena

    CERN Document Server

    Roy, Suman Deb

    2014-01-01

    This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

  1. A Versatile Multichannel Digital Signal Processing Module for Microcalorimeter Arrays

    Science.gov (United States)

    Tan, H.; Collins, J. W.; Walby, M.; Hennig, W.; Warburton, W. K.; Grudberg, P.

    2012-06-01

    Different techniques have been developed for reading out microcalorimeter sensor arrays: individual outputs for small arrays, and time-division or frequency-division or code-division multiplexing for large arrays. Typically, raw waveform data are first read out from the arrays using one of these techniques and then stored on computer hard drives for offline optimum filtering, leading not only to requirements for large storage space but also limitations on achievable count rate. Thus, a read-out module that is capable of processing microcalorimeter signals in real time will be highly desirable. We have developed multichannel digital signal processing electronics that are capable of on-board, real time processing of microcalorimeter sensor signals from multiplexed or individual pixel arrays. It is a 3U PXI module consisting of a standardized core processor board and a set of daughter boards. Each daughter board is designed to interface a specific type of microcalorimeter array to the core processor. The combination of the standardized core plus this set of easily designed and modified daughter boards results in a versatile data acquisition module that not only can easily expand to future detector systems, but is also low cost. In this paper, we first present the core processor/daughter board architecture, and then report the performance of an 8-channel daughter board, which digitizes individual pixel outputs at 1 MSPS with 16-bit precision. We will also introduce a time-division multiplexing type daughter board, which takes in time-division multiplexing signals through fiber-optic cables and then processes the digital signals to generate energy spectra in real time.

  2. The adapter protein, Grb10, is a positive regulator of vascular endothelial growth factor signaling.

    Science.gov (United States)

    Giorgetti-Peraldi, S; Murdaca, J; Mas, J C; Van Obberghen, E

    2001-07-05

    Vascular endothelial growth factor (VEGF) is an important regulator of vasculogenesis and angiogenesis. Activation of VEGF receptors leads to the recruitment of SH2 containing proteins which link the receptors to the activation of signaling pathways. Here we report that Grb10, an adapter protein of which the biological role remains unknown, is tyrosine phosphorylated in response to VEGF in endothelial cells (HUVEC) and in 293 cells expressing the VEGF receptor KDR. An intact SH2 domain is required for Grb10 tyrosine phosphorylation in response to VEGF, and this phosphorylation is mediated in part through the activation of Src. In HUVEC, VEGF increases Grb10 mRNA level. Expression of Grb10 in HUVEC or in KDR expressing 293 cells results in an increase in the amount and in the tyrosine phosphorylation of KDR. In 293 cells, this is correlated with the activation of signaling molecules, such as MAP kinase. By expressing mutants of Grb10, we found that the positive action of Grb10 is independent of its SH2 domain. Moreover, these Grb10 effects on KDR seem to be specific since Grb10 has no effect on the insulin receptor, and Grb2, another adapter protein, does not mimic the effect of Grb10 on KDR. In conclusion, we propose that VEGF up-regulates Grb10 level, which in turn increases KDR molecules, suggesting that Grb10 could be involved in a positive feedback loop in VEGF signaling.

  3. Adaptation to TKI Treatment Reactivates ERK Signaling in Tyrosine Kinase-Driven Leukemias and Other Malignancies.

    Science.gov (United States)

    Bruner, J Kyle; Ma, Hayley S; Li, Li; Qin, Alice Can Ran; Rudek, Michelle A; Jones, Richard J; Levis, Mark J; Pratz, Keith W; Pratilas, Christine A; Small, Donald

    2017-10-15

    FMS-like tyrosine kinase-3 (FLT3) tyrosine kinase inhibitors (TKI) have been tested extensively to limited benefit in acute myeloid leukemia (AML). We hypothesized that FLT3/internal tandem duplication (ITD) leukemia cells exhibit mechanisms of intrinsic signaling adaptation to TKI treatment that are associated with an incomplete response. Here, we identified reactivation of ERK signaling within hours following treatment of FLT3/ITD AML cells with selective inhibitors of FLT3. When these cells were treated with inhibitors of both FLT3 and MEK in combination, ERK reactivation was abrogated and anti-leukemia effects were more pronounced compared with either drug alone. ERK reactivation was also observed following inhibition of other tyrosine kinase-driven cancer cells, including EGFR-mutant lung cancer, HER2-amplified breast cancer, and BCR-ABL leukemia. These studies reveal an adaptive feedback mechanism in tyrosine kinase-driven cancers associated with reactivation of ERK signaling in response to targeted inhibition. Cancer Res; 77(20); 5554-63. ©2017 AACR . ©2017 American Association for Cancer Research.

  4. A computational model of human auditory signal processing and perception

    DEFF Research Database (Denmark)

    Jepsen, Morten Løve; Ewert, Stephan D.; Dau, Torsten

    2008-01-01

    A model of computational auditory signal-processing and perception that accounts for various aspects of simultaneous and nonsimultaneous masking in human listeners is presented. The model is based on the modulation filterbank model described by Dau et al. [J. Acoust. Soc. Am. 102, 2892 (1997...... discrimination with pure tones and broadband noise, tone-in-noise detection, spectral masking with narrow-band signals and maskers, forward masking with tone signals and tone or noise maskers, and amplitude-modulation detection with narrow- and wideband noise carriers. The model can account for most of the key...... properties of the data and is more powerful than the original model. The model might be useful as a front end in technical applications....

  5. Analog integrated circuits design for processing physiological signals.

    Science.gov (United States)

    Li, Yan; Poon, Carmen C Y; Zhang, Yuan-Ting

    2010-01-01

    Analog integrated circuits (ICs) designed for processing physiological signals are important building blocks of wearable and implantable medical devices used for health monitoring or restoring lost body functions. Due to the nature of physiological signals and the corresponding application scenarios, the ICs designed for these applications should have low power consumption, low cutoff frequency, and low input-referred noise. In this paper, techniques for designing the analog front-end circuits with these three characteristics will be reviewed, including subthreshold circuits, bulk-driven MOSFETs, floating gate MOSFETs, and log-domain circuits to reduce power consumption; methods for designing fully integrated low cutoff frequency circuits; as well as chopper stabilization (CHS) and other techniques that can be used to achieve a high signal-to-noise performance. Novel applications using these techniques will also be discussed.

  6. Statistical 21-cm Signal Separation via Gaussian Process Regression Analysis

    Science.gov (United States)

    Mertens, F. G.; Ghosh, A.; Koopmans, L. V. E.

    2018-05-01

    Detecting and characterizing the Epoch of Reionization and Cosmic Dawn via the redshifted 21-cm hyperfine line of neutral hydrogen will revolutionize the study of the formation of the first stars, galaxies, black holes and intergalactic gas in the infant Universe. The wealth of information encoded in this signal is, however, buried under foregrounds that are many orders of magnitude brighter. These must be removed accurately and precisely in order to reveal the feeble 21-cm signal. This requires not only the modeling of the Galactic and extra-galactic emission, but also of the often stochastic residuals due to imperfect calibration of the data caused by ionospheric and instrumental distortions. To stochastically model these effects, we introduce a new method based on `Gaussian Process Regression' (GPR) which is able to statistically separate the 21-cm signal from most of the foregrounds and other contaminants. Using simulated LOFAR-EoR data that include strong instrumental mode-mixing, we show that this method is capable of recovering the 21-cm signal power spectrum across the entire range k = 0.07 - 0.3 {h cMpc^{-1}}. The GPR method is most optimal, having minimal and controllable impact on the 21-cm signal, when the foregrounds are correlated on frequency scales ≳ 3 MHz and the rms of the signal has σ21cm ≳ 0.1 σnoise. This signal separation improves the 21-cm power-spectrum sensitivity by a factor ≳ 3 compared to foreground avoidance strategies and enables the sensitivity of current and future 21-cm instruments such as the Square Kilometre Array to be fully exploited.

  7. Blind I/Q Signal Separation-Based Solutions for Receiver Signal Processing

    Directory of Open Access Journals (Sweden)

    Visa Koivunen

    2005-09-01

    Full Text Available This paper introduces some novel digital signal processing (DSP-based approaches to some of the most fundamental tasks of radio receivers, namely, channel equalization, carrier synchronization, and I/Q mismatch compensation. The leading principle is to show that all these problems can be solved blindly (i.e., without training signals by forcing the I and Q components of the observed data as independent as possible. Blind signal separation (BSS is then introduced as an efficient tool to carry out these tasks, and simulation examples are used to illustrate the performance of the proposed approaches. The main application area of the presented carrier synchronization and I/Q mismatch compensation techniques is in direct-conversion type receivers, while the proposed channel equalization principles basically apply to any radio architecture.

  8. Process and circuiting arrangement for the conversion of analog signals to digital signals and digital signals to analog signals

    International Nuclear Information System (INIS)

    Wintzer, K.

    1977-01-01

    Process for analog-to-digital and digital-to-analog conversion in telecommunication systems whose outstations each have an analog transmitter and an analog receiver. The invention illustrates a method of reducing the power demand of the converters at times when no conversion processes take place. (RW) [de

  9. Adaptive PCA based fault diagnosis scheme in imperial smelting process.

    Science.gov (United States)

    Hu, Zhikun; Chen, Zhiwen; Gui, Weihua; Jiang, Bin

    2014-09-01

    In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  10. CONSTRUCTIVE MODEL OF ADAPTATION OF DATA STRUCTURES IN RAM. PART II. CONSTRUCTORS OF SCENARIOS AND ADAPTATION PROCESSES

    Directory of Open Access Journals (Sweden)

    V. I. Shynkarenko

    2016-04-01

    Full Text Available Purpose.The second part of the paper completes presentation of constructive and the productive structures (CPS, modeling adaptation of data structures in memory (RAM. The purpose of the second part in the research is to develop a model of process of adaptation data in a RAM functioning in different hardware and software environments and scenarios of data processing. Methodology. The methodology of mathematical and algorithmic constructionism was applied. In this part of the paper, changes were developed the constructors of scenarios and adaptation processes based on a generalized CPS through its transformational conversions. Constructors are interpreted, specialized CPS. Were highlighted the terminal alphabets of the constructor scenarios in the form of data processing algorithms and the constructor of adaptation – in the form of algorithmic components of the adaptation process. The methodology involves the development of substitution rules that determine the output process of the relevant structures. Findings. In the second part of the paper, system is represented by CPS modeling adaptation data placement in the RAM, namely, constructors of scenarios and of adaptation processes. The result of the implementation of constructor of scenarios is a set of data processing operations in the form of text in the language of programming C#, constructor of the adaptation processes – a process of adaptation, and the result the process of adaptation – the adapted binary code of processing data structures. Originality. For the first time proposed the constructive model of data processing – the scenario that takes into account the order and number of calls to the various elements of data structures and adaptation of data structures to the different hardware and software environments. At the same the placement of data in RAM and processing algorithms are adapted. Constructionism application in modeling allows to link data models and algorithms for

  11. Calculation of vehicle delay at signal-controlled intersections with adaptive traffic control algorithm

    Directory of Open Access Journals (Sweden)

    Andronov Roman

    2018-01-01

    Full Text Available By widely introducing information technology tools in the field of traffic control, it is possible to increase the capacity of hubs and reduce vehicle delays. Adaptive traffic light control is one of such tools. Its effectiveness can be assessed through traffic flow simulation. The aim of this study is to create a simulation model of a signal-controlled intersection that can be used to assess the effectiveness of adaptive control in various traffic situations, including the presence or absence of pedestrian traffic through an intersection. The model is based on a numerical experiment conducted using the Monte Carlo method. As a result of the study, vehicle delays, queue length and duration of traffic light cycles are calculated subject to different intensities of incoming traffic flows, and the presence or absence of pedestrian traffic.

  12. Evaluation of Adaptive Signal Control Technology—Volume 2 : Comparison of Base Condition to the First Year After Implementation

    Science.gov (United States)

    2018-05-01

    Field evaluation of adaptive signal control technologies (ASCT) is very important in understanding the systems contribution to safety and operational efficiency. Data were collected at six intersections along the Neil Street corridor in Champaign,...

  13. [Super sweet corn hybrids adaptability for industrial processing. I freezing].

    Science.gov (United States)

    Alfonzo, Braunnier; Camacho, Candelario; Ortiz de Bertorelli, Ligia; De Venanzi, Frank

    2002-09-01

    With the purpose of evaluating adaptability to the freezing process of super sweet corn sh2 hybrids Krispy King, Victor and 324, 100 cobs of each type were frozen at -18 degrees C. After 120 days of storage, their chemical, microbiological and sensorial characteristics were compared with a sweet corn su. Industrial quality of the process of freezing and length and number of rows in cobs were also determined. Results revealed yields above 60% in frozen corns. Length and number of rows in cobs were acceptable. Most of the chemical characteristics of super sweet hybrids were not different from the sweet corn assayed at the 5% significance level. Moisture content and soluble solids of hybrid Victor, as well as total sugars of hybrid 324 were statistically different. All sh2 corns had higher pH values. During freezing, soluble solids concentration, sugars and acids decreased whereas pH increased. Frozen cobs exhibited acceptable microbiological rank, with low activities of mesophiles and total coliforms, absence of psychrophiles and fecal coliforms, and an appreciable amount of molds. In conclusion, sh2 hybrids adapted with no problems to the freezing process, they had lower contents of soluble solids and higher contents of total sugars, which almost doubled the amount of su corn; flavor, texture, sweetness and appearance of kernels were also better. Hybrid Victor was preferred by the evaluating panel and had an outstanding performance due to its yield and sensorial characteristics.

  14. Adapting bilateral directional processing to individual and situational influences

    DEFF Research Database (Denmark)

    Neher, Tobias; Wagener, Kirsten C.; Latzel, Matthias

    2017-01-01

    This study examined differences in benefit from bilateral directional processing. Groups of listeners with symmetric or asymmetric audiograms level difference, BILD......), and no difference in age or overall degree of hearing loss took part. Aided speech reception was measured using virtual acoustics together with a simulation of a linked pair of closed-fit behind-the-ear hearing aids. Five processing schemes and three acoustic scenarios were used. The processing schemes differed...... in the trade-off between signal-to-noise ratio (SNR) improvement and binaural cue preservation. The acoustic scenarios consisted of a frontal target talker and two lateral speech maskers or spatially diffuse noise. For both groups, a significant interaction between BILD, processing scheme and acoustic scenario...

  15. Monitoring of drilling process with the application of acoustic signal

    Directory of Open Access Journals (Sweden)

    Labaš Milan

    2000-09-01

    Full Text Available Monitoring of rock disintegration process at drilling, scanning of input quantities: thrust F, revolution n and the course of some output quantities: the drilling rate v and the power input P are needed for the control of this process. We can calculate the specific volume work of rock disintegration w and ϕ - quotient of drilling rate v and the specific volume work of disintegration w from the presented quantities.Works on an expertimental stand showed that the correlation relationships between the input and output quantities can be found by scanning the accompanying sound of the drilling proces.Research of the rock disintegration with small-diameter diamond drill tools and different rock types is done at the Institute of Geotechnics. The aim of this research is the possibility of monitoring and controlling the rock disintegration process with the application of acoustic signal. The acoustic vibrations accompanying the drilling process are recorded by a microphone placed in a defined position in the acoustic space. The drilling device (drilling stand, the drilling tool and the rock are the source of sound. Two basic sound states exist in the drilling stand research : the noise at no-load running and the noise at the rotary drilling of rock. Suitable quantities for optimizing the rock disintegration process are searched by the study of the acoustic signal. The dominant frequencies that characterize the disintegration process for the given rock and tool are searched by the analysis of the acoustic signal. The analysis of dominant frequencies indicates the possibility of determining an optimal regime for the maximal drilling rate. Extreme of the specific disintegration energy is determinated by the dispersion of the dominant frequency.The scanned acoustic signal is processed by the Fourier transformation. The Fourier transformation facilitates the distribution of the general non-harmonic periodic process into harmonic components. The harmonic

  16. A review of channel selection algorithms for EEG signal processing

    Science.gov (United States)

    Alotaiby, Turky; El-Samie, Fathi E. Abd; Alshebeili, Saleh A.; Ahmad, Ishtiaq

    2015-12-01

    Digital processing of electroencephalography (EEG) signals has now been popularly used in a wide variety of applications such as seizure detection/prediction, motor imagery classification, mental task classification, emotion classification, sleep state classification, and drug effects diagnosis. With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. The main purpose of the channel selection process is threefold: (i) to reduce the computational complexity of any processing task performed on EEG signals by selecting the relevant channels and hence extracting the features of major importance, (ii) to reduce the amount of overfitting that may arise due to the utilization of unnecessary channels, for the purpose of improving the performance, and (iii) to reduce the setup time in some applications. Signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform have been used for feature extraction and hence for channel selection in most of channel selection algorithms. In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods according to the evaluation approach.

  17. Fetal QRS extraction from abdominal recordings via model-based signal processing and intelligent signal merging

    International Nuclear Information System (INIS)

    Haghpanahi, Masoumeh; Borkholder, David A

    2014-01-01

    Noninvasive fetal ECG (fECG) monitoring has potential applications in diagnosing congenital heart diseases in a timely manner and assisting clinicians to make more appropriate decisions during labor. However, despite advances in signal processing and machine learning techniques, the analysis of fECG signals has still remained in its preliminary stages. In this work, we describe an algorithm to automatically locate QRS complexes in noninvasive fECG signals obtained from a set of four electrodes placed on the mother’s abdomen. The algorithm is based on an iterative decomposition of the maternal and fetal subspaces and filtering of the maternal ECG (mECG) components from the fECG recordings. Once the maternal components are removed, a novel merging technique is applied to merge the signals and detect the fetal QRS (fQRS) complexes. The algorithm was trained and tested on the fECG datasets provided by the PhysioNet/CinC challenge 2013. The final results indicate that the algorithm is able to detect fetal peaks for a variety of signals with different morphologies and strength levels encountered in clinical practice. (paper)

  18. Task effects on BOLD signal correlates of implicit syntactic processing

    Science.gov (United States)

    Caplan, David

    2010-01-01

    BOLD signal was measured in sixteen participants who made timed font change detection judgments in visually presented sentences that varied in syntactic structure and the order of animate and inanimate nouns. Behavioral data indicated that sentences were processed to the level of syntactic structure. BOLD signal increased in visual association areas bilaterally and left supramarginal gyrus in the contrast of sentences with object- and subject-extracted relative clauses without font changes in which the animacy order of the nouns biased against the syntactically determined meaning of the sentence. This result differs from the findings in a non-word detection task (Caplan et al, 2008a), in which the same contrast led to increased BOLD signal in the left inferior frontal gyrus. The difference in areas of activation indicates that the sentences were processed differently in the two tasks. These differences were further explored in an eye tracking study using the materials in the two tasks. Issues pertaining to how parsing and interpretive operations are affected by a task that is being performed, and how this might affect BOLD signal correlates of syntactic contrasts, are discussed. PMID:20671983

  19. When noise is beneficial for sensory encoding: Noise adaptation can improve face processing.

    Science.gov (United States)

    Menzel, Claudia; Hayn-Leichsenring, Gregor U; Redies, Christoph; Németh, Kornél; Kovács, Gyula

    2017-10-01

    The presence of noise usually impairs the processing of a stimulus. Here, we studied the effects of noise on face processing and show, for the first time, that adaptation to noise patterns has beneficial effects on face perception. We used noiseless faces that were either surrounded by random noise or presented on a uniform background as stimuli. In addition, the faces were either preceded by noise adaptors or not. Moreover, we varied the statistics of the noise so that its spectral slope either matched that of the faces or it was steeper or shallower. Results of parallel ERP recordings showed that the background noise reduces the amplitude of the face-evoked N170, indicating less intensive face processing. Adaptation to a noise pattern, however, led to reduced P1 and enhanced N170 amplitudes as well as to a better behavioral performance in two of the three noise conditions. This effect was also augmented by the presence of background noise around the target stimuli. Additionally, the spectral slope of the noise pattern affected the size of the P1, N170 and P2 amplitudes. We reason that the observed effects are due to the selective adaptation of noise-sensitive neurons present in the face-processing cortical areas, which may enhance the signal-to-noise-ratio. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Instantaneous and Frequency-Warped Signal Processing Techniques for Auditory Source Separation.

    Science.gov (United States)

    Wang, Avery Li-Chun

    This thesis summarizes several contributions to the areas of signal processing and auditory source separation. The philosophy of Frequency-Warped Signal Processing is introduced as a means for separating the AM and FM contributions to the bandwidth of a complex-valued, frequency-varying sinusoid p (n), transforming it into a signal with slowly-varying parameters. This transformation facilitates the removal of p (n) from an additive mixture while minimizing the amount of damage done to other signal components. The average winding rate of a complex-valued phasor is explored as an estimate of the instantaneous frequency. Theorems are provided showing the robustness of this measure. To implement frequency tracking, a Frequency-Locked Loop algorithm is introduced which uses the complex winding error to update its frequency estimate. The input signal is dynamically demodulated and filtered to extract the envelope. This envelope may then be remodulated to reconstruct the target partial, which may be subtracted from the original signal mixture to yield a new, quickly-adapting form of notch filtering. Enhancements to the basic tracker are made which, under certain conditions, attain the Cramer -Rao bound for the instantaneous frequency estimate. To improve tracking, the novel idea of Harmonic -Locked Loop tracking, using N harmonically constrained trackers, is introduced for tracking signals, such as voices and certain musical instruments. The estimated fundamental frequency is computed from a maximum-likelihood weighting of the N tracking estimates, making it highly robust. The result is that harmonic signals, such as voices, can be isolated from complex mixtures in the presence of other spectrally overlapping signals. Additionally, since phase information is preserved, the resynthesized harmonic signals may be removed from the original mixtures with relatively little damage to the residual signal. Finally, a new methodology is given for designing linear-phase FIR filters

  1. FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling.

    Science.gov (United States)

    Kim, Chang-Min; Park, Hyung-Min; Kim, Taesu; Choi, Yoon-Kyung; Lee, Soo-Young

    2003-01-01

    An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in FPGA. The chip design fully utilizes modular concept and several chips may be put together for complex applications with a large number of noise sources. Experimental results with a fabricated test board are reported for ANC only, BSS only, and simultaneous ANC/BSS, which demonstrates successful speech enhancement in real environments in real time.

  2. Missile signal processing common computer architecture for rapid technology upgrade

    Science.gov (United States)

    Rabinkin, Daniel V.; Rutledge, Edward; Monticciolo, Paul

    2004-10-01

    Interceptor missiles process IR images to locate an intended target and guide the interceptor towards it. Signal processing requirements have increased as the sensor bandwidth increases and interceptors operate against more sophisticated targets. A typical interceptor signal processing chain is comprised of two parts. Front-end video processing operates on all pixels of the image and performs such operations as non-uniformity correction (NUC), image stabilization, frame integration and detection. Back-end target processing, which tracks and classifies targets detected in the image, performs such algorithms as Kalman tracking, spectral feature extraction and target discrimination. In the past, video processing was implemented using ASIC components or FPGAs because computation requirements exceeded the throughput of general-purpose processors. Target processing was performed using hybrid architectures that included ASICs, DSPs and general-purpose processors. The resulting systems tended to be function-specific, and required custom software development. They were developed using non-integrated toolsets and test equipment was developed along with the processor platform. The lifespan of a system utilizing the signal processing platform often spans decades, while the specialized nature of processor hardware and software makes it difficult and costly to upgrade. As a result, the signal processing systems often run on outdated technology, algorithms are difficult to update, and system effectiveness is impaired by the inability to rapidly respond to new threats. A new design approach is made possible three developments; Moore's Law - driven improvement in computational throughput; a newly introduced vector computing capability in general purpose processors; and a modern set of open interface software standards. Today's multiprocessor commercial-off-the-shelf (COTS) platforms have sufficient throughput to support interceptor signal processing requirements. This application

  3. Adaptive endpoint detection of seismic signal based on auto-correlated function

    International Nuclear Information System (INIS)

    Fan Wanchun; Shi Ren

    2000-01-01

    There are certain shortcomings for the endpoint detection by time-waveform envelope and/or by checking the travel table (both labelled as the artificial detection method). Based on the analysis of the auto-correlation function, the notion of the distance between auto-correlation functions was quoted, and the characterizations of the noise and the signal with noise were discussed by using the distance. Then, the method of auto-adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low SNR circumstance

  4. Neurotrophin and FGF Signaling Adapter Proteins, FRS2 and FRS3, Regulate Dentate Granule Cell Maturation and Excitatory Synaptogenesis.

    Science.gov (United States)

    Nandi, Sayan; Alviña, Karina; Lituma, Pablo J; Castillo, Pablo E; Hébert, Jean M

    2018-01-15

    Dentate granule cells (DGCs) play important roles in cognitive processes. Knowledge about how growth factors such as FGFs and neurotrophins contribute to the maturation and synaptogenesis of DGCs is limited. Here, using brain-specific and germline mouse mutants we show that a module of neurotrophin and FGF signaling, the FGF Receptor Substrate (FRS) family of intracellular adapters, FRS2 and FRS3, are together required for postnatal brain development. In the hippocampus, FRS promotes dentate gyrus morphogenesis and DGC maturation during developmental neurogenesis, similar to previously published functions for both neurotrophins and FGFs. Consistent with a role in DGC maturation, two-photon imaging revealed that Frs2,3-double mutants have reduced numbers of dendritic branches and spines in DGCs. Functional analysis further showed that double-mutant mice exhibit fewer excitatory synaptic inputs onto DGCs. These observations reveal roles for FRS adapters in DGC maturation and synaptogenesis and suggest that FRS proteins may act as an important node for FGF and neurotrophin signaling in postnatal hippocampal development. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  5. Eddy currents signal processing for steam generator inspection in PWR nuclear power plants

    International Nuclear Information System (INIS)

    Georgel, B.

    1992-01-01

    Steam generator tubes in nuclear power plants are periodically checked by means of eddy current probes. The output of a probe is composed of three types of signals: known events (rolling zone, support plates, U-bend part), noise (mainly metallurgical noise) and possible flaws. The latter are random transients, both in arrival time and in shape: they have to be detected and then estimated, before to be fed to the high level stages of a diagnostic system. The objective of the study presented is to develop a semi-automatic system, which could manage and process more than 1 M-bytes of data per tube and provide an operator with reliable diagnostics proposals within a few minutes. This can be achieved only by cooperation of several digital signal processing techniques: detection, segmentation, estimation, noise subtraction, adaptive filtering, modelization, pattern recognition. The paper describes some of these items

  6. Advanced Signal Processing for MIMO-OFDM Receivers

    DEFF Research Database (Denmark)

    Manchón, Carles Navarro

    This thesis deals with a wide range of topics within the research area of advanced baseband receiver design for wireless communication systems. In particular, the work focuses on signal processing algorithms for receivers in multiple-input multiple-output (MIMO) orthogonal frequency-division mult......This thesis deals with a wide range of topics within the research area of advanced baseband receiver design for wireless communication systems. In particular, the work focuses on signal processing algorithms for receivers in multiple-input multiple-output (MIMO) orthogonal frequency...... the structure of the receiver with the hope that the resulting heuristic architecture will exhibit the desired behavior and performance. On the other hand, one can employ analytical frameworks to pose the problem as the optimization of a global objective function subject to certain constraints. This work...

  7. Systolic pocessing and an implementation for signal and image processing

    Energy Technology Data Exchange (ETDEWEB)

    Kulkarni, A.V.; Yen, D.W.L.

    1982-10-01

    Many signal and image processing applications impose a severe demand on the I/O bandwidth and computation power of general-purpose computers. The systolic concept offers guidelines in building cost-effective systems that balance I/O with computation. The resulting simplicity and regularity of such systems leads to modular designs suitable for VLSI implementation. The authors describe a linear systolic array capable of evaluating a large class of inner-product functions used in signal and image processing. These include matrix multiplications, multidimensional convolutions using fixed or time-varying kernels, as well as various nonlinear functions of vectors. The system organization of a working prototype is also described. 11 references.

  8. Signal processing methods for in-situ creep specimen monitoring

    Science.gov (United States)

    Guers, Manton J.; Tittmann, Bernhard R.

    2018-04-01

    Previous work investigated using guided waves for monitoring creep deformation during accelerated life testing. The basic objective was to relate observed changes in the time-of-flight to changes in the environmental temperature and specimen gage length. The work presented in this paper investigated several signal processing strategies for possible application in the in-situ monitoring system. Signal processing methods for both group velocity (wave-packet envelope) and phase velocity (peak tracking) time-of-flight were considered. Although the Analytic Envelope found via the Hilbert transform is commonly applied for group velocity measurements, erratic behavior in the indicated time-of-flight was observed when this technique was applied to the in-situ data. The peak tracking strategies tested had generally linear trends, and tracking local minima in the raw waveform ultimately showed the most consistent results.

  9. An Adaptive Model for Calculating the Correlation Degree of Multiple Adjacent Signalized Intersections

    Directory of Open Access Journals (Sweden)

    Linhong Wang

    2013-01-01

    Full Text Available As an important component of the urban adaptive traffic control system, subarea partition algorithm divides the road network into some small subareas and then determines the optimal signal control mode for each signalized intersection. Correlation model is the core of subarea partition algorithm because it can quantify the correlation degree of adjacent signalized intersections and decides whether these intersections can be grouped into one subarea. In most cases, there are more than two intersections in one subarea. However, current researches only focus on the correlation model for two adjacent intersections. The objective of this study is to develop a model which can calculate the correlation degree of multiple intersections adaptively. The cycle lengths, link lengths, number of intersections, and path flow between upstream and downstream coordinated phases were selected as the contributing factors of the correlation model. Their jointly impacts on the performance of the coordinated control mode relative to the isolated control mode were further studied using numerical experiments. The paper then proposed a correlation index (CI as an alternative to relative performance. The relationship between CI and the four contributing factors was established in order to predict the correlation, which determined whether adjacent intersections could be partitioned into one subarea. A value of 0 was set as the threshold of CI. If CI was larger than 0, multiple intersections could be partitioned into one subarea; otherwise, they should be separated. Finally, case studies were conducted in a real-life signalized network to evaluate the performance of the model. The results show that the CI simulates the relative performance well and could be a reliable index for subarea partition.

  10. Signal Processing for Time-Series Functions on a Graph

    Science.gov (United States)

    2018-02-01

    Figures Fig. 1 Time -series function on a fixed graph.............................................2 iv Approved for public release; distribution is...φi〉`2(V)φi (39) 6= f̄ (40) Instead, we simply recover the average of f over time . 13 Approved for public release; distribution is unlimited. This...ARL-TR-8276• FEB 2018 US Army Research Laboratory Signal Processing for Time -Series Functions on a Graph by Humberto Muñoz-Barona, Jean Vettel, and

  11. Wavelet based methods for improved wind profiler signal processing

    Directory of Open Access Journals (Sweden)

    V. Lehmann

    2001-08-01

    Full Text Available In this paper, we apply wavelet thresholding for removing automatically ground and intermittent clutter (airplane echoes from wind profiler radar data. Using the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop wavelet domain thresholding rules, which allow us to identify the coefficients relevant for clutter and to suppress them in order to obtain filtered reconstructions.Key words. Meteorology and atmospheric dynamics (instruments and techniques – Radio science (remote sensing; signal processing

  12. Synthesis of computational structures for analog signal processing

    CERN Document Server

    Popa, Cosmin Radu

    2011-01-01

    Presents the most important classes of computational structures for analog signal processing, including differential or multiplier structures, squaring or square-rooting circuits, exponential or Euclidean distance structures and active resistor circuitsIntroduces the original concept of the multifunctional circuit, an active structure that is able to implement, starting from the same circuit core, a multitude of continuous mathematical functionsCovers mathematical analysis, design and implementation of a multitude of function generator structures

  13. Signal Processing Effects for Ultrasonic Guided Wave Scanning of Composites

    International Nuclear Information System (INIS)

    Roth, D.J.; Cosgriff, L.M.; Martin, R.E.; Burns, E.A.; Teemer, L.

    2005-01-01

    The goal of this ongoing work is to optimize experimental variables for a guided wave scanning method to obtain the most revealing and accurate images of defect conditions in composite materials. This study focuses on signal processing effects involved in forming guided wave scan images. Signal processing is involved at two basic levels for deriving ultrasonic guided wave scan images. At the primary level, NASA GRC has developed algorithms to extract over 30 parameters from the multimode signal and its power spectral density. At the secondary level, there are many variables for which values must be chosen that affect actual computation of these parameters. In this study, a ceramic matrix composite sample having a delamination is characterized using the ultrasonic guided wave scan method. Energy balance and decay rate parameters of the guided wave at each scan location are calculated to form images. These images are compared with ultrasonic c-scan and thermography images. The effect of the time portion of the waveform processed on image quality is assessed by comparing with images formed using the total waveform acquired

  14. Road Sign Recognition with Fuzzy Adaptive Pre-Processing Models

    Science.gov (United States)

    Lin, Chien-Chuan; Wang, Ming-Shi

    2012-01-01

    A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle's speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance. PMID:22778650

  15. Digital signal processing of data from borehole creep closure

    International Nuclear Information System (INIS)

    Chakrabarti, S.; Patrick, W.C.; Duplancic, N.

    1987-01-01

    Digital signal processing, a technique commonly used in the fields of electrical engineering and communication technology, has been successfully used to analyze creep closure data obtained from a 0.91 m diameter by 5.13 deep borehole in bedded salt. By filtering the ''noise'' component of the closure data from a test borehole, important data trends were made more evident and average creep closure rates were able to be calculated. This process provided accurate estimates of closure rates that are used in the design of lined boreholes in which heat-generating transuranic nuclear wastes are emplaced at the Waste Isolation Pilot Plant

  16. Low power signal processing electronics for wearable medical devices.

    Science.gov (United States)

    Casson, Alexander J; Rodriguez-Villegas, Esther

    2010-01-01

    Custom designed microchips, known as Application Specific Integrated Circuits (ASICs), offer the lowest possible power consumption electronics. However, this comes at the cost of a longer, more complex and more costly design process compared to one using generic, off-the-shelf components. Nevertheless, their use is essential in future truly wearable medical devices that must operate for long periods of time from physically small, energy limited batteries. This presentation will demonstrate the state-of-the-art in ASIC technology for providing online signal processing for use in these wearable medical devices.

  17. Interactions between visceral afferent signaling and stimulus processing

    Directory of Open Access Journals (Sweden)

    Hugo D Critchley

    2015-08-01

    Full Text Available Visceral afferent signals to the brain influence thoughts, feelings and behaviour. Here we highlight the findings of a set of empirical investigations in humans concerning body-mind interaction that focus on how feedback from states of autonomic arousal shapes cognition and emotion. There is a longstanding debate regarding the contribution of the body, to mental processes. Recent theoretical models broadly acknowledge the role of (autonomically-mediated physiological arousal to emotional, social and motivational behaviours, yet the underlying mechanisms are only partially characterized. Neuroimaging is overcoming this shortfall; first, by demonstrating correlations between autonomic change and discrete patterns of evoked, and task-independent, neural activity; second, by mapping the central consequences of clinical perturbations in autonomic response and; third, by probing how dynamic fluctuations in peripheral autonomic state are integrated with perceptual, cognitive and emotional processes. Building on the notion that an important source of the brain’s representation of physiological arousal is derived from afferent information from arterial baroreceptors, we have exploited the phasic nature of these signals to show their differential contribution to the processing of emotionally-salient stimuli. This recent work highlights the facilitation at neural and behavioral levels of fear and threat processing that contrasts with the more established observations of the inhibition of central pain processing during baroreceptors activation. The implications of this body-brain-mind axis are discussed.

  18. Wireless receiver architectures and design antennas, RF, synthesizers, mixed signal, and digital signal processing

    CERN Document Server

    Rouphael, Tony J

    2014-01-01

    Wireless Receiver Architectures and Design presents the various designs and architectures of wireless receivers in the context of modern multi-mode and multi-standard devices. This one-stop reference and guide to designing low-cost low-power multi-mode, multi-standard receivers treats analog and digital signal processing simultaneously, with equal detail given to the chosen architecture and modulating waveform. It provides a complete understanding of the receiver's analog front end and the digital backend, and how each affects the other. The book explains the design process in great detail, s

  19. Signal processing in urodynamics: towards high definition urethral pressure profilometry.

    Science.gov (United States)

    Klünder, Mario; Sawodny, Oliver; Amend, Bastian; Ederer, Michael; Kelp, Alexandra; Sievert, Karl-Dietrich; Stenzl, Arnulf; Feuer, Ronny

    2016-03-22

    Urethral pressure profilometry (UPP) is used in the diagnosis of stress urinary incontinence (SUI) which is a significant medical, social, and economic problem. Low spatial pressure resolution, common occurrence of artifacts, and uncertainties in data location limit the diagnostic value of UPP. To overcome these limitations, high definition urethral pressure profilometry (HD-UPP) combining enhanced UPP hardware and signal processing algorithms has been developed. In this work, we present the different signal processing steps in HD-UPP and show experimental results from female minipigs. We use a special microtip catheter with high angular pressure resolution and an integrated inclination sensor. Signals from the catheter are filtered and time-correlated artifacts removed. A signal reconstruction algorithm processes pressure data into a detailed pressure image on the urethra's inside. Finally, the pressure distribution on the urethra's outside is calculated through deconvolution. A mathematical model of the urethra is contained in a point-spread-function (PSF) which is identified depending on geometric and material properties of the urethra. We additionally investigate the PSF's frequency response to determine the relevant frequency band for pressure information on the urinary sphincter. Experimental pressure data are spatially located and processed into high resolution pressure images. Artifacts are successfully removed from data without blurring other details. The pressure distribution on the urethra's outside is reconstructed and compared to the one on the inside. Finally, the pressure images are mapped onto the urethral geometry calculated from inclination and position data to provide an integrated image of pressure distribution, anatomical shape, and location. With its advanced sensing capabilities, the novel microtip catheter collects an unprecedented amount of urethral pressure data. Through sequential signal processing steps, physicians are provided with

  20. A signal processing analysis of Purkinje cells in vitro

    Directory of Open Access Journals (Sweden)

    Ze'ev R Abrams

    2010-05-01

    Full Text Available Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM. We find that the three characteristic frequencies - Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques.

  1. Temporally selective processing of communication signals by auditory midbrain neurons

    DEFF Research Database (Denmark)

    Elliott, Taffeta M; Christensen-Dalsgaard, Jakob; Kelley, Darcy B

    2011-01-01

    click rates ranged from 4 to 50 Hz, the rate at which the clicks begin to overlap. Frequency selectivity and temporal processing were characterized using response-intensity curves, temporal-discharge patterns, and autocorrelations of reduplicated responses to click trains. Characteristic frequencies...... of the rate of clicks in calls. The majority of neurons (85%) were selective for click rates, and this selectivity remained unchanged over sound levels 10 to 20 dB above threshold. Selective neurons give phasic, tonic, or adapting responses to tone bursts and click trains. Some algorithms that could compute...

  2. Dysphagia Screening: Contributions of Cervical Auscultation Signals and Modern Signal-Processing Techniques

    Science.gov (United States)

    Dudik, Joshua M.; Coyle, James L.

    2015-01-01

    Cervical auscultation is the recording of sounds and vibrations caused by the human body from the throat during swallowing. While traditionally done by a trained clinician with a stethoscope, much work has been put towards developing more sensitive and clinically useful methods to characterize the data obtained with this technique. The eventual goal of the field is to improve the effectiveness of screening algorithms designed to predict the risk that swallowing disorders pose to individual patients’ health and safety. This paper provides an overview of these signal processing techniques and summarizes recent advances made with digital transducers in hopes of organizing the highly varied research on cervical auscultation. It investigates where on the body these transducers are placed in order to record a signal as well as the collection of analog and digital filtering techniques used to further improve the signal quality. It also presents the wide array of methods and features used to characterize these signals, ranging from simply counting the number of swallows that occur over a period of time to calculating various descriptive features in the time, frequency, and phase space domains. Finally, this paper presents the algorithms that have been used to classify this data into ‘normal’ and ‘abnormal’ categories. Both linear as well as non-linear techniques are presented in this regard. PMID:26213659

  3. Speech perception at positive signal-to-noise ratios using adaptive adjustment of time compression.

    Science.gov (United States)

    Schlueter, Anne; Brand, Thomas; Lemke, Ulrike; Nitzschner, Stefan; Kollmeier, Birger; Holube, Inga

    2015-11-01

    Positive signal-to-noise ratios (SNRs) characterize listening situations most relevant for hearing-impaired listeners in daily life and should therefore be considered when evaluating hearing aid algorithms. For this, a speech-in-noise test was developed and evaluated, in which the background noise is presented at fixed positive SNRs and the speech rate (i.e., the time compression of the speech material) is adaptively adjusted. In total, 29 younger and 12 older normal-hearing, as well as 24 older hearing-impaired listeners took part in repeated measurements. Younger normal-hearing and older hearing-impaired listeners conducted one of two adaptive methods which differed in adaptive procedure and step size. Analysis of the measurements with regard to list length and estimation strategy for thresholds resulted in a practical method measuring the time compression for 50% recognition. This method uses time-compression adjustment and step sizes according to Versfeld and Dreschler [(2002). J. Acoust. Soc. Am. 111, 401-408], with sentence scoring, lists of 30 sentences, and a maximum likelihood method for threshold estimation. Evaluation of the procedure showed that older participants obtained higher test-retest reliability compared to younger participants. Depending on the group of listeners, one or two lists are required for training prior to data collection.

  4. DBPM signal processing with field programmable gate arrays

    International Nuclear Information System (INIS)

    Lai Longwei; Yi Xing; Zhang Ning; Yang Guisen; Wang Baopeng; Xiong Yun; Leng Yongbin; Yan Yingbing

    2011-01-01

    DBPM system performance is determined by the design and implementation of beam position signal processing algorithm. In order to develop the system, a beam position signal processing algorithm is implemented on FPGA. The hardware is a PMC board ICS-1554A-002 (GE Corp.) with FPGA chip XC5VSX95T. This paper adopts quadrature frequency mixing to down convert high frequency signal to base. Different from conventional method, the mixing is implemented by CORDIC algorithm. The algorithm theory and implementation details are discussed in this paper. As the board contains no front end gain controller, this paper introduces a published patent-pending technique that has been adopted to realize the function in digital logic. The whole design is implemented with VHDL language. An on-line evaluation has been carried on SSRF (Shanghai Synchrotron Radiation Facility)storage ring. Results indicate that the system turn-by-turn data can measure the real beam movement accurately,and system resolution is 1.1μm. (authors)

  5. Receptor downregulation and desensitization enhance the information processing ability of signalling receptors

    Directory of Open Access Journals (Sweden)

    Resat Haluk

    2007-11-01

    Full Text Available Abstract Background In addition to initiating signaling events, the activation of cell surface receptors also triggers regulatory processes that restrict the duration of signaling. Acute attenuation of signaling can be accomplished either via ligand-induced internalization of receptors (endocytic downregulation or via ligand-induced receptor desensitization. These phenomena have traditionally been viewed in the context of adaptation wherein the receptor system enters a refractory state in the presence of sustained ligand stimuli and thereby prevents the cell from over-responding to the ligand. Here we use the epidermal growth factor receptor (EGFR and G-protein coupled receptors (GPCR as model systems to respectively examine the effects of downregulation and desensitization on the ability of signaling receptors to decode time-varying ligand stimuli. Results Using a mathematical model, we show that downregulation and desensitization mechanisms can lead to tight and efficient input-output coupling thereby ensuring synchronous processing of ligand inputs. Frequency response analysis indicates that upstream elements of the EGFR and GPCR networks behave like low-pass filters with the system being able to faithfully transduce inputs below a critical frequency. Receptor downregulation and desensitization increase the filter bandwidth thereby enabling the receptor systems to decode inputs in a wider frequency range. Further, system-theoretic analysis reveals that the receptor systems are analogous to classical mechanical over-damped systems. This analogy enables us to metaphorically describe downregulation and desensitization as phenomena that make the systems more resilient in responding to ligand perturbations thereby improving the stability of the system resting state. Conclusion Our findings suggest that in addition to serving as mechanisms for adaptation, receptor downregulation and desensitization can play a critical role in temporal information

  6. Perspectives of using spin waves for computing and signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Csaba, György, E-mail: gcsaba@gmail.com [Center for Nano Science and Technology, University of Notre Dame (United States); Faculty for Information Technology and Bionics, Pázmány Péter Catholic University (Hungary); Papp, Ádám [Center for Nano Science and Technology, University of Notre Dame (United States); Faculty for Information Technology and Bionics, Pázmány Péter Catholic University (Hungary); Porod, Wolfgang [Center for Nano Science and Technology, University of Notre Dame (United States)

    2017-05-03

    Highlights: • We give an overview of spin wave-based computing with emphasis on non-Boolean signal processors. • Spin waves can combine the best of electronics and photonics and do it in an on-chip and integrable way. • Copying successful approaches from microelectronics may not be the best way toward spin-wave based computing. • Practical devices can be constructed by minimizing the number of required magneto-electric interconnections. - Abstract: Almost all the world's information is processed and transmitted by either electric currents or photons. Now they may get a serious contender: spin-wave-based devices may just perform some information-processing tasks in a lot more efficient and practical way. In this article, we give an engineering perspective of the potential of spin-wave-based devices. After reviewing various flavors for spin-wave-based processing devices, we argue that the niche for spin-wave-based devices is low-power, compact and high-speed signal-processing devices, where most traditional electronics show poor performance.

  7. Wigner Ville Distribution in Signal Processing, using Scilab Environment

    Directory of Open Access Journals (Sweden)

    Petru Chioncel

    2011-01-01

    Full Text Available The Wigner Ville distribution offers a visual display of quantitative information about the way a signal’s energy is distributed in both, time and frequency. Through that, this distribution embodies the fundamentally concepts of the Fourier and time-domain analysis. The energy of the signal is distributed so that specific frequencies are localized in time by the group delay time and at specifics instants in time the frequency is given by the instantaneous frequency. The net positive volum of the Wigner distribution is numerically equal to the signal’s total energy. The paper shows the application of the Wigner Ville distribution, in the field of signal processing, using Scilab environment.

  8. CAS - CERN Accelerator School: Course on Digital Signal Processing

    CERN Document Server

    Digital Signal Processing; CAS 2007

    2008-01-01

    These proceedings present the lectures given at the twenty-first specialized course organized by the CERN Accelerator School (CAS), the topic being Digital Signal Processing. The course was held in Sigtuna, Sweden, from 31 May–9 June 2007. This is the first time this topic has been selected for a specialized course. Taking into account the number of related applications currently in use in accelerators around the world, it was recognized that such a topic should definitively be incorporated into the CAS series of specialized courses. The specific aim of the course was to introduce the participants to the use and programming of Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs) evaluation boards. The course consisted of lectures in the mornings covering fundamental background knowledge in mathematics, controls theory, design tools, programming hardware platforms, and implementation details. In the afternoons the students split into two groups with people working in pairs. One group w...

  9. Ultra-high-speed Optical Signal Processing using Silicon Photonics

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Ji, Hua; Jensen, Asger Sellerup

    with a photonic layer on top to interconnect them. For such systems, silicon is an attractive candidate enabling both electronic and photonic control. For some network scenarios, it may be beneficial to use optical on-chip packet switching, and for high data-density environments one may take advantage...... of the ultra-fast nonlinear response of silicon photonic waveguides. These chips offer ultra-broadband wavelength operation, ultra-high timing resolution and ultra-fast response, and when used appropriately offer energy-efficient switching. In this presentation we review some all-optical functionalities based...... on silicon photonics. In particular we use nano-engineered silicon waveguides (nanowires) [1] enabling efficient phasematched four-wave mixing (FWM), cross-phase modulation (XPM) or self-phase modulation (SPM) for ultra-high-speed optical signal processing of ultra-high bit rate serial data signals. We show...

  10. Autonomous data acquisition system for Paks NPP process noise signals

    International Nuclear Information System (INIS)

    Lipcsei, S.; Kiss, S.; Czibok, T.; Dezso, Z.; Horvath, Cs.

    2005-01-01

    A prototype of a new concept noise diagnostics data acquisition system has been developed recently to renew the aged present system. This new system is capable of collecting the whole available noise signal set simultaneously. Signal plugging and data acquisition are performed by autonomous systems (installed at each reactor unit) that are controlled through the standard plant network from a central computer installed at a suitable location. Experts can use this central unit to process and archive data series downloaded from the reactor units. This central unit also provides selected noise diagnostics information for other departments. The paper describes the hardware and software architecture of the new system in detail, emphasising the potential benefits of the new approach. (author)

  11. Conflict and disfluency as aversive signals: context-specific processing adjustments are modulated by affective location associations.

    Science.gov (United States)

    Dreisbach, Gesine; Reindl, Anna-Lena; Fischer, Rico

    2018-03-01

    Context-specific processing adjustments are one signature feature of flexible human action control. However, up to now the precise mechanisms underlying these adjustments are not fully understood. Here it is argued that aversive signals produced by conflict- or disfluency-experience originally motivate such context-specific processing adjustments. We tested whether the efficiency of the aversive conflict signal for control adaptation depends on the affective nature of the context it is presented in. In two experiments, high vs. low proportions of aversive signals (Experiment 1: conflict trials; Experiment 2: disfluent trials) were presented either above or below the screen center. This location manipulation was motivated by existing evidence that verticality is generally associated with affective valence with up being positive and down being negative. From there it was hypothesized that the aversive signals would lose their trigger function for processing adjustments when presented at the lower (i.e., more negative) location. This should then result in a reduced context-specific proportion effect when the high proportion of aversive signals was presented at the lower location. Results fully confirmed the predictions. In both experiments, the location-specific proportion effects were only present when the high proportion of aversive signals occurred at the more positive location above but were reduced (Experiment 1) or even eliminated (Experiment 2) when the high proportion occurred at the more negative location below. This interaction of processing adjustments with affective background contexts can thus be taken as further hint for an affective origin of control adaptations.

  12. Adapting the transtheoretical model of change to the bereavement process.

    Science.gov (United States)

    Calderwood, Kimberly A

    2011-04-01

    Theorists currently believe that bereaved people undergo some transformation of self rather than returning to their original state. To advance our understanding of this process, this article presents an adaptation of Prochaska and DiClemente's transtheoretical model of change as it could be applied to the journey that bereaved individuals experience. This theory is unique because it addresses attitudes, intentions, and behavioral processes at each stage; it allows for a focus on a broader range of emotions than just anger and depression; it allows for the recognition of two periods of regression during the bereavement process; and it adds a maintenance stage, which other theories lack. This theory can benefit bereaved individuals directly and through the increased awareness among counselors, family, friends, employers, and society at large. This theory may also be used as a tool for bereavement programs to consider whether they are meeting clients' needs throughout the transformation change bereavement process rather than only focusing on the initial stages characterized by intense emotion.

  13. Green Software Engineering Adaption In Requirement Elicitation Process

    Directory of Open Access Journals (Sweden)

    Umma Khatuna Jannat

    2015-08-01

    Full Text Available A recent technology investigates the role of concern in the environment software that is green software system. Now it is widely accepted that the green software can fit all process of software development. It is also suitable for the requirement elicitation process. Now a days software companies have used requirements elicitation techniques in an enormous majority. Because this process plays more and more important roles in software development. At the present time most of the requirements elicitation process is improved by using some techniques and tools. So that the intention of this research suggests to adapt green software engineering for the intention of existing elicitation technique and recommend suitable actions for improvement. This research being involved qualitative data. I used few keywords in my searching procedure then searched IEEE ACM Springer Elsevier Google scholar Scopus and Wiley. Find out articles which published in 2010 until 2016. Finding from the literature review Identify 15 traditional requirement elicitations factors and 23 improvement techniques to convert green engineering. Lastly The paper includes a squat review of the literature a description of the grounded theory and some of the identity issues related finding of the necessity for requirements elicitation improvement techniques.

  14. Hierarchical adaptive experimental design for Gaussian process emulators

    International Nuclear Information System (INIS)

    Busby, Daniel

    2009-01-01

    Large computer simulators have usually complex and nonlinear input output functions. This complicated input output relation can be analyzed by global sensitivity analysis; however, this usually requires massive Monte Carlo simulations. To effectively reduce the number of simulations, statistical techniques such as Gaussian process emulators can be adopted. The accuracy and reliability of these emulators strongly depend on the experimental design where suitable evaluation points are selected. In this paper a new sequential design strategy called hierarchical adaptive design is proposed to obtain an accurate emulator using the least possible number of simulations. The hierarchical design proposed in this paper is tested on various standard analytic functions and on a challenging reservoir forecasting application. Comparisons with standard one-stage designs such as maximin latin hypercube designs show that the hierarchical adaptive design produces a more accurate emulator with the same number of computer experiments. Moreover a stopping criterion is proposed that enables to perform the number of simulations necessary to obtain required approximation accuracy.

  15. Role of Nonneuronal TRPV4 Signaling in Inflammatory Processes.

    Science.gov (United States)

    Rajasekhar, Pradeep; Poole, Daniel P; Veldhuis, Nicholas A

    2017-01-01

    Transient receptor potential (TRP) ion channels are important signaling components in nociceptive and inflammatory pathways. This is attributed to their ability to function as polymodal sensors of environmental stimuli (chemical and mechanical) and as effector molecules in receptor signaling pathways. TRP vanilloid 4 (TRPV4) is a nonselective cation channel that is activated by multiple endogenous stimuli including shear stress, membrane stretch, and arachidonic acid metabolites. TRPV4 contributes to many important physiological processes and dysregulation of its activity is associated with chronic conditions of metabolism, inflammation, peripheral neuropathies, musculoskeletal development, and cardiovascular regulation. Mechanosensory and receptor- or lipid-mediated signaling functions of TRPV4 have historically been attributed to central and peripheral neurons. However, with the development of potent and selective pharmacological tools, transgenic mice and improved molecular and imaging techniques, many new roles for TRPV4 have been revealed in nonneuronal cells. In this chapter, we discuss these recent findings and highlight the need for greater characterization of TRPV4-mediated signaling in nonneuronal cell types that are either directly associated with neurons or indirectly control their excitability through release of sensitizing cellular factors. We address the integral role of these cells in sensory and inflammatory processes as well as their importance when considering undesirable on-target effects that may be caused by systemic delivery of TRPV4-selective pharmaceutical agents for treatment of chronic diseases. In future, this will drive a need for targeted drug delivery strategies to regulate such a diverse and promiscuous protein. © 2017 Elsevier Inc. All rights reserved.

  16. AUX: a scripting language for auditory signal processing and software packages for psychoacoustic experiments and education.

    Science.gov (United States)

    Kwon, Bomjun J

    2012-06-01

    This article introduces AUX (AUditory syntaX), a scripting syntax specifically designed to describe auditory signals and processing, to the members of the behavioral research community. The syntax is based on descriptive function names and intuitive operators suitable for researchers and students without substantial training in programming, who wish to generate and examine sound signals using a written script. In this article, the essence of AUX is discussed and practical examples of AUX scripts specifying various signals are illustrated. Additionally, two accompanying Windows-based programs and development libraries are described. AUX Viewer is a program that generates, visualizes, and plays sounds specified in AUX. AUX Viewer can also be used for class demonstrations or presentations. Another program, Psycon, allows a wide range of sound signals to be used as stimuli in common psychophysical testing paradigms, such as the adaptive procedure, the method of constant stimuli, and the method of adjustment. AUX Library is also provided, so that researchers can develop their own programs utilizing AUX. The philosophical basis of AUX is to separate signal generation from the user interface needed for experiments. AUX scripts are portable and reusable; they can be shared by other researchers, regardless of differences in actual AUX-based programs, and reused for future experiments. In short, the use of AUX can be potentially beneficial to all members of the research community-both those with programming backgrounds and those without.

  17. Processing-Efficient Distributed Adaptive RLS Filtering for Computationally Constrained Platforms

    Directory of Open Access Journals (Sweden)

    Noor M. Khan

    2017-01-01

    Full Text Available In this paper, a novel processing-efficient architecture of a group of inexpensive and computationally incapable small platforms is proposed for a parallely distributed adaptive signal processing (PDASP operation. The proposed architecture runs computationally expensive procedures like complex adaptive recursive least square (RLS algorithm cooperatively. The proposed PDASP architecture operates properly even if perfect time alignment among the participating platforms is not available. An RLS algorithm with the application of MIMO channel estimation is deployed on the proposed architecture. Complexity and processing time of the PDASP scheme with MIMO RLS algorithm are compared with sequentially operated MIMO RLS algorithm and liner Kalman filter. It is observed that PDASP scheme exhibits much lesser computational complexity parallely than the sequential MIMO RLS algorithm as well as Kalman filter. Moreover, the proposed architecture provides an improvement of 95.83% and 82.29% decreased processing time parallely compared to the sequentially operated Kalman filter and MIMO RLS algorithm for low doppler rate, respectively. Likewise, for high doppler rate, the proposed architecture entails an improvement of 94.12% and 77.28% decreased processing time compared to the Kalman and RLS algorithms, respectively.

  18. Applied Fourier analysis from signal processing to medical imaging

    CERN Document Server

    Olson, Tim

    2017-01-01

    The first of its kind, this focused textbook serves as a self-contained resource for teaching from scratch the fundamental mathematics of Fourier analysis and illustrating some of its most current, interesting applications, including medical imaging and radar processing. Developed by the author from extensive classroom teaching experience, it provides a breadth of theory that allows students to appreciate the utility of the subject, but at as accessible a depth as possible. With myriad applications included, this book can be adapted to a one or two semester course in Fourier Analysis or serve as the basis for independent study. Applied Fourier Analysis assumes no prior knowledge of analysis from its readers, and begins by making the transition from linear algebra to functional analysis. It goes on to cover basic Fourier series and Fourier transforms before delving into applications in sampling and interpolation theory, digital communications, radar processing, medical i maging, and heat and wave equations. Fo...

  19. Uncertainty during pain anticipation: the adaptive value of preparatory processes.

    Science.gov (United States)

    Seidel, Eva-Maria; Pfabigan, Daniela M; Hahn, Andreas; Sladky, Ronald; Grahl, Arvina; Paul, Katharina; Kraus, Christoph; Küblböck, Martin; Kranz, Georg S; Hummer, Allan; Lanzenberger, Rupert; Windischberger, Christian; Lamm, Claus

    2015-02-01

    Anticipatory processes prepare the organism for upcoming experiences. The aim of this study was to investigate neural responses related to anticipation and processing of painful stimuli occurring with different levels of uncertainty. Twenty-five participants (13 females) took part in an electroencephalography and functional magnetic resonance imaging (fMRI) experiment at separate times. A visual cue announced the occurrence of an electrical painful or nonpainful stimulus, delivered with certainty or uncertainty (50% chance), at some point during the following 15 s. During the first 2 s of the anticipation phase, a strong effect of uncertainty was reflected in a pronounced frontal stimulus-preceding negativity (SPN) and increased fMRI activation in higher visual processing areas. In the last 2 s before stimulus delivery, we observed stimulus-specific preparatory processes indicated by a centroparietal SPN and posterior insula activation that was most pronounced for the certain pain condition. Uncertain anticipation was associated with attentional control processes. During stimulation, the results revealed that unexpected painful stimuli produced the strongest activation in the affective pain processing network and a more pronounced offset-P2. Our results reflect that during early anticipation uncertainty is strongly associated with affective mechanisms and seems to be a more salient event compared to certain anticipation. During the last 2 s before stimulation, attentional control mechanisms are initiated related to the increased salience of uncertainty. Furthermore, stimulus-specific preparatory mechanisms during certain anticipation also shaped the response to stimulation, underlining the adaptive value of stimulus-targeted preparatory activity which is less likely when facing an uncertain event. © 2014 Wiley Periodicals, Inc.

  20. Adaptive model predictive process control using neural networks

    Science.gov (United States)

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  1. Adaptive Automatic Gauge Control of a Cold Strip Rolling Process

    Directory of Open Access Journals (Sweden)

    ROMAN, N.

    2010-02-01

    Full Text Available The paper tackles with thickness control structure of the cold rolled strips. This structure is based on the rolls position control of a reversible quarto rolling mill. The main feature of the system proposed in the paper consists in the compensation of the errors introduced by the deficient dynamics of the hydraulic servo-system used for the rolls positioning, by means of a dynamic compensator that approximates the inverse system of the servo-system. Because the servo-system is considered variant over time, an on-line identification of the servo-system and parameter adapting of the compensator are achieved. The results obtained by numerical simulation are presented together with the data taken from real process. These results illustrate the efficiency of the proposed solutions.

  2. Towards Measuring the Adaptability of an AO4BPEL Process

    OpenAIRE

    Botangen, Khavee Agustus; Yu, Jian; Sheng, Michael

    2017-01-01

    Adaptability is a significant property which enables software systems to continuously provide the required functionality and achieve optimal performance. The recognised importance of adaptability makes its evaluation an essential task. However, the various adaptability dimensions and implementation mechanisms make adaptive strategies difficult to evaluate. In service oriented computing, several frameworks that extend the WS-BPEL, the de facto standard in composing distributed business applica...

  3. Bacterial Biofilm Control by Perturbation of Bacterial Signaling Processes

    Directory of Open Access Journals (Sweden)

    Tim Holm Jakobsen

    2017-09-01

    Full Text Available The development of effective strategies to combat biofilm infections by means of either mechanical or chemical approaches could dramatically change today’s treatment procedures for the benefit of thousands of patients. Remarkably, considering the increased focus on biofilms in general, there has still not been invented and/or developed any simple, efficient and reliable methods with which to “chemically” eradicate biofilm infections. This underlines the resilience of infective agents present as biofilms and it further emphasizes the insufficiency of today’s approaches used to combat chronic infections. A potential method for biofilm dismantling is chemical interception of regulatory processes that are specifically involved in the biofilm mode of life. In particular, bacterial cell to cell signaling called “Quorum Sensing” together with intracellular signaling by bis-(3′-5′-cyclic-dimeric guanosine monophosphate (cyclic-di-GMP have gained a lot of attention over the last two decades. More recently, regulatory processes governed by two component regulatory systems and small non-coding RNAs have been increasingly investigated. Here, we review novel findings and potentials of using small molecules to target and modulate these regulatory processes in the bacterium Pseudomonas aeruginosa to decrease its pathogenic potential.

  4. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (United States)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  5. Use of fuzzy logic in signal processing and validation

    International Nuclear Information System (INIS)

    Heger, A.S.; Alang-Rashid, N.K.; Holbert, K.E.

    1993-01-01

    The advent of fuzzy logic technology has afforded another opportunity to reexamine the signal processing and validation process (SPV). The features offered by fuzzy logic can lend themselves to a more reliable and perhaps fault-tolerant approach to SPV. This is particularly attractive to complex system operations, where optimal control for safe operation depends on reliable input data. The reason for the use of fuzzy logic as the tool for SPV is its ability to transform information from the linguistic domain to a mathematical domain for processing and then transformation of its result back into the linguistic domain for presentation. To ensure the safe and optimal operation of a nuclear plant, for example, reliable and valid data must be available to the human and computer operators. Based on these input data, the operators determine the current state of the power plant and project corrective actions for future states. This determination is based on available data and the conceptual and mathematical models for the plant. A fault-tolerant SPV based on fuzzy logic can help the operators meet the objective of effective, efficient, and safe operation of the nuclear power plant. The ultimate product of this project will be a code that will assist plant operators in making informed decisions under uncertain conditions when conflicting signals may be present

  6. Photonic Ultra-Wideband 781.25-Mb/s Signal Generation and Transmission Incorporating Digital Signal Processing Detection

    DEFF Research Database (Denmark)

    Gibbon, Timothy Braidwood; Yu, Xianbin; Tafur Monroy, Idelfonso

    2009-01-01

    The generation of photonic ultra-wideband (UWB) impulse signals using an uncooled distributed-feedback laser is proposed. For the first time, we experimentally demonstrate bit-for-bit digital signal processing (DSP) bit-error-rate measurements for transmission of a 781.25-Mb/s photonic UWB signal...

  7. Information-educational environment with adaptive control of learning process

    Science.gov (United States)

    Modjaev, A. D.; Leonova, N. M.

    2017-01-01

    Recent years, a new scientific branch connected with the activities in social sphere management developing intensively and it is called "Social Cybernetics". In the framework of this scientific branch, theory and methods of management of social sphere are formed. Considerable attention is paid to the management, directly in real time. However, the decision of such management tasks is largely constrained by the lack of or insufficiently deep study of the relevant sections of the theory and methods of management. The article discusses the use of cybernetic principles in solving problems of control in social systems. Applying to educational activities a model of composite interrelated objects representing the behaviour of students at various stages of educational process is introduced. Statistical processing of experimental data obtained during the actual learning process is being done. If you increase the number of features used, additionally taking into account the degree and nature of variability of levels of current progress of students during various types of studies, new properties of students' grouping are discovered. L-clusters were identified, reflecting the behaviour of learners with similar characteristics during lectures. It was established that the characteristics of the clusters contain information about the dynamics of learners' behaviour, allowing them to be used in additional lessons. The ways of solving the problem of adaptive control based on the identified dynamic characteristics of the learners are planned.

  8. Digital signal processing in power electronics control circuits

    CERN Document Server

    Sozanski, Krzysztof

    2013-01-01

    Many digital control circuits in current literature are described using analog transmittance. This may not always be acceptable, especially if the sampling frequency and power transistor switching frequencies are close to the band of interest. Therefore, a digital circuit is considered as a digital controller rather than an analog circuit. This helps to avoid errors and instability in high frequency components. Digital Signal Processing in Power Electronics Control Circuits covers problems concerning the design and realization of digital control algorithms for power electronics circuits using

  9. Diffraction and signal processing experiments with a liquid crystal microdisplay

    International Nuclear Information System (INIS)

    MartInez, Jose Luis; Moreno, Ignacio; Ahouzi, Esmail

    2006-01-01

    In this work, we show some diffraction experiments performed with a liquid crystal display (LCD) that shows how useful this device can be to teach and experience diffraction optics and signal processing experiments. The LCD acts as a programmable pixelated diffractive mask. The Fourier spectrum of the image displayed in the LCD is visualized through a simple free propagation diffraction experiment. This optical system allows easy testing of different diffractive elements. As a demonstration we include experimental results with well-known diffractive elements like diffraction gratings or Fresnel lenses, and with more complicated elements like computer-generated holograms

  10. Diffraction and signal processing experiments with a liquid crystal microdisplay

    Energy Technology Data Exchange (ETDEWEB)

    MartInez, Jose Luis [Departamento de Ciencia y TecnologIa de Materiales, Universidad Miguel Hernandez de Elche, Alicante (Spain); Moreno, Ignacio [Departamento de Ciencia y TecnologIa de Materiales, Universidad Miguel Hernandez de Elche, Alicante (Spain); Ahouzi, Esmail [Institut National des Postes et Telecomunications (INTP), Madinat Al Irfane, Rabat (Morocco)

    2006-09-01

    In this work, we show some diffraction experiments performed with a liquid crystal display (LCD) that shows how useful this device can be to teach and experience diffraction optics and signal processing experiments. The LCD acts as a programmable pixelated diffractive mask. The Fourier spectrum of the image displayed in the LCD is visualized through a simple free propagation diffraction experiment. This optical system allows easy testing of different diffractive elements. As a demonstration we include experimental results with well-known diffractive elements like diffraction gratings or Fresnel lenses, and with more complicated elements like computer-generated holograms.

  11. Computational information geometry for image and signal processing

    CERN Document Server

    Critchley, Frank; Dodson, Christopher

    2017-01-01

    This book focuses on the application and development of information geometric methods in the analysis, classification and retrieval of images and signals. It provides introductory chapters to help those new to information geometry and applies the theory to several applications. This area has developed rapidly over recent years, propelled by the major theoretical developments in information geometry, efficient data and image acquisition and the desire to process and interpret large databases of digital information. The book addresses both the transfer of methodology to practitioners involved in database analysis and in its efficient computational implementation.

  12. Music Signal Processing Using Vector Product Neural Networks

    Science.gov (United States)

    Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

    2017-05-01

    We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

  13. Oversampling of digitized images. [effects on interpolation in signal processing

    Science.gov (United States)

    Fischel, D.

    1976-01-01

    Oversampling is defined as sampling with a device whose characteristic width is greater than the interval between samples. This paper shows why oversampling should be avoided and discusses the limitations in data processing if circumstances dictate that oversampling cannot be circumvented. Principally, oversampling should not be used to provide interpolating data points. Rather, the time spent oversampling should be used to obtain more signal with less relative error, and the Sampling Theorem should be employed to provide any desired interpolated values. The concepts are applicable to single-element and multielement detectors.

  14. Multilevel processes and cultural adaptation: Examples from past and present small-scale societies

    OpenAIRE

    Reyes-García, V.; Balbo, A. L.; Gomez-Baggethun, E.; Gueze, M.; Mesoudi, A.; Richerson, P.; Rubio-Campillo, X.; Ruiz-Mallén, I.; Shennan, S.

    2016-01-01

    Cultural adaptation has become central in the context of accelerated global change with authors increasingly acknowledging the importance of understanding multilevel processes that operate as adaptation takes place. We explore the importance of multilevel processes in explaining cultural adaptation by describing how processes leading to cultural (mis)adaptation are linked through a complex nested hierarchy, where the lower levels combine into new units with new organizations, functions, and e...

  15. Social signal processing for studying parent-infant interaction

    Directory of Open Access Journals (Sweden)

    Marie eAvril

    2014-12-01

    Full Text Available Studying early interactions is a core issue of infant development and psychopathology. Automatic social signal processing theoretically offers the possibility to extract and analyse communication by taking an integrative perspective, considering the multimodal nature and dynamics of behaviours (including synchrony. This paper proposes an explorative method to acquire and extract relevant social signals from a naturalistic early parent-infant interaction. An experimental setup is proposed based on both clinical and technical requirements. We extracted various cues from body postures and speech productions of partners using the IMI2S (Interaction, Multimodal Integration, and Social Signal Framework. Preliminary clinical and computational results are reported for two dyads (one pathological in a situation of severe emotional neglect and one normal control as an illustration of our cross-disciplinary protocol. The results from both clinical and computational analyses highlight similar differences: the pathological dyad shows dyssynchronic interaction led by the infant whereas the control dyad shows synchronic interaction and a smooth interactive dialog. The results suggest that the current method might be promising for future studies.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-12-31

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

  17. Performance bounds on micro-Doppler estimation and adaptive waveform design using OFDM signals

    Science.gov (United States)

    Sen, Satyabrata; Barhen, Jacob; Glover, Charles W.

    2014-05-01

    We analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a target having multiple rotating scatterers (e.g., rotor blades of a helicopter, propellers of a submarine). The presence of rotating scatterers introduces Doppler frequency modulation in the received signal by generating sidebands about the transmitted frequencies. This is called the micro-Doppler effects. The use of a frequency-diverse OFDM signal in this context enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. Therefore, to characterize the accuracy of micro-Doppler frequency estimation, we compute the Craḿer-Rao Bound (CRB) on the angular-velocity estimate of the target while considering the scatterer responses as deterministic but unknown nuisance parameters. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the transmitting OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations at different values of the signal-to-noise ratio (SNR) and the number of OFDM subcarriers. The CRB values not only decrease with the increase in the SNR values, but also reduce as we increase the number of subcarriers implying the significance of frequency-diverse OFDM waveforms. The improvement in estimation accuracy due to the adaptive waveform design is also numerically analyzed. Interestingly, we find that the relative decrease in the CRBs on the angular-velocity estimate is more pronounced for larger number of OFDM subcarriers.

  18. Performance Bounds on Micro-Doppler Estimation and Adaptive Waveform Design Using OFDM Signals

    Energy Technology Data Exchange (ETDEWEB)

    Sen, Satyabrata [ORNL; Barhen, Jacob [ORNL; Glover, Charles Wayne [ORNL

    2014-01-01

    We analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a target having multiple rotating scatterers (e.g., rotor blades of a helicopter, propellers of a submarine). The presence of rotating scatterers introduces Doppler frequency modulation in the received signal by generating sidebands about the transmitted frequencies. This is called the micro-Doppler effects. The use of a frequency-diverse OFDM signal in this context enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. Therefore, to characterize the accuracy of micro-Doppler frequency estimation, we compute the Cram er-Rao Bound (CRB) on the angular-velocity estimate of the target while considering the scatterer responses as deterministic but unknown nuisance parameters. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the transmitting OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations at different values of the signal-to-noise ratio (SNR) and the number of OFDM subcarriers. The CRB values not only decrease with the increase in the SNR values, but also reduce as we increase the number of subcarriers implying the significance of frequency-diverse OFDM waveforms. The improvement in estimation accuracy due to the adaptive waveform design is also numerically analyzed. Interestingly, we find that the relative decrease in the CRBs on the angular-velocity estimate is more pronounced for larger number of OFDM subcarriers.

  19. Signal processing for passive detection and classification of underwater acoustic signals

    Science.gov (United States)

    Chung, Kil Woo

    2011-12-01

    This dissertation examines signal processing for passive detection, classification and tracking of underwater acoustic signals for improving port security and the security of coastal and offshore operations. First, we consider the problem of passive acoustic detection of a diver in a shallow water environment. A frequency-domain multi-band matched-filter approach to swimmer detection is presented. The idea is to break the frequency contents of the hydrophone signals into multiple narrow frequency bands, followed by time averaged (about half of a second) energy calculation over each band. Then, spectra composed of such energy samples over the chosen frequency bands are correlated to form a decision variable. The frequency bands with highest Signal/Noise ratio are used for detection. The performance of the proposed approach is demonstrated for experimental data collected for a diver in the Hudson River. We also propose a new referenceless frequency-domain multi-band detector which, unlike other reference-based detectors, does not require a diver specific signature. Instead, our detector matches to a general feature of the diver spectrum in the high frequency range: the spectrum is roughly periodic in time and approximately flat when the diver exhales. The performance of the proposed approach is demonstrated by using experimental data collected from the Hudson River. Moreover, we present detection, classification and tracking of small vessel signals. Hydroacoustic sensors can be applied for the detection of noise generated by vessels, and this noise can be used for vessel detection, classification and tracking. This dissertation presents recent improvements aimed at the measurement and separation of ship DEMON (Detection of Envelope Modulation on Noise) acoustic signatures in busy harbor conditions. Ship signature measurements were conducted in the Hudson River and NY Harbor. The DEMON spectra demonstrated much better temporal stability compared with the full ship

  20. MUSIC-CONTENT-ADAPTIVE ROBUST PRINCIPAL COMPONENT ANALYSIS FOR A SEMANTICALLY CONSISTENT SEPARATION OF FOREGROUND AND BACKGROUND IN MUSIC AUDIO SIGNALS

    OpenAIRE

    Papadopoulos , Hélène; Ellis , Daniel P.W.

    2014-01-01

    International audience; Robust Principal Component Analysis (RPCA) is a technique to decompose signals into sparse and low rank components, and has recently drawn the attention of the MIR field for the problem of separating leading vocals from accompaniment, with appealing re-sults obtained on small excerpts of music. However, the perfor-mance of the method drops when processing entire music tracks. We present an adaptive formulation of RPCA that incorporates music content information to guid...