WorldWideScience

Sample records for time signal processing

  1. 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....

  2. 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....

  3. 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

  4. 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

  5. A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

    International Nuclear Information System (INIS)

    Monte, G E; Scarone, N C; Liscovsky, P O; Rotter, P

    2011-01-01

    This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.

  6. A novel time-domain signal processing algorithm for real time ventricular fibrillation detection

    Science.gov (United States)

    Monte, G. E.; Scarone, N. C.; Liscovsky, P. O.; Rotter S/N, P.

    2011-12-01

    This paper presents an application of a novel algorithm for real time detection of ECG pathologies, especially ventricular fibrillation. It is based on segmentation and labeling process of an oversampled signal. After this treatment, analyzing sequence of segments, global signal behaviours are obtained in the same way like a human being does. The entire process can be seen as a morphological filtering after a smart data sampling. The algorithm does not require any ECG digital signal pre-processing, and the computational cost is low, so it can be embedded into the sensors for wearable and permanent applications. The proposed algorithms could be the input signal description to expert systems or to artificial intelligence software in order to detect other pathologies.

  7. All-optical signal processing of OTDM and OFDM signals based on time-domain optical fourier transformation

    DEFF Research Database (Denmark)

    Galili, Michael; Guan, Pengyu; Lillieholm, Mads

    2017-01-01

    In the talk, we will review recent work on optical signal processing based on time lenses. Various applications of optical Fourier transformation for optical communications will be discussed.......In the talk, we will review recent work on optical signal processing based on time lenses. Various applications of optical Fourier transformation for optical communications will be discussed....

  8. Real-time radar signal processing using GPGPU (general-purpose graphic processing unit)

    Science.gov (United States)

    Kong, Fanxing; Zhang, Yan Rockee; Cai, Jingxiao; Palmer, Robert D.

    2016-05-01

    This study introduces a practical approach to develop real-time signal processing chain for general phased array radar on NVIDIA GPUs(Graphical Processing Units) using CUDA (Compute Unified Device Architecture) libraries such as cuBlas and cuFFT, which are adopted from open source libraries and optimized for the NVIDIA GPUs. The processed results are rigorously verified against those from the CPUs. Performance benchmarked in computation time with various input data cube sizes are compared across GPUs and CPUs. Through the analysis, it will be demonstrated that GPGPUs (General Purpose GPU) real-time processing of the array radar data is possible with relatively low-cost commercial GPUs.

  9. 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.

  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. Fast, multi-channel real-time processing of signals with microsecond latency using graphics processing units

    Energy Technology Data Exchange (ETDEWEB)

    Rath, N., E-mail: Nikolaus@rath.org; Levesque, J. P.; Mauel, M. E.; Navratil, G. A.; Peng, Q. [Department of Applied Physics and Applied Mathematics, Columbia University, 500 W 120th St, New York, New York 10027 (United States); Kato, S. [Department of Information Engineering, Nagoya University, Nagoya (Japan)

    2014-04-15

    Fast, digital signal processing (DSP) has many applications. Typical hardware options for performing DSP are field-programmable gate arrays (FPGAs), application-specific integrated DSP chips, or general purpose personal computer systems. This paper presents a novel DSP platform that has been developed for feedback control on the HBT-EP tokamak device. The system runs all signal processing exclusively on a Graphics Processing Unit (GPU) to achieve real-time performance with latencies below 8 μs. Signals are transferred into and out of the GPU using PCI Express peer-to-peer direct-memory-access transfers without involvement of the central processing unit or host memory. Tests were performed on the feedback control system of the HBT-EP tokamak using forty 16-bit floating point inputs and outputs each and a sampling rate of up to 250 kHz. Signals were digitized by a D-TACQ ACQ196 module, processing done on an NVIDIA GTX 580 GPU programmed in CUDA, and analog output was generated by D-TACQ AO32CPCI modules.

  12. Fast, multi-channel real-time processing of signals with microsecond latency using graphics processing units

    International Nuclear Information System (INIS)

    Rath, N.; Levesque, J. P.; Mauel, M. E.; Navratil, G. A.; Peng, Q.; Kato, S.

    2014-01-01

    Fast, digital signal processing (DSP) has many applications. Typical hardware options for performing DSP are field-programmable gate arrays (FPGAs), application-specific integrated DSP chips, or general purpose personal computer systems. This paper presents a novel DSP platform that has been developed for feedback control on the HBT-EP tokamak device. The system runs all signal processing exclusively on a Graphics Processing Unit (GPU) to achieve real-time performance with latencies below 8 μs. Signals are transferred into and out of the GPU using PCI Express peer-to-peer direct-memory-access transfers without involvement of the central processing unit or host memory. Tests were performed on the feedback control system of the HBT-EP tokamak using forty 16-bit floating point inputs and outputs each and a sampling rate of up to 250 kHz. Signals were digitized by a D-TACQ ACQ196 module, processing done on an NVIDIA GTX 580 GPU programmed in CUDA, and analog output was generated by D-TACQ AO32CPCI modules

  13. Microcomputer-based real-time optical signal processing system

    Science.gov (United States)

    Yu, F. T. S.; Cao, M. F.; Ludman, J. E.

    1986-01-01

    A microcomputer-based real-time programmable optical signal processing system utilizing a Magneto-Optic Spatial Light Modulator (MOSLM) and a Liquid Crystal Light Valve (LCLV) is described. This system can perform a myriad of complicated optical operations, such as image correlation, image subtraction, matrix multiplication and many others. The important assets of this proposed system must be the programmability and the capability of real-time addressing. The design specification and the progress toward practical implementation of this proposed system are discussed. Some preliminary experimental demonstrations are conducted. The feasible applications of this proposed system to image correlation for optical pattern recognition, image subtraction for IC chip inspection and matrix multiplication for optical computing are demonstrated.

  14. Time resolution improvement of Schottky CdTe PET detectors using digital signal processing

    International Nuclear Information System (INIS)

    Nakhostin, M.; Ishii, K.; Kikuchi, Y.; Matsuyama, S.; Yamazaki, H.; Torshabi, A. Esmaili

    2009-01-01

    We present the results of our study on the timing performance of Schottky CdTe PET detectors using the technique of digital signal processing. The coincidence signals between a CdTe detector (15x15x1 mm 3 ) and a fast liquid scintillator detector were digitized by a fast digital oscilloscope and analyzed. In the analysis, digital versions of the elements of timing circuits, including pulse shaper and time discriminator, were created and a digital implementation of the Amplitude and Rise-time Compensation (ARC) mode of timing was performed. Owing to a very fine adjustment of the parameters of timing measurement, a good time resolution of less than 9.9 ns (FWHM) at an energy threshold of 150 keV was achieved. In the next step, a new method of time pickoff for improvement of timing resolution without loss in the detection efficiency of CdTe detectors was examined. In the method, signals from a CdTe detector are grouped by their rise-times and different procedures of time pickoff are applied to the signals of each group. Then, the time pickoffs are synchronized by compensating the fixed time offset, caused by the different time pickoff procedures. This method leads to an improved time resolution of ∼7.2 ns (FWHM) at an energy threshold of as low as 150 keV. The methods presented in this work are computationally fast enough to be used for online processing of data in an actual PET system.

  15. Advanced Optical Signal Processing using Time Lens based Optical Fourier Transformation

    DEFF Research Database (Denmark)

    Guan, Pengyu; Røge, Kasper Meldgaard; Lillieholm, Mads

    2016-01-01

    An overview of recent progress on time lens based advanced optical signal processing is presented, with a special focus on all-optical ultrafast 640 Gbit/s all-channel serial-to-parallel conversion, and scalable WDM regeneration....

  16. Photonics-based real-time ultra-high-range-resolution radar with broadband signal generation and processing.

    Science.gov (United States)

    Zhang, Fangzheng; Guo, Qingshui; Pan, Shilong

    2017-10-23

    Real-time and high-resolution target detection is highly desirable in modern radar applications. Electronic techniques have encountered grave difficulties in the development of such radars, which strictly rely on a large instantaneous bandwidth. In this article, a photonics-based real-time high-range-resolution radar is proposed with optical generation and processing of broadband linear frequency modulation (LFM) signals. A broadband LFM signal is generated in the transmitter by photonic frequency quadrupling, and the received echo is de-chirped to a low frequency signal by photonic frequency mixing. The system can operate at a high frequency and a large bandwidth while enabling real-time processing by low-speed analog-to-digital conversion and digital signal processing. A conceptual radar is established. Real-time processing of an 8-GHz LFM signal is achieved with a sampling rate of 500 MSa/s. Accurate distance measurement is implemented with a maximum error of 4 mm within a range of ~3.5 meters. Detection of two targets is demonstrated with a range-resolution as high as 1.875 cm. We believe the proposed radar architecture is a reliable solution to overcome the limitations of current radar on operation bandwidth and processing speed, and it is hopefully to be used in future radars for real-time and high-resolution target detection and imaging.

  17. Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

    Science.gov (United States)

    Garcia-Belmonte, Germà

    2017-06-01

    Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor

  18. 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....

  19. Massively Parallel Signal Processing using the Graphics Processing Unit for Real-Time Brain-Computer Interface Feature Extraction.

    Science.gov (United States)

    Wilson, J Adam; Williams, Justin C

    2009-01-01

    The clock speeds of modern computer processors have nearly plateaued in the past 5 years. Consequently, neural prosthetic systems that rely on processing large quantities of data in a short period of time face a bottleneck, in that it may not be possible to process all of the data recorded from an electrode array with high channel counts and bandwidth, such as electrocorticographic grids or other implantable systems. Therefore, in this study a method of using the processing capabilities of a graphics card [graphics processing unit (GPU)] was developed for real-time neural signal processing of a brain-computer interface (BCI). The NVIDIA CUDA system was used to offload processing to the GPU, which is capable of running many operations in parallel, potentially greatly increasing the speed of existing algorithms. The BCI system records many channels of data, which are processed and translated into a control signal, such as the movement of a computer cursor. This signal processing chain involves computing a matrix-matrix multiplication (i.e., a spatial filter), followed by calculating the power spectral density on every channel using an auto-regressive method, and finally classifying appropriate features for control. In this study, the first two computationally intensive steps were implemented on the GPU, and the speed was compared to both the current implementation and a central processing unit-based implementation that uses multi-threading. Significant performance gains were obtained with GPU processing: the current implementation processed 1000 channels of 250 ms in 933 ms, while the new GPU method took only 27 ms, an improvement of nearly 35 times.

  20. 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.

  1. 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.

  2. Massively parallel signal processing using the graphics processing unit for real-time brain-computer interface feature extraction

    Directory of Open Access Journals (Sweden)

    J. Adam Wilson

    2009-07-01

    Full Text Available The clock speeds of modern computer processors have nearly plateaued in the past five years. Consequently, neural prosthetic systems that rely on processing large quantities of data in a short period of time face a bottleneck, in that it may not be possible to process all of the data recorded from an electrode array with high channel counts and bandwidth, such as electrocorticographic grids or other implantable systems. Therefore, in this study a method of using the processing capabilities of a graphics card (GPU was developed for real-time neural signal processing of a brain-computer interface (BCI. The NVIDIA CUDA system was used to offload processing to the GPU, which is capable of running many operations in parallel, potentially greatly increasing the speed of existing algorithms. The BCI system records many channels of data, which are processed and translated into a control signal, such as the movement of a computer cursor. This signal processing chain involves computing a matrix-matrix multiplication (i.e., a spatial filter, followed by calculating the power spectral density on every channel using an auto-regressive method, and finally classifying appropriate features for control. In this study, the first two computationally-intensive steps were implemented on the GPU, and the speed was compared to both the current implementation and a CPU-based implementation that uses multi-threading. Significant performance gains were obtained with GPU processing: the current implementation processed 1000 channels in 933 ms, while the new GPU method took only 27 ms, an improvement of nearly 35 times.

  3. A real time ECG signal processing application for arrhythmia detection on portable devices

    Science.gov (United States)

    Georganis, A.; Doulgeraki, N.; Asvestas, P.

    2017-11-01

    Arrhythmia describes the disorders of normal heart rate, which, depending on the case, can even be fatal for a patient with severe history of heart disease. The purpose of this work is to develop an application for heart signal visualization, processing and analysis in Android portable devices e.g. Mobile phones, tablets, etc. The application is able to retrieve the signal initially from a file and at a later stage this signal is processed and analysed within the device so that it can be classified according to the features of the arrhythmia. In the processing and analysing stage, different algorithms are included among them the Moving Average and Pan Tompkins algorithm as well as the use of wavelets, in order to extract features and characteristics. At the final stage, testing is performed by simulating our application in real-time records, using the TCP network protocol for communicating the mobile with a simulated signal source. The classification of ECG beat to be processed is performed by neural networks.

  4. PEANO, a toolbox for real-time process signal validation and estimation

    International Nuclear Information System (INIS)

    Fantoni, Paolo F.; Figedy, Stefan; Racz, Attila

    1998-02-01

    PEANO (Process Evaluation and Analysis by Neural Operators), a toolbox for real time process signal validation and condition monitoring has been developed. This system analyses the signals, which are e.g. the readings of process monitoring sensors, computes their expected values and alerts if real values are deviated from the expected ones more than limits allow. The reliability level of the current analysis is also produced. The system is based on neuro-fuzzy techniques. Artificial Neural Networks and Fuzzy Logic models can be combined to exploit learning and generalisation capability of the first technique with the approximate reasoning embedded in the second approach. Real-time process signal validation is an application field where the use of this technique can improve the diagnosis of faulty sensors and the identification of outliers in a robust and reliable way. This study implements a fuzzy and possibilistic clustering algorithm to classify the operating region where the validation process has to be performed. The possibilistic approach (rather than probabilistic) allows a ''don't know'' classification that results in a fast detection of unforeseen plant conditions or outliers. Specialised Artificial Neural Networks are used for the validation process, one for each fuzzy cluster in which the operating map has been divided. There are two main advantages in using this technique: the accuracy and generalisation capability is increased compared to the case of a single network working in the entire operating region, and the ability to identify abnormal conditions, where the system is not capable to operate with a satisfactory accuracy, is improved. This model has been tested in a simulated environment on a French PWR, to monitor safety-related reactor variables over the entire power-flow operating map. (author)

  5. PEANO, a toolbox for real-time process signal validation and estimation

    Energy Technology Data Exchange (ETDEWEB)

    Fantoni, Paolo F.; Figedy, Stefan; Racz, Attila

    1998-02-01

    PEANO (Process Evaluation and Analysis by Neural Operators), a toolbox for real time process signal validation and condition monitoring has been developed. This system analyses the signals, which are e.g. the readings of process monitoring sensors, computes their expected values and alerts if real values are deviated from the expected ones more than limits allow. The reliability level of the current analysis is also produced. The system is based on neuro-fuzzy techniques. Artificial Neural Networks and Fuzzy Logic models can be combined to exploit learning and generalisation capability of the first technique with the approximate reasoning embedded in the second approach. Real-time process signal validation is an application field where the use of this technique can improve the diagnosis of faulty sensors and the identification of outliers in a robust and reliable way. This study implements a fuzzy and possibilistic clustering algorithm to classify the operating region where the validation process has to be performed. The possibilistic approach (rather than probabilistic) allows a ''don't know'' classification that results in a fast detection of unforeseen plant conditions or outliers. Specialised Artificial Neural Networks are used for the validation process, one for each fuzzy cluster in which the operating map has been divided. There are two main advantages in using this technique: the accuracy and generalisation capability is increased compared to the case of a single network working in the entire operating region, and the ability to identify abnormal conditions, where the system is not capable to operate with a satisfactory accuracy, is improved. This model has been tested in a simulated environment on a French PWR, to monitor safety-related reactor variables over the entire power-flow operating map. (author)

  6. Time Lens based Optical Fourier Transformation for All-Optical Signal Processing of Spectrally-Efficient Data

    DEFF Research Database (Denmark)

    Guan, Pengyu; Røge, Kasper Meldgaard; Lillieholm, Mads

    2017-01-01

    We review recent progress in the use of time lens based optical Fourier transformation for advanced all-optical signal processing. A novel time lens based complete optical Fourier transformation (OFT) technique is introduced. This complete OFT is based on two quadratic phase-modulation stages using...... four-wave mixing (FWM), separated by a dispersive medium, which enables time-to-frequency and frequency-to-time conversions simultaneously, thus performing an exchange between the temporal and spectral profiles of the input signal. Using the proposed complete OFT, several advanced all-optical signal......, such as orthogonal frequency division multiplexing (OFDM), Nyquist wavelength-division multiplexing (Nyquist-WDM) and Nyquist optical time division multiplexing (Nyquist-OTDM) signals....

  7. Time lens based optical fourier transformation for advanced processing of spectrally-efficient OFDM and N-WDM signals

    DEFF Research Database (Denmark)

    Guan, Pengyu; Røge, Kasper Meldgaard; Morioka, Toshio

    2016-01-01

    We review recent progress in the use of time lens based optical Fourier transformation for advanced optical signal processing, with focus on all-optical generation, detection and format conversion of spectrally-efficient OFDM and N-WDM signals.......We review recent progress in the use of time lens based optical Fourier transformation for advanced optical signal processing, with focus on all-optical generation, detection and format conversion of spectrally-efficient OFDM and N-WDM signals....

  8. Real-time numerical processing for HPGE detectors signals

    International Nuclear Information System (INIS)

    Eric Barat; Thomas Dautremer; Laurent Laribiere; Jean Christophe Trama

    2006-01-01

    Full text of publication follows: Concerning the gamma spectrometry, technology progresses in the processor field makes very conceivable and attractive executing complex real-time digital process. Only some simplified and rigid treatments can be find in the market up to now. Indeed, the historical solution used for 50 years consists of performing a so-called 'cusp' filtering and disturbing the optimal shape in order to shrink and/or truncate it. This tuning largely determined by the input count rate (ICR) the user expects to measure is then a compromise between the resolution and the throughput. Because it is not possible to tune it for each pulse, that is a kind of 'leveling down' which is made: the energy of each pulse is not as well estimated as it could be. The new approach proposed here avoids totally this restricting hand tuning. The innovation lies in the modelling of the shot-noise signal as a Jump Markov Linear System. The jump is the occurrence of a pulse in the signal. From this model, we developed an algorithm which makes possible the on-line estimation of the energies without having to temporally enlarge the pulses as the cusp filter does. The algorithm first determines whether there is a pulse or not at each time, then conditionally to this information, it performs an optimal Kalman smoother. Thanks to this global optimization, this allows us to dramatically increase the compromise throughput versus resolution, gaining an important factor on a commercial device concerning the admissible ICR (more than 1 million counts per second admissible). A huge advantage of the absence of hand tuning is that the system accepts fluctuating ICR. To validate the concept we built a real time demonstrator. First, our equipment is composed of an electronic stage which prepared the signal coming from the preamplifier of the detector and optimized the signal-to-noise ratio. Then the signal is sampled at 10 MHz and the powerful of two Pentium running at 3 GHz is enough to

  9. 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.)

  10. 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...

  11. 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

  12. 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...

  13. 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....

  14. 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

  15. Noise and signal processing in a microstrip detector with a time variant readout system

    International Nuclear Information System (INIS)

    Cattaneo, P.W.

    1995-01-01

    This paper treats the noise and signal processing by a time variant filter in a microstrip detector. In particular, the noise sources in the detector-electronics chain and the signal losses that cause a substantial decrease of the original signal are thoroughly analyzed. This work has been motivated by the analysis of the data of the microstrip detectors designed for the ALEPH minivertex detector. Hence, even if the discussion will be kept as general as possible, concrete examples will be presented referring to the specific ALEPH design. (orig.)

  16. 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

  17. 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

  18. The Photoplethismographic Signal Processed with Nonlinear Time Series Analysis Tools

    International Nuclear Information System (INIS)

    Hernandez Caceres, Jose Luis; Hong, Rolando; Garcia Lanz, Abel; Garcia Dominguez, Luis; Cabannas, Karelia

    2001-01-01

    Finger photoplethismography (PPG) signals were submitted to nonlinear time series analysis. The applied analytical techniques were: (i) High degree polynomial fitting for baseline estimation; (ii) FFT analysis for estimating power spectra; (iii) fractal dimension estimation via the Higuchi's time-domain method, and (iv) kernel nonparametric estimation for reconstructing noise free-attractors and also for estimating signal's stochastic components

  19. 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

  20. 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

  1. Signal existence verification (SEV) for GPS low received power signal detection using the time-frequency approach.

    Science.gov (United States)

    Jan, Shau-Shiun; Sun, Chih-Cheng

    2010-01-01

    The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.

  2. Digital signal processing for the Johnson noise thermometry: a time series analysis of the Johnson noise

    International Nuclear Information System (INIS)

    Moon, Byung Soo; Hwang, In Koo; Chung, Chong Eun; Kwon, Kee Choon; David, E. H.; Kisner, R.A.

    2004-06-01

    In this report, we first proved that a random signal obtained by taking the sum of a set of signal frequency signals generates a continuous Markov process. We used this random signal to simulate the Johnson noise and verified that the Johnson noise thermometry can be used to improve the measurements of the reactor coolant temperature within an accuracy of below 0.14%. Secondly, by using this random signal we determined the optimal sampling rate when the frequency band of the Johnson noise signal is given. Also the results of our examination on how good the linearity of the Johnson noise is and how large the relative error of the temperature could become when the temperature increases are described. Thirdly, the results of our analysis on a set of the Johnson noise signal blocks taken from a simple electric circuit are described. We showed that the properties of the continuous Markov process are satisfied even when some channel noises are present. Finally, we describe the algorithm we devised to handle the problem of the time lag in the long-term average or the moving average in a transient state. The algorithm is based on the Haar wavelet and is to estimate the transient temperature that has much smaller time delay. We have shown that the algorithm can track the transient temperature successfully

  3. 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.

  4. 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).

  5. Acoustic wave focusing in complex media using Nonlinear Time Reversal coded signal processing

    Czech Academy of Sciences Publication Activity Database

    Dos Santos, S.; Dvořáková, Zuzana; Lints, M.; Kůs, V.; Salupere, A.; Převorovský, Zdeněk

    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 : ultrasonic testing (UT) * signal processing * TR- NEWS * nonlinear time reversal * NDT * nonlinear acoustics Subject RIV: BI - Acoustics http://www.ndt.net/events/ECNDT2014/app/content/Slides/590_DosSantos_Rev1.pdf

  6. 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.

  7. 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)

  8. 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.

  9. Real-time process signal validation based on neuro-fuzzy and possibilistic approach

    International Nuclear Information System (INIS)

    Figedy, S.; Fantoni, P.F.; Hoffmann, M.

    2001-01-01

    Real-time process signal validation is an application field where the use of fuzzy logic and Artificial Neural Networks can improve the diagnostics of faulty sensors and the identification of outliers in a robust and reliable way. This study implements a fuzzy and possibilistic clustering algorithm to classify the operating region where the validation process is to be performed. The possibilistic approach allows a fast detection of unforeseen plant conditions. Specialized Artificial Neural Networks are used, one for each fuzzy cluster. This offers two main advantages: the accuracy and generalization capability is increased compared to the case of a single network working in the entire operating region, and the ability to identify abnormal conditions, where the system is not capable to operate with a satisfactory accuracy, is improved. This system analyzes the signals, which are e.g. the readings of process monitoring sensors, computes their expected values and alerts if real values are deviated from the expected ones more than limits allow. The reliability level of the current analysis is also produced. This model has been tested on a simulated data from the PWR type of a nuclear power plant, to monitor safety-related reactor variables over the entire power-flow operating map and were installed in real conditions of BWR nuclear reactor. (Authors)

  10. 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.)

  11. SCOTT: A time and amplitude digitizer ASIC for PMT signal processing

    Science.gov (United States)

    Ferry, S.; Guilloux, F.; Anvar, S.; Chateau, F.; Delagnes, E.; Gautard, V.; Louis, F.; Monmarthe, E.; Le Provost, H.; Russo, S.; Schuller, J.-P.; Stolarczyk, Th.; Vallage, B.; Zonca, E.; KM3NeT Consortium

    2013-10-01

    SCOTT is an ASIC designed for the readout electronics of photomultiplier tubes developed for KM3NeT, the cubic-kilometer scale neutrino telescope in Mediterranean Sea. To digitize the PMT signals, the multi-time-over-threshold technique is used with up to 16 adjustable thresholds. Digital outputs of discriminators feed a circular sampling memory and a “first in first out” digital memory. A specific study has shown that five specifically chosen thresholds are suited to reach the required timing accuracy. A dedicated method based on the duration of the signal over a given threshold allows an equivalent timing precision at any charge. To verify that the KM3NeT requirements are fulfilled, this method is applied on PMT signals digitized by SCOTT.

  12. Multi-time-over-threshold technique for photomultiplier signal processing: Description and characterization of the SCOTT ASIC

    International Nuclear Information System (INIS)

    Ferry, S.; Guilloux, F.; Anvar, S.; Chateau, F.; Delagnes, E.; Gautard, V.; Louis, F.; Monmarthe, E.; Le Provost, H.; Russo, S.; Schuller, J.-P.; Stolarczyk, Th.; Vallage, B.; Zonca, E.

    2012-01-01

    KM3NeT aims to build a cubic-kilometer scale neutrino telescope in the Mediterranean Sea based on a 3D array of photomultiplier tubes. A dedicated ASIC, named SCOTT, has been developed for the readout electronics of the PMTs: it uses up to 16 adjustable thresholds to digitize the signals with the multi-time-over-threshold technique. Digital outputs of discriminators feed a circular sampling memory and a “first in first out” digital memory for derandomization. At the end of the data processing, the ASIC produces a digital waveform sampled at 800 MHz. A specific study was carried out to process PMT data and has showed that five specifically chosen thresholds are suited to reach the required timing precision. A dedicated method based on the duration of the signal over a given threshold allows an equivalent timing precision at any charge. A charge estimator using the information from the thresholds allows a charge determination within less than 20% up to 60 pe.

  13. Multi-time-over-threshold technique for photomultiplier signal processing: Description and characterization of the SCOTT ASIC

    Science.gov (United States)

    Ferry, S.; Guilloux, F.; Anvar, S.; Chateau, F.; Delagnes, E.; Gautard, V.; Louis, F.; Monmarthe, E.; Le Provost, H.; Russo, S.; Schuller, J.-P.; Stolarczyk, Th.; Vallage, B.; Zonca, E.; Representing the KM3NeT Consortium

    2012-12-01

    KM3NeT aims to build a cubic-kilometer scale neutrino telescope in the Mediterranean Sea based on a 3D array of photomultiplier tubes. A dedicated ASIC, named SCOTT, has been developed for the readout electronics of the PMTs: it uses up to 16 adjustable thresholds to digitize the signals with the multi-time-over-threshold technique. Digital outputs of discriminators feed a circular sampling memory and a “first in first out” digital memory for derandomization. At the end of the data processing, the ASIC produces a digital waveform sampled at 800 MHz. A specific study was carried out to process PMT data and has showed that five specifically chosen thresholds are suited to reach the required timing precision. A dedicated method based on the duration of the signal over a given threshold allows an equivalent timing precision at any charge. A charge estimator using the information from the thresholds allows a charge determination within less than 20% up to 60 pe.

  14. Virtual instrumentation technique used in the nuclear digital signal processing system design: Energy and time measurement tests

    International Nuclear Information System (INIS)

    Pechousek, J.; Prochazka, R.; Prochazka, V.; Frydrych, J.

    2011-01-01

    In this report, computer-based digital signal processing system with a 200 MS s -1 sampling digitizer is presented. Virtual instrumentation technique is used to easily develop a system which provides spectroscopy measurements such as amplitude and time signal analysis, with the time-of-flight facility. Several test measurements were performed to determine the characteristics of a system. The presented system may find its application in the coincidence measurement since the system is usable for different types of detectors and sensitive to decay lifetimes from tens of nanoseconds to seconds.

  15. 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...

  16. Broadband true time delay for microwave signal processing, using slow light based on stimulated Brillouin scattering in optical fibers.

    Science.gov (United States)

    Chin, Sanghoon; Thévenaz, Luc; Sancho, Juan; Sales, Salvador; Capmany, José; Berger, Perrine; Bourderionnet, Jérôme; Dolfi, Daniel

    2010-10-11

    We experimentally demonstrate a novel technique to process broadband microwave signals, using all-optically tunable true time delay in optical fibers. The configuration to achieve true time delay basically consists of two main stages: photonic RF phase shifter and slow light, based on stimulated Brillouin scattering in fibers. Dispersion properties of fibers are controlled, separately at optical carrier frequency and in the vicinity of microwave signal bandwidth. This way time delay induced within the signal bandwidth can be manipulated to correctly act as true time delay with a proper phase compensation introduced to the optical carrier. We completely analyzed the generated true time delay as a promising solution to feed phased array antenna for radar systems and to develop dynamically reconfigurable microwave photonic filters.

  17. Real-time measurement and control at JET signal processing and physics analysis for diagnostics

    International Nuclear Information System (INIS)

    Felton, R.; Joffrin, E.; Murari, A.

    2005-01-01

    To meet the requirements of the scientific programme, the EFDA JET real-time measurement and control project has developed an integrated set of real-time plasma measurements, experiment control and communication facilities. Traditional experiments collected instrument data during the plasma pulse and calculated physics data after the pulse. The challenge for continuous tokamak operation is to calculate the physics data in real-time, keeping up with the evolution of the plasma. In JET, many plasma diagnostics have been augmented with extra data acquisition and signal-processing systems so that they can both capture instrument data for conventional post-pulse analysis and calculate calibrated, validated physics results in real-time. During the pulse, the systems send sampled data sets into a network, which distributes the data to several destinations. The receiving systems may do further analysis, integrating data from several measurements, or may control the plasma scenario by heating or fuelling. The simplest real-time diagnostic systems apply scale factors to the signals, as with the electron cyclotron emission (ECE) diagnostic's 96 tuned radiometer channels, giving the electron temperature profile. In various spectroscopy diagnostics, spectral features are least-squares-fitted to measure spectra from several lines of sight, within 50 ms. Ion temperatures and rotation speed can be calculated from the line widths and shifts. For diagnostics using modulation techniques, the systems implement digital-signal processing phase trackers, lock-in amplifiers and filters, e.g., the far infrared (FIR) interferometer samples 15 channels at 400 kHz for 30 s, i.e., six million samples per second. Diagnostics have specific lines of sight, spatial channels, and various sampling rates. The heating/fuelling systems have relatively coarse spatial localisation. Analysis systems have been developed to integrate the basic physics data into smaller sets of controllable parameters on a

  18. Earthquake early warning system using real-time signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Leach, R.R. Jr.; Dowla, F.U.

    1996-02-01

    An earthquake warning system has been developed to provide a time series profile from which vital parameters such as the time until strong shaking begins, the intensity of the shaking, and the duration of the shaking, can be derived. Interaction of different types of ground motion and changes in the elastic properties of geological media throughout the propagation path result in a highly nonlinear function. We use neural networks to model these nonlinearities and develop learning techniques for the analysis of temporal precursors occurring in the emerging earthquake seismic signal. The warning system is designed to analyze the first-arrival from the three components of an earthquake signal and instantaneously provide a profile of impending ground motion, in as little as 0.3 sec after first ground motion is felt at the sensors. For each new data sample, at a rate of 25 samples per second, the complete profile of the earthquake is updated. The profile consists of a magnitude-related estimate as well as an estimate of the envelope of the complete earthquake signal. The envelope provides estimates of damage parameters, such as time until peak ground acceleration (PGA) and duration. The neural network based system is trained using seismogram data from more than 400 earthquakes recorded in southern California. The system has been implemented in hardware using silicon accelerometers and a standard microprocessor. The proposed warning units can be used for site-specific applications, distributed networks, or to enhance existing distributed networks. By producing accurate, and informative warnings, the system has the potential to significantly minimize the hazards of catastrophic ground motion. Detailed system design and performance issues, including error measurement in a simple warning scenario are discussed in detail.

  19. 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.

  20. 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

  1. 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...

  2. Research on control law accelerator of digital signal process chip TMS320F28035 for real-time data acquisition and processing

    Science.gov (United States)

    Zhao, Shuangle; Zhang, Xueyi; Sun, Shengli; Wang, Xudong

    2017-08-01

    TI C2000 series digital signal process (DSP) chip has been widely used in electrical engineering, measurement and control, communications and other professional fields, DSP TMS320F28035 is one of the most representative of a kind. When using the DSP program, need data acquisition and data processing, and if the use of common mode C or assembly language programming, the program sequence, analogue-to-digital (AD) converter cannot be real-time acquisition, often missing a lot of data. The control low accelerator (CLA) processor can run in parallel with the main central processing unit (CPU), and the frequency is consistent with the main CPU, and has the function of floating point operations. Therefore, the CLA coprocessor is used in the program, and the CLA kernel is responsible for data processing. The main CPU is responsible for the AD conversion. The advantage of this method is to reduce the time of data processing and realize the real-time performance of data acquisition.

  3. 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.

  4. 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.

  5. Digital signal processing for velocity measurements in dynamical material's behaviour studies

    International Nuclear Information System (INIS)

    Devlaminck, Julien; Luc, Jerome; Chanal, Pierre-Yves

    2014-01-01

    In this work, we describe different configurations of optical fiber interferometers (types Michelson and Mach-Zehnder) used to measure velocities during dynamical material's behaviour studies. We detail the algorithms of processing developed and optimized to improve the performance of these interferometers especially in terms of time and frequency resolutions. Three methods of analysis of interferometric signals were studied. For Michelson interferometers, the time-frequency analysis of signals by Short-Time Fourier Transform (STFT) is compared to a time-frequency analysis by Continuous Wavelet Transform (CWT). The results have shown that the CWT was more suitable than the STFT for signals with low signal-to-noise, and low velocity and high acceleration areas. For Mach- Zehnder interferometers, the measurement is carried out by analyzing the phase shift between three interferometric signals (Triature processing). These three methods of digital signal processing were evaluated, their measurement uncertainties estimated, and their restrictions or operational limitations specified from experimental results performed on a pulsed power machine. (authors)

  6. 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.

  7. 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...

  8. 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

  9. Constant versus variable response signal delays in speed--accuracy trade-offs: effects of advance preparation for processing time.

    Science.gov (United States)

    Miller, Jeff; Sproesser, Gudrun; Ulrich, Rolf

    2008-07-01

    In two experiments, we used response signals (RSs) to control processing time and trace out speed--accuracy trade-off(SAT) functions in a difficult perceptual discrimination task. Each experiment compared performance in blocks of trials with constant and, hence, temporally predictable RS lags against performance in blocks with variable, unpredictable RS lags. In both experiments, essentially equivalent SAT functions were observed with constant and variable RS lags. We conclude that there is little effect of advance preparation for a given processing time, suggesting that the discrimination mechanisms underlying SAT functions are driven solely by bottom-up information processing in perceptual discrimination tasks.

  10. Real-Time Signal Processing for Multiantenna Systems: Algorithms, Optimization, and Implementation on an Experimental Test-Bed

    Directory of Open Access Journals (Sweden)

    Haustein Thomas

    2006-01-01

    Full Text Available A recently realized concept of a reconfigurable hardware test-bed suitable for real-time mobile communication with multiple antennas is presented in this paper. We discuss the reasons and prerequisites for real-time capable MIMO transmission systems which may allow channel adaptive transmission to increase link stability and data throughput. We describe a concept of an efficient implementation of MIMO signal processing using FPGAs and DSPs. We focus on some basic linear and nonlinear MIMO detection and precoding algorithms and their optimization for a DSP target, and a few principal steps for computational performance enhancement are outlined. An experimental verification of several real-time MIMO transmission schemes at high data rates in a typical office scenario is presented and results on the achieved BER and throughput performance are given. The different transmission schemes used either channel state information at both sides of the link or at one side only (transmitter or receiver. Spectral efficiencies of more than 20 bits/s/Hz and a throughput of more than 150 Mbps were shown with a single-carrier transmission. The experimental results clearly show the feasibility of real-time high data rate MIMO techniques with state-of-the-art hardware and that more sophisticated baseband signal processing will be an essential part of future communication systems. A discussion on implementation challenges towards future wireless communication systems supporting higher data rates (1 Gbps and beyond or high mobility concludes the paper.

  11. Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation †

    Directory of Open Access Journals (Sweden)

    Ali Ibrahim

    2017-03-01

    Full Text Available Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g., robots, biomedical instrumentation, and replacement prosthetic devices. An essential task of the electronic skin system is to locally process the tactile data and send structured information either to mimic human skin or to respond to the application demands. The electronic skin must be fabricated together with an embedded electronic system which has the role of acquiring the tactile data, processing, and extracting structured information. On the other hand, processing tactile data requires efficient methods to extract meaningful information from raw sensor data. Machine learning represents an effective method for data analysis in many domains: it has recently demonstrated its effectiveness in processing tactile sensor data. In this framework, this paper presents the implementation of digital signal processing based on FPGAs for tactile data processing. It provides the implementation of a tensorial kernel function for a machine learning approach. Implementation results are assessed by highlighting the FPGA resource utilization and power consumption. Results demonstrate the feasibility of the proposed implementation when real-time classification of input touch modalities are targeted.

  12. Real time loss detection for SNM in process

    International Nuclear Information System (INIS)

    Candy, J.V.; Dunn, D.R.; Gavel, D.T.

    1980-01-01

    This paper discusses the basis of a design for real time special nuclear material (SNM) loss detectors. The design utilizes process measurements and signal processing techniques to produce a timely estimate of material loss. A state estimator is employed as the primary signal processing algorithm. Material loss is indicated by changes in the states or process innovations (residuals). The design philosophy is discussed in the context of these changes

  13. 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.

  14. Energy Efficient Scheduling of Real Time Signal Processing Applications through Combined DVFS and DPM

    OpenAIRE

    Nogues , Erwan; Pelcat , Maxime; Menard , Daniel; Mercat , Alexandre

    2016-01-01

    International audience; This paper proposes a framework to design energy efficient signal processing systems. The energy efficiency is provided by combining Dynamic Frequency and Voltage Scaling (DVFS) and Dynamic Power Management (DPM). The framework is based on Synchronous Dataflow (SDF) modeling of signal processing applications. A transformation to a single rate form is performed to expose the application parallelism. An automated scheduling is then performed, minimizing the constraint of...

  15. 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.

  16. 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...

  17. Sensor response time calculation with no stationary signals from a Nuclear Power Plant

    International Nuclear Information System (INIS)

    Vela, O.; Vallejo, I.

    1998-01-01

    Protection systems in a Nuclear Power Plant have to response in a specific time fixed by design requirements. This time includes the event detection (sensor delay) and the actuation time system. This time is obtained in refuel simulating the physics event, which trigger the protection system, with an electric signal and measuring the protection system actuation time. Nowadays sensor delay is calculated with noise analysis techniques. The signals are measured in Control Room during the normal operation of the Plant, decreasing both the cost in time and personal radioactive exposure. The noise analysis techniques require stationary signals but normally the data collected are mixed with process signals that are no stationary. This work shows the signals processing to avoid no-stationary components using conventional filters and new wavelets analysis. (Author) 2 refs

  18. 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.

  19. pySPACE-a signal processing and classification environment in Python.

    Science.gov (United States)

    Krell, Mario M; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H; Kirchner, Elsa A; Kirchner, Frank

    2013-01-01

    In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries.

  20. Pulse shaping for all-optical signal processing of ultra-high bit rate serial data signals

    DEFF Research Database (Denmark)

    Palushani, Evarist

    The following thesis concerns pulse shaping and optical waveform manipulation for all-optical signal processing of ultra-high bit rate serial data signals, including generation of optical pulses in the femtosecond regime, serial-to-parallel conversion and terabaud coherent optical time division...

  1. 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.

  2. 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.

  3. Data acquisition and real-time signal processing of plasma diagnostics on ASDEX Upgrade using LabVIEW RT

    International Nuclear Information System (INIS)

    Giannone, L.; Cerna, M.; Cole, R.; Fitzek, M.; Kallenbach, A.; Lueddecke, K.; McCarthy, P.J.; Scarabosio, A.; Schneider, W.; Sips, A.C.C.; Treutterer, W.; Vrancic, A.; Wenzel, L.; Yi, H.; Behler, K.; Eich, T.; Eixenberger, H.; Fuchs, J.C.; Haas, G.; Lexa, G.

    2010-01-01

    The existing VxWorks real-time system for the position and shape control in ASDEX Upgrade has been extended to calculate magnetic flux surfaces in real-time using a multi-core PCI Express system running LabVIEW RT 8.6. real-time signal processing of bolometers and manometers is performed with the on-board FPGA to calculate the measured radiated power flux and particle flux respectively from the raw data. Radiation feedback experiments use halo current measurements from the outer divertor with real-time median filter pre-processing to remove the excursions produced by ELMs. Integration of these plasma diagnostics into the control system by the exchange of XML sheets for communicating the real-time variables to be produced and consumed is in operation. Reflective memory and UDP are employed by the LabVIEW RT plasma diagnostics to communicate with the control system and other plasma diagnostics in a multi-platform real-time network.

  4. Data acquisition and real-time signal processing of plasma diagnostics on ASDEX Upgrade using LabVIEW RT

    Energy Technology Data Exchange (ETDEWEB)

    Giannone, L., E-mail: Louis.Giannone@ipp.mpg.d [Max-Planck-Institut fuer Plasmaphysik, EURATOM-IPP Association, D-85748 Garching (Germany); Cerna, M. [National Instruments, Austin, TX 78759-3504 (United States); Cole, R.; Fitzek, M. [Unlimited Computer Systems GmbH, 82393 Iffeldorf (Germany); Kallenbach, A. [Max-Planck-Institut fuer Plasmaphysik, EURATOM-IPP Association, D-85748 Garching (Germany); Lueddecke, K. [Unlimited Computer Systems GmbH, 82393 Iffeldorf (Germany); McCarthy, P.J. [Department of Physics, University College Cork, Association EURATOM-DCU, Cork (Ireland); Scarabosio, A.; Schneider, W.; Sips, A.C.C.; Treutterer, W. [Max-Planck-Institut fuer Plasmaphysik, EURATOM-IPP Association, D-85748 Garching (Germany); Vrancic, A.; Wenzel, L.; Yi, H. [National Instruments, Austin, TX 78759-3504 (United States); Behler, K.; Eich, T.; Eixenberger, H.; Fuchs, J.C.; Haas, G.; Lexa, G. [Max-Planck-Institut fuer Plasmaphysik, EURATOM-IPP Association, D-85748 Garching (Germany)

    2010-07-15

    The existing VxWorks real-time system for the position and shape control in ASDEX Upgrade has been extended to calculate magnetic flux surfaces in real-time using a multi-core PCI Express system running LabVIEW RT 8.6. real-time signal processing of bolometers and manometers is performed with the on-board FPGA to calculate the measured radiated power flux and particle flux respectively from the raw data. Radiation feedback experiments use halo current measurements from the outer divertor with real-time median filter pre-processing to remove the excursions produced by ELMs. Integration of these plasma diagnostics into the control system by the exchange of XML sheets for communicating the real-time variables to be produced and consumed is in operation. Reflective memory and UDP are employed by the LabVIEW RT plasma diagnostics to communicate with the control system and other plasma diagnostics in a multi-platform real-time network.

  5. Enhancement of the automatic ultrasonic signal processing system using digital technology

    International Nuclear Information System (INIS)

    Koo, In Soo; Park, H. Y.; Suh, Y. S.; Kim, D. Hoon; Huh, S.; Sung, S. H.; Jang, G. S.; Ryoo, S. G.; Choi, J. H.; Kim, Y. H.; Lee, J. C.; Kim, D. Hyun; Park, H. J.; Kim, Y. C.; Lee, J. P.; Park, C. H.; Kim, M. S.

    1999-12-01

    The objective of this study is to develop the automatic ultrasonic signal processing system which can be used in the inspection equipment to assess the integrity of the reactor vessel by enhancing the performance of the ultrasonic signal processing system. Main activities of this study divided into three categories such as the development of the circuits for generating ultrasonic signal and receiving the signal from the inspection equipment, the development of signal processing algorithm and H/W of the data processing system, and the development of the specification for application programs and system S/W for the analysis and evaluation computer. The results of main activities are as follows 1) the design of the ultrasonic detector and the automatic ultrasonic signal processing system by using the investigation of the state-of-the-art technology in the inside and outside of the country. 2) the development of H/W and S/W of the data processing system based on the results. Especially, the H/W of the data processing system, which have both advantages of digital and analog controls through the real-time digital signal processing, was developed using the DSP which can process the digital signal in the real-time, and was developed not only firmware of the data processing system in order for the peripherals but also the test algorithm of specimen for the calibration. The application programs and the system S/W of the analysis/evaluation computer were developed. Developed equipment was verified by the performance test. Based on developed prototype for the automatic ultrasonic signal processing system, the localization of the overall ultrasonic inspection equipment for nuclear industries would be expected through the further studies of the H/W establishment of real applications, developing the S/W specification of the analysis computer. (author)

  6. 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, ...

  7. 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

  8. Fetal Cardiac Doppler Signal Processing Techniques: Challenges and Future Research Directions

    Directory of Open Access Journals (Sweden)

    Saeed Abdulrahman Alnuaimi

    2017-12-01

    Full Text Available The fetal Doppler Ultrasound (DUS is commonly used for monitoring fetal heart rate and can also be used for identifying the event timings of fetal cardiac valve motions. In early-stage fetuses, the detected Doppler signal suffers from noise and signal loss due to the fetal movements and changing fetal location during the measurement procedure. The fetal cardiac intervals, which can be estimated by measuring the fetal cardiac event timings, are the most important markers of fetal development and well-being. To advance DUS-based fetal monitoring methods, several powerful and well-advanced signal processing and machine learning methods have recently been developed. This review provides an overview of the existing techniques used in fetal cardiac activity monitoring and a comprehensive survey on fetal cardiac Doppler signal processing frameworks. The review is structured with a focus on their shortcomings and advantages, which helps in understanding fetal Doppler cardiogram signal processing methods and the related Doppler signal analysis procedures by providing valuable clinical information. Finally, a set of recommendations are suggested for future research directions and the use of fetal cardiac Doppler signal analysis, processing, and modeling to address the underlying challenges.

  9. pySPACE - A Signal Processing and Classification Environment in Python

    Directory of Open Access Journals (Sweden)

    Mario Michael Krell

    2013-12-01

    Full Text Available In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace, signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG. The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries.

  10. 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

  11. 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.

  12. 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.

  13. 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...

  14. Design of signal reception and processing system of embedded ultrasonic endoscope

    Science.gov (United States)

    Li, Ming; Yu, Feng; Zhang, Ruiqiang; Li, Yan; Chen, Xiaodong; Yu, Daoyin

    2009-11-01

    Embedded Ultrasonic Endoscope, based on embedded microprocessor and embedded real-time operating system, sends a micro ultrasonic probe into coelom through the biopsy channel of the Electronic Endoscope to get the fault histology features of digestive organs by rotary scanning, and acquires the pictures of the alimentary canal mucosal surface. At the same time, ultrasonic signals are processed by signal reception and processing system, forming images of the full histology of the digestive organs. Signal Reception and Processing System is an important component of Embedded Ultrasonic Endoscope. However, the traditional design, using multi-level amplifiers and special digital processing circuits to implement signal reception and processing, is no longer satisfying the standards of high-performance, miniaturization and low power requirements that embedded system requires, and as a result of the high noise that multi-level amplifier brought, the extraction of small signal becomes hard. Therefore, this paper presents a method of signal reception and processing based on double variable gain amplifier and FPGA, increasing the flexibility and dynamic range of the Signal Reception and Processing System, improving system noise level, and reducing power consumption. Finally, we set up the embedded experiment system, using a transducer with the center frequency of 8MHz to scan membrane samples, and display the image of ultrasonic echo reflected by each layer of membrane, with a frame rate of 5Hz, verifying the correctness of the system.

  15. A FPGA-based signal processing unit for a GEM array detector

    International Nuclear Information System (INIS)

    Yen, W.W.; Chou, H.P.

    2013-06-01

    in the present study, a signal processing unit for a GEM one-dimensional array detector is presented to measure the trajectory of photoelectrons produced by cosmic X-rays. The present GEM array detector system has 16 signal channels. The front-end unit provides timing signals from trigger units and energy signals from charge sensitive amplifies. The prototype of the processing unit is implemented using commercial field programmable gate array circuit boards. The FPGA based system is linked to a personal computer for testing and data analysis. Tests using simulated signals indicated that the FPGA-based signal processing unit has a good linearity and is flexible for parameter adjustment for various experimental conditions (authors)

  16. 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

  17. 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 ...

  18. 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.

  19. Real time pressure signal system for a rotary engine

    Science.gov (United States)

    Rice, W. J. (Inventor)

    1984-01-01

    A real-time IMEP signal which is a composite of those produced in any one chamber of a three-lobed rotary engine is developed by processing the signals of four transducers positioned in a Wankel engine housing such that the rotor overlaps two of the transducers for a brief period during each cycle. During the overlap period of any two transducers, their output is compared and sampled for 10 microseconds per 0.18 degree of rotation by a sampling switch and capacitive circuit. When the switch is closed, the instantaneous difference between the value of the transducer signals is provided while with the switch open the average difference is produced. This combined signal, along with the original signal of the second transducer, is fed through a multiplexer to a pressure output terminal. Timing circuits, controlled by a crank angle encoder on the engine, determine which compared transducer signals are applied to the output terminal and when, as well as the open and closed periods of the switches.

  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. 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.

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. All-optical microwave signal processing based on optical phase modulation

    Science.gov (United States)

    Zeng, Fei

    This thesis presents a theoretical and experimental study of optical phase modulation and its applications in all-optical microwave signal processing, which include all-optical microwave filtering, all-optical microwave mixing, optical code-division multiple-access (CDMA) coding, and ultrawideband (UWB) signal generation. All-optical microwave signal processing can be considered as the use of opto-electronic devices and systems to process microwave signals in the optical domain, which provides several significant advantages such as low loss, low dispersion, light weight, high time bandwidth products, and immunity to electromagnetic interference. In conventional approaches, the intensity of an optical carrier is modulated by a microwave signal based on direct modulation or external modulation. The intensity-modulated optical signal is then fed to a photonic circuit or system to achieve specific signal processing functionalities. The microwave signal being processed is usually obtained based on direct detection, i.e., an opto-electronic conversion by use of a photodiode. In this thesis, the research efforts are focused on the optical phase modulation and its applications in all-optical microwave signal processing. To avoid using coherent detection which is complicated and costly, simple and effective phase modulation to intensity modulation (PM-IM) conversion schemes are pursued. Based on a theoretical study of optical phase modulation, two approaches to achieving PM-IM conversions are proposed. In the first approach, the use of chromatic dispersion induced by a dispersive device to alter the phase relationships among the sidebands and the optical carrier of a phase-modulated optical signal to realize PM-IM conversion is investigated. In the second approach, instead of using a dispersive device, the PM-IM conversion is realized based on optical frequency discrimination implemented using an optical filter. We show that the proposed PM-IM conversion schemes can be

  9. 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...

  10. Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis

    Directory of Open Access Journals (Sweden)

    SU, H.

    2011-08-01

    Full Text Available Border effects are very common in many finite signals analysis and processing approaches using convolution operation. Alleviating the border effects that can occur in the processing of finite-length signals using wavelet transform is considered in this paper. Traditional methods for alleviating the border effects are suitable to compression or coding applications. We propose an algorithm based on Fourier series which is proved to be appropriate to the application of time-frequency analysis of nonlinear signals. Fourier series extension method preserves the time-varying characteristics of the signals. A modified signal duration expression for measuring the extent of border effects region is presented. The proposed algorithm is confirmed to be efficient to alleviate the border effects in comparison to the current methods through the numerical examples.

  11. Stability of the Filter Equation for a Time-Dependent Signal on Rd

    International Nuclear Information System (INIS)

    Stannat, Wilhelm

    2005-01-01

    Stability of the pathwise filter equation for a time-dependent signal process induced by a d-dimensional stochastic differential equation and a linear observation is studied, using a variational approach. A lower bound for the rate of stability is identified in terms of the mass-gap of a parabolic ground state transform associated with the generator of the signal process and the square of the observation. The lower bound can be easily calculated a priori and provides hints on how precisely to measure the signal in order to reach a certain rate of stability. Ergodicity of the signal process is not needed

  12. High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

    International Nuclear Information System (INIS)

    Hadjiloucas, S; Walker, G C; Bowen, J W; Becerra, V M; Zafiropoulos, A; Galvao, R K H

    2009-01-01

    Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

  13. High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

    Energy Technology Data Exchange (ETDEWEB)

    Hadjiloucas, S; Walker, G C; Bowen, J W; Becerra, V M [Cybernetics, School of Systems Engineering, University of Reading, RG6 6AY (United Kingdom); Zafiropoulos, A [Biosystems Engineering Department, School of Agricultural Technology, Technological Educational Institute of Larissa, 411 10, Larissa (Greece); Galvao, R K H, E-mail: s.hadjiloucas@reading.ac.u [Divisao de Engenharia Eletronica, Instituto Tecnologico de Aeronautica, Sao Jose dos Campos, SP, 12228-900 Brazil (Brazil)

    2009-08-01

    Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

  14. Nonlinear Estimation of Discrete-Time Signals Under Random Observation Delay

    International Nuclear Information System (INIS)

    Caballero-Aguila, R.; Jimenez-Lopez, J. D.; Hermoso-Carazo, A.; Linares-Perez, J.; Nakamori, S.

    2008-01-01

    This paper presents an approximation to the nonlinear least-squares estimation problem of discrete-time stochastic signals using nonlinear observations with additive white noise which can be randomly delayed by one sampling time. The observation delay is modelled by a sequence of independent Bernoulli random variables whose values, zero or one, indicate that the real observation arrives on time or it is delayed and, hence, the available measurement to estimate the signal is not up-to-date. Assuming that the state-space model generating the signal is unknown and only the covariance functions of the processes involved in the observation equation are ready for use, a filtering algorithm based on linear approximations of the real observations is proposed.

  15. Real-time Nyquist signaling with dynamic precision and flexible non-integer oversampling.

    Science.gov (United States)

    Schmogrow, R; Meyer, M; Schindler, P C; Nebendahl, B; Dreschmann, M; Meyer, J; Josten, A; Hillerkuss, D; Ben-Ezra, S; Becker, J; Koos, C; Freude, W; Leuthold, J

    2014-01-13

    We demonstrate two efficient processing techniques for Nyquist signals, namely computation of signals using dynamic precision as well as arbitrary rational oversampling factors. With these techniques along with massively parallel processing it becomes possible to generate and receive high data rate Nyquist signals with flexible symbol rates and bandwidths, a feature which is highly desirable for novel flexgrid networks. We achieved maximum bit rates of 252 Gbit/s in real-time.

  16. Implementation and optimization of ultrasound signal processing algorithms on mobile GPU

    Science.gov (United States)

    Kong, Woo Kyu; Lee, Wooyoul; Kim, Kyu Cheol; Yoo, Yangmo; Song, Tai-Kyong

    2014-03-01

    A general-purpose graphics processing unit (GPGPU) has been used for improving computing power in medical ultrasound imaging systems. Recently, a mobile GPU becomes powerful to deal with 3D games and videos at high frame rates on Full HD or HD resolution displays. This paper proposes the method to implement ultrasound signal processing on a mobile GPU available in the high-end smartphone (Galaxy S4, Samsung Electronics, Seoul, Korea) with programmable shaders on the OpenGL ES 2.0 platform. To maximize the performance of the mobile GPU, the optimization of shader design and load sharing between vertex and fragment shader was performed. The beamformed data were captured from a tissue mimicking phantom (Model 539 Multipurpose Phantom, ATS Laboratories, Inc., Bridgeport, CT, USA) by using a commercial ultrasound imaging system equipped with a research package (Ultrasonix Touch, Ultrasonix, Richmond, BC, Canada). The real-time performance is evaluated by frame rates while varying the range of signal processing blocks. The implementation method of ultrasound signal processing on OpenGL ES 2.0 was verified by analyzing PSNR with MATLAB gold standard that has the same signal path. CNR was also analyzed to verify the method. From the evaluations, the proposed mobile GPU-based processing method has no significant difference with the processing using MATLAB (i.e., PSNRe., 11.31). From the mobile GPU implementation, the frame rates of 57.6 Hz were achieved. The total execution time was 17.4 ms that was faster than the acquisition time (i.e., 34.4 ms). These results indicate that the mobile GPU-based processing method can support real-time ultrasound B-mode processing on the smartphone.

  17. The Real-time Frequency Spectrum Analysis of Neutron Pulse Signal Series

    International Nuclear Information System (INIS)

    Tang Yuelin; Ren Yong; Wei Biao; Feng Peng; Mi Deling; Pan Yingjun; Li Jiansheng; Ye Cenming

    2009-01-01

    The frequency spectrum analysis of neutron pulse signal is a very important method in nuclear stochastic signal processing Focused on the special '0' and '1' of neutron pulse signal series, this paper proposes new rotation-table and realizes a real-time frequency spectrum algorithm under 1G Hz sample rate based on PC with add, address and SSE. The numerical experimental results show that under the count rate of 3X10 6 s -1 , this algorithm is superior to FFTW in time-consumption and can meet the real-time requirement of frequency spectrum analysis. (authors)

  18. 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.

  19. Optimum short-time polynomial regression for signal analysis

    Indian Academy of Sciences (India)

    A Sreenivasa Murthy

    the Proceedings of European Signal Processing Conference. (EUSIPCO) 2008. ... In a seminal paper, Savitzky and Golay [4] showed that short-time polynomial modeling is ...... We next consider a linearly frequency-modulated chirp with an exponentially .... 1 http://www.physionet.org/physiotools/matlab/ECGwaveGen/.

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

    Science.gov (United States)

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

    2004-10-01

    may be programmed under existing real-time operating systems using parallel processing software libraries, resulting in highly portable code that can be rapidly migrated to new platforms as processor technology evolves. Use of standardized development tools and 3rd party software upgrades are enabled as well as rapid upgrade of processing components as improved algorithms are developed. The resulting weapon system will have a superior processing capability over a custom approach at the time of deployment as a result of a shorter development cycles and use of newer technology. The signal processing computer may be upgraded over the lifecycle of the weapon system, and can migrate between weapon system variants enabled by modification simplicity. This paper presents a reference design using the new approach that utilizes an Altivec PowerPC parallel COTS platform. It uses a VxWorks-based real-time operating system (RTOS), and application code developed using an efficient parallel vector library (PVL). A quantification of computing requirements and demonstration of interceptor algorithm operating on this real-time platform are provided.

  1. 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

  2. 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

  3. 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.

  4. 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.

  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. 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/...

  7. 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.

  8. Signal processing techniques for damage detection with piezoelectric wafer active sensors and embedded ultrasonic structural radar

    Science.gov (United States)

    Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

    2004-07-01

    Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.

  9. Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

    Science.gov (United States)

    Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.

    2011-03-01

    Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.

  10. 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.

  11. 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)

  12. 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

  13. 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.

  14. Analysis of Seasonal Signal in GPS Short-Baseline Time Series

    Science.gov (United States)

    Wang, Kaihua; Jiang, Weiping; Chen, Hua; An, Xiangdong; Zhou, Xiaohui; Yuan, Peng; Chen, Qusen

    2018-04-01

    Proper modeling of seasonal signals and their quantitative analysis are of interest in geoscience applications, which are based on position time series of permanent GPS stations. Seasonal signals in GPS short-baseline (paper, to better understand the seasonal signal in GPS short-baseline time series, we adopted and processed six different short-baselines with data span that varies from 2 to 14 years and baseline length that varies from 6 to 1100 m. To avoid seasonal signals that are overwhelmed by noise, each of the station pairs is chosen with significant differences in their height (> 5 m) or type of the monument. For comparison, we also processed an approximately zero baseline with a distance of pass-filtered (BP) noise is valid for approximately 40% of the baseline components, and another 20% of the components can be best modeled by a combination of the first-order Gauss-Markov (FOGM) process plus white noise (WN). The TEM displacements are then modeled by considering the monument height of the building structure beneath the GPS antenna. The median contributions of TEM to the annual amplitude in the vertical direction are 84% and 46% with and without additional parts of the monument, respectively. Obvious annual signals with amplitude > 0.4 mm in the horizontal direction are observed in five short-baselines, and the amplitudes exceed 1 mm in four of them. These horizontal seasonal signals are likely related to the propagation of daily/sub-daily TEM displacement or other signals related to the site environment. Mismodeling of the tropospheric delay may also introduce spurious seasonal signals with annual amplitudes of 5 and 2 mm, respectively, for two short-baselines with elevation differences greater than 100 m. The results suggest that the monument height of the additional part of a typical GPS station should be considered when estimating the TEM displacement and that the tropospheric delay should be modeled cautiously, especially with station pairs with

  15. 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.

  16. 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.

  17. Digital signals processing using non-linear orthogonal transformation in frequency domain

    Directory of Open Access Journals (Sweden)

    Ivanichenko E.V.

    2017-12-01

    Full Text Available The rapid progress of computer technology in recent decades led to a wide introduction of methods of digital information processing practically in all fields of scientific research. In this case, among various applications of computing one of the most important places is occupied by digital processing systems signals (DSP that are used in data processing remote solution tasks of navigation of aerospace and marine objects, communications, radiophysics, digital optics and in a number of other applications. Digital Signal Processing (DSP is a dynamically developing an area that covers both technical and software tools. Related areas for digital signal processing are theory information, in particular, the theory of optimal signal reception and theory pattern recognition. In the first case, the main problem is signal extraction against a background of noise and interference of a different physical nature, and in the second - automatic recognition, i.e. classification and signal identification. In the digital processing of signals under a signal, we mean its mathematical description, i.e. a certain real function, containing information on the state or behavior of a physical system under an event that can be defined on a continuous or discrete space of time variation or spatial coordinates. In the broad sense, DSP systems mean a complex algorithmic, hardware and software. As a rule, systems contain specialized technical means of preliminary (or primary signal processing and special technical means for secondary processing of signals. Means of pretreatment are designed to process the original signals observed in general case against a background of random noise and interference of a different physical nature and represented in the form of discrete digital samples, for the purpose of detecting and selection (selection of the useful signal and evaluation characteristics of the detected signal. A new method of digital signal processing in the frequency

  18. Digital Signal Processing for a Sliceable Transceiver for Optical Access Networks

    DEFF Research Database (Denmark)

    Saldaña Cercos, Silvia; Wagner, Christoph; Vegas Olmos, Juan José

    2015-01-01

    Methods to upgrade the network infrastructure to cope with current traffic demands has attracted increasing research efforts. A promising alternative is signal slicing. Signal slicing aims at re-using low bandwidth equipment to satisfy high bandwidth traffic demands. This technique has been used...... also for implementing full signal path symmetry in real-time oscilloscopes to provide performance and signal fidelity (i.e. lower noise and jitter). In this paper the key digital signal processing (DSP) subsystems required to achieve signal slicing are surveyed. It also presents, for the first time...... penalty is reported for 10 Gbps. Power savings of the order of hundreds of Watts can be obtained when using signal slicing as an alternative to 10 Gbps implemented access networks....

  19. 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....

  20. 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

  1. Discrete time process algebra and the semantics of SDL

    NARCIS (Netherlands)

    J.A. Bergstra; C.A. Middelburg; Y.S. Usenko (Yaroslav)

    1998-01-01

    htmlabstractWe present an extension of discrete time process algebra with relative timing where recursion, propositional signals and conditions, a counting process creation operator, and the state operator are combined. Except the counting process creation operator, which subsumes the original

  2. Constant versus variable response signal delays in speed accuracy trade-offs : Effects of advance preparation for processing time

    OpenAIRE

    Miller, Jeff; Sproesser, Gudrun; Ulrich, Rolf

    2008-01-01

    In two experiments, we used response signals (RSs) to control processing time and trace out speed accuracy trade-off (SAT) functions in a difficult perceptual discrimination task. Each experiment compared performance in blocks of trials with constant and, hence, temporally predictable RS lags against performance in blocks with variable, unpredictable RS lags. In both experiments, essentially equivalent SAT functions were observed with constant and variable RS lags. We conclude that there is l...

  3. Improvement of the characterization of ultrasonic data by means of digital signal processing

    International Nuclear Information System (INIS)

    Bieth, M.; Romy, D.; Weigel, D.

    1985-01-01

    The digital signal processing method for averaging using minima developed by Framatome allows to improve signal-to-noise ratio up to 7 dB during ultrasonic testing of cast stainless steel structures (primary pipes of PWR power plants). Application of digital signal processing to industrial testing conditions requires the availability of a fast analog-digital converter capable of real time processings which has been developed by CGR [fr

  4. 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...

  5. 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

  6. Self-Sustained Operation of Radiation Detectors Based on Embedded Signal Processing

    International Nuclear Information System (INIS)

    Talnishnikh, Elena; Paganini, Lucia; Stegenga, Jan; Woertche, Heinrich; Limburgy, Han

    2013-06-01

    Radiation detectors featuring long term stability, self-sustained operation and low power consumption are crucial for long-term environmental monitoring (e.g. nuclear waste disposals and mining activities) and provide enhanced applications of nuclear fingerprinting e.g. in farming and geological surveying. INCAS3 is developing a compact modular system consisting of four functional modules, namely analogue conditioning and signal digitalization, dead-time-free real-time signal processing, embedded high level analysis of the processed signal, and wireless communication. The modules are organized such that they can be interchanged and modified independently. For the input module one can choose an ADC sampling frequency to be either 100 MHz with 14 bit precision or 1 GHz with reduced precision (10 bit). The main focus of the signal processing section, based on an FPGA, is on providing dead-time-free signal handling in real time. Other useful features such as base line correction, pulse shape analysis (energy, decay and arrival time) are being developed as (VHDL) library functions. Additional modules, e.g. anomaly detection in the incoming signal, pile-up correction if operated at high rates and advanced signal shape processing, can be included in the processing if required and can be applied to autonomously generate the information necessary to control the sensor parameters and stabilize energy spectra and sensitivity. At present we operate the system in conjunction with inorganic scintillators (NaI, CsI) read out by a photomultiplier in order to provide a system capable of long term quantification of nuclear contaminations in natural environments. The underlying technology is based on detecting natural or anthropogenic gamma radiation and generating corresponding energy spectra in real time. The generated spectra are analyzed either in a standard way by any suitable desktop software in a lab or, as it is described in this work, by the ENSA (Embedded Nuclear Spectra

  7. 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.

  8. 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)

  9. IDP++: signal and image processing algorithms in C++ version 4.1

    International Nuclear Information System (INIS)

    Lehman, S.K.

    1996-11-01

    IDP++ (Image and Data Processing in C++) is a collection of signal and image processing algorithms written in C++. It is a compiled signal processing environment which supports four data types of up to four dimensions. It is developed within Lawrence Livermore National Laboratory's Image and Data Processing group as a partial replacement for View. IDP ++ takes advantage of the latest, implemented and actually working, object-oriented compiler technology to provide 'information hiding.' Users need only know C, not C++. Signals are treated like any other variable with a defined set of operators and functions in an intuitive manner. IDP++ is designed for real-time environment where interpreted processing packages are less efficient. IDP++ exists for both SUNs and Silicon Graphics using their most current compilers

  10. All-Optical Signal Processing for 640 Gbit/s Applications

    DEFF Research Database (Denmark)

    Mulvad, Hans Christian Hansen

    2008-01-01

    This thesis concerns all-optical signal processing technologies for ultra-high serial data rates up to 640 Gbit/s. Firstly, time-division add-drop multiplexing at 640 Gbit/s is demonstrated for the first time using two different fibre-based switching techniques. Secondly, a novel principle for po...

  11. Optical Time-Division Multiplexing of 10 Gbit/s Ethernet Signals Synchronized by All-Optical Signal Processing Based on a Time-Lens

    DEFF Research Database (Denmark)

    Areal, Janaina Laguardia

    This Thesis presents 3 years work of an optical circuit that performs both pulse compression and frame synchronization and retiming. Our design aims at directly multiplexing several 10G Ethernet data packets (frames) to a high-speed OTDM link. This scheme is optically transparent and does not req...... coupler, completing the OTDM signal generation. We demonstrate the effectiveness of the design by laboratory experiments and simulations with VPI and MatLab....... not require clock recovery, resulting in a potentially very efficient solution. The scheme uses a time-lens, implemented through a sinusoidally driven optical phase modulation, combined with a linear dispersion element. As time-lenses are also used for pulse compression, we design the circuit also to perform...

  12. 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

  13. Noise-assisted data processing with empirical mode decomposition in biomedical signals.

    Science.gov (United States)

    Karagiannis, Alexandros; Constantinou, Philip

    2011-01-01

    In this paper, a methodology is described in order to investigate the performance of empirical mode decomposition (EMD) in biomedical signals, and especially in the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with white Gaussian noise are employed and time series of various lengths are processed with EMD in order to extract the intrinsic mode functions (IMFs). A statistical significance test is implemented for the identification of IMFs with high-level noise components and their exclusion from denoising procedures. Simulation campaign results reveal that a decrease of processing time is accomplished with the introduction of preprocessing stage, prior to the application of EMD in biomedical time series. Furthermore, the variation in the number of IMFs according to the type of the preprocessing stage is studied as a function of SNR and time-series length. The application of the methodology in MIT-BIH ECG records is also presented in order to verify the findings in real ECG signals.

  14. 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)

  15. An X-ray CCD signal generator with true random arrival time

    International Nuclear Information System (INIS)

    Huo Jia; Xu Yuming; Chen Yong; Cui Weiwei; Li Wei; Zhang Ziliang; Han Dawei; Wang Yusan; Wang Juan

    2011-01-01

    An FPGA-based true random signal generator with adjustable amplitude and exponential distribution of time interval is presented. Since traditional true random number generators (TRNG) are resource costly and difficult to transplant, we employed a method of random number generation based on jitter and phase noise in ring oscillators formed by gates in an FPGA. In order to improve the random characteristics, a combination of two different pseudo-random processing circuits is used for post processing. The effects of the design parameters, such as sample frequency are discussed. Statistical tests indicate that the generator can well simulate the timing behavior of random signals with Poisson distribution. The X-ray CCD signal generator will be used in debugging the CCD readout system of the Low Energy X-ray Instrument onboard the Hard X-ray Modulation Telescope (HXMT). (authors)

  16. CERN Technical Training 2003: Learning for the LHC ! DISP-2003 - Digital Signal Processing

    CERN Multimedia

    2003-01-01

    DISP-2003 - Digital Signal Processing DISP-2003 is a two-term course given by CERN and University of Lausanne (UNIL) experts within the framework of the Technical Training Programme. The course will review the current techniques dealing with Digital Signal Processing, and it is intended for an audience who work or will work on digital signal processing aspects, and who need an introductory or refresher/update course. The course will be in English, with question and answers also in French. Spring 2 Term: DISP-2003: Advanced Digital Signal Processing 30 April 2003 - 21 May 2003, 4 lectures, Wednesdays afternoon (attendance cost: 40.- CHF, registration required) Lecturers: Léonard Studer, UNIL; Laurent Deniau, AT-MTM; Elena Wildner, AT-MAS Programme: Intelligent signal processing (ISP). Non-linear time series analysis. Image processing. Wavelets. (Basic concepts and definitions have been introduced during the previous Spring 1 Term: DISP-2003: Introduction to Digital Signal Processing). DISP-2003 is open...

  17. Measurement of gas phase characteristics using new monofiber optical probes and real time signal processing

    International Nuclear Information System (INIS)

    Cartellier, A.

    1998-01-01

    Single optical or impedance phase detection probes are able to measure gas velocities provided that their sensitive length L is accurately known. In this paper, it is shown that L can be controlled during the manufacture of optical probes. Beside, for a probe geometry in the form of a cone + a cylinder + a cone, the corresponding rise time / velocity correlation becomes weakly sensitive to uncontrollable parameter such as the angle of impact on the interface. A real time signal processing performing phase detection as well as velocity measurements is described. Since its sensitivity to the operator inputs is less than the reproducibility of measurements, it is a fairly objective tool. Qualifications achieved in air/water flows with various optical probes demonstrate that the void fraction is detected with a relative error less than 10 %. For bubbly flows, the gas flux is accurate within ±10%, but this uncertainty increases when large bubbles are present in the flow. (author)

  18. Signal Tracking Beyond the Time Resolution of an Atomic Sensor by Kalman Filtering

    Science.gov (United States)

    Jiménez-Martínez, Ricardo; Kołodyński, Jan; Troullinou, Charikleia; Lucivero, Vito Giovanni; Kong, Jia; Mitchell, Morgan W.

    2018-01-01

    We study causal waveform estimation (tracking) of time-varying signals in a paradigmatic atomic sensor, an alkali vapor monitored by Faraday rotation probing. We use Kalman filtering, which optimally tracks known linear Gaussian stochastic processes, to estimate stochastic input signals that we generate by optical pumping. Comparing the known input to the estimates, we confirm the accuracy of the atomic statistical model and the reliability of the Kalman filter, allowing recovery of waveform details far briefer than the sensor's intrinsic time resolution. With proper filter choice, we obtain similar benefits when tracking partially known and non-Gaussian signal processes, as are found in most practical sensing applications. The method evades the trade-off between sensitivity and time resolution in coherent sensing.

  19. 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.

  20. Real Time Phase Noise Meter Based on a Digital Signal Processor

    Science.gov (United States)

    Angrisani, Leopoldo; D'Arco, Mauro; Greenhall, Charles A.; Schiano Lo Morille, Rosario

    2006-01-01

    A digital signal-processing meter for phase noise measurement on sinusoidal signals is dealt with. It enlists a special hardware architecture, made up of a core digital signal processor connected to a data acquisition board, and takes advantage of a quadrature demodulation-based measurement scheme, already proposed by the authors. Thanks to an efficient measurement process and an optimized implementation of its fundamental stages, the proposed meter succeeds in exploiting all hardware resources in such an effective way as to gain high performance and real-time operation. For input frequencies up to some hundreds of kilohertz, the meter is capable both of updating phase noise power spectrum while seamlessly capturing the analyzed signal into its memory, and granting as good frequency resolution as few units of hertz.

  1. The CaloRIC ASIC: Signal Processing for High Granularity Calorimeter

    International Nuclear Information System (INIS)

    Royer, L; Manen, S; Soumpholphakdy, X; Bonnard, J; Gay, P

    2013-01-01

    A readout ASIC called CaloRIC, has been developed to fulfil the signal processing requirements for the Silicon-Tungsten (Si-W) electromagnetic calorimeter of the International Linear Collider (ILC). This ASIC performs the complete processing of the signal delivered by the Si-PIN diode of the detector: charge sensitive amplification, shaping, analog memorization and digitization. Measurements show a global integral non-linearity better than 0.2% for low energy particles, and limited to 2% for high energy particles. The measured Equivalent Noise Charge (ENC) is evaluated at 0.6 fC, which corresponds to 1/6 times the signal released by a Minimum Ionizing Particle (MIP). With the timing sequence of the ILC, the power consumption of the complete channel is evaluated at 43 μW using a power pulsing. A new ASIC (CaloRIC 4 ch) with four improved readout channels has been designed and is ready for manufacturing.

  2. Calibration of Galileo signals for time metrology.

    Science.gov (United States)

    Defraigne, Pascale; Aerts, Wim; Cerretto, Giancarlo; Cantoni, Elena; Sleewaegen, Jean-Marie

    2014-12-01

    Using global navigation satellite system (GNSS) signals for accurate timing and time transfer requires the knowledge of all electric delays of the signals inside the receiving system. GNSS stations dedicated to timing or time transfer are classically calibrated only for Global Positioning System (GPS) signals. This paper proposes a procedure to determine the hardware delays of a GNSS receiving station for Galileo signals, once the delays of the GPS signals are known. This approach makes use of the broadcast satellite inter-signal biases, and is based on the ionospheric delay measured from dual-frequency combinations of GPS and Galileo signals. The uncertainty on the so-determined hardware delays is estimated to 3.7 ns for each isolated code in the L5 frequency band, and 4.2 ns for the ionosphere-free combination of E1 with a code of the L5 frequency band. For the calibration of a time transfer link between two stations, another approach can be used, based on the difference between the common-view time transfer results obtained with calibrated GPS data and with uncalibrated Galileo data. It is shown that the results obtained with this approach or with the ionospheric method are equivalent.

  3. 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...

  4. 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

  5. Harnessing mode-selective nonlinear optics for on-chip multi-channel all-optical signal processing

    Directory of Open Access Journals (Sweden)

    Ming Ma

    2016-11-01

    Full Text Available All-optical signal processing based on nonlinear optical effects allows for the realization of important functions in telecommunications including wavelength conversion, optical multiplexing/demultiplexing, Fourier transformation, and regeneration, amongst others, on ultrafast time scales to support high data rate transmission. In integrated photonic subsystems, the majority of all-optical signal processing systems demonstrated to date typically process only a single channel at a time or perform a single processing function, which imposes a serious limitation on the functionality of integrated solutions. Here, we demonstrate how nonlinear optical effects can be harnessed in a mode-selective manner to perform simultaneous multi-channel (two and multi-functional optical signal processing (i.e., regenerative wavelength conversion in an integrated silicon photonic device. This approach, which can be scaled to a higher number of channels, opens up a new degree of freedom for performing a broad range of multi-channel nonlinear optical signal processing functions using a single integrated photonic device.

  6. A user configurable data acquisition and signal processing system for high-rate, high channel count applications

    International Nuclear Information System (INIS)

    Salim, Arwa; Crockett, Louise; McLean, John; Milne, Peter

    2012-01-01

    Highlights: ► The development of a new digital signal processing platform is described. ► The system will allow users to configure the real-time signal processing through software routines. ► The architecture of the DRUID system and signal processing elements is described. ► A prototype of the DRUID system has been developed for the digital chopper-integrator. ► The results of acquisition on 96 channels at 500 kSamples/s per channel are presented. - Abstract: Real-time signal processing in plasma fusion experiments is required for control and for data reduction as plasma pulse times grow longer. The development time and cost for these high-rate, multichannel signal processing systems can be significant. This paper proposes a new digital signal processing (DSP) platform for the data acquisition system that will allow users to easily customize real-time signal processing systems to meet their individual requirements. The D-TACQ reconfigurable user in-line DSP (DRUID) system carries out the signal processing tasks in hardware co-processors (CPs) implemented in an FPGA, with an embedded microprocessor (μP) for control. In the fully developed platform, users will be able to choose co-processors from a library and configure programmable parameters through the μP to meet their requirements. The DRUID system is implemented on a Spartan 6 FPGA, on the new rear transition module (RTM-T), a field upgrade to existing D-TACQ digitizers. As proof of concept, a multiply-accumulate (MAC) co-processor has been developed, which can be configured as a digital chopper-integrator for long pulse magnetic fusion devices. The DRUID platform allows users to set options for the integrator, such as the number of masking samples. Results from the digital integrator are presented for a data acquisition system with 96 channels simultaneously acquiring data at 500 kSamples/s per channel.

  7. 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)

  8. Si(Li) x-ray spectrometer with signal processing system based on digital filtering

    International Nuclear Information System (INIS)

    Lakatos, Tamas

    1985-01-01

    A new signal processing system is under development at ATOMKI, Debrecen, Hungary, based on digital filtering by a microprocessor. The advantages of the new method are summarized. Dead time can be decreased and the speed of signal processing can be increased. Computer simulations verified the theoretical conclusions. (D.Gy.)

  9. 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...

  10. 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...

  11. Time-frequency analysis of fusion plasma signals beyond the short-time Fourier transform paradigm: An overview

    International Nuclear Information System (INIS)

    Bizarro, Joao P.S.; Figueiredo, Antonio C.A.

    2008-01-01

    Performing a time-frequency (t-f) analysis on actual magnetic pick-up coil data from the JET tokamak, a comparison is presented between the spectrogram and the Wigner and Choi-Williams distributions. Whereas the former, which stems from the short-time Fourier transform and has been the work-horse for t-f signal processing, implies an unavoidable trade-off between time and frequency resolutions, the latter two belong to a later generation of distributions that yield better, if not optimal joint t-f localization. Topics addressed include signal representation in the t-f plane, frequency identification and evolution, instantaneous-frequency estimation, and amplitude tracking

  12. Optical signal processing up to 1.28 Tbits/s

    DEFF Research Database (Denmark)

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

    2009-01-01

    Techniques for 640 Gbit/s optical signal processing are described, including demultiplexing, clock recovery, transmission, wavelength conversion, add-drop multiplexing, and timing-jitter tolerance. Demultiplexing at 1.28 Tbit/s is presented, with preliminary results for 1.28 Tbit/s transmission....

  13. 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.

  14. 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

  15. Predict or classify: The deceptive role of time-locking in brain signal classification

    Science.gov (United States)

    Rusconi, Marco; Valleriani, Angelo

    2016-06-01

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal.

  16. 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

  17. CERN Technical Training 2003: Learning for the LHC! DISP-2003 - Digital Signal Processing

    CERN Multimedia

    2003-01-01

    DISP-2003 is a two-term course given by CERN and University of Lausanne (UNIL) experts within the framework of the Technical Training Programme. The course will review the current techniques dealing with Digital Signal Processing, and it is intended for an audience who work or will work on digital signal processing aspects, and who need an introductory or refresher/update course. The course will be in English, with question and answers also in French. Spring 2 Term: DISP-2003: Advanced Digital Signal Processing 30 April 2003 - 21 May 2003, 4 lectures, Wednesdays afternoon. Attendance cost: 40.- CHF, registration required. Lecturers: Léonard Studer, UNIL; Laurent Deniau, AT-MTM; Elena Wildner, AT-MAS. Programme: Intelligent signal processing (ISP). Non-linear time series analysis. Image processing. Wavelets. Basic concepts and definitions have been introduced during the previous Spring 1 Term: DISP-2003: Introduction to Digital Signal Processing. DISP-2003 is open to all people interested, but registrat...

  18. Properties of an improved Gabor wavelet transform and its applications to seismic signal processing and interpretation

    Science.gov (United States)

    Ji, Zhan-Huai; Yan, Sheng-Gang

    2017-12-01

    This paper presents an analytical study of the complete transform of improved Gabor wavelets (IGWs), and discusses its application to the processing and interpretation of seismic signals. The complete Gabor wavelet transform has the following properties. First, unlike the conventional transform, the improved Gabor wavelet transform (IGWT) maps time domain signals to the time-frequency domain instead of the time-scale domain. Second, the IGW's dominant frequency is fixed, so the transform can perform signal frequency division, where the dominant frequency components of the extracted sub-band signal carry essentially the same information as the corresponding components of the original signal, and the subband signal bandwidth can be regulated effectively by the transform's resolution factor. Third, a time-frequency filter consisting of an IGWT and its inverse transform can accurately locate target areas in the time-frequency field and perform filtering in a given time-frequency range. The complete IGW transform's properties are investigated using simulation experiments and test cases, showing positive results for seismic signal processing and interpretation, such as enhancing seismic signal resolution, permitting signal frequency division, and allowing small faults to be identified.

  19. Joint time frequency analysis in digital signal processing

    DEFF Research Database (Denmark)

    Pedersen, Flemming

    with this technique is that the resolution is limited because of distortion. To overcome the resolution limitations of the Fourier Spectogram, many new distributions have been developed. In spite of this the Fourier Spectogram is by far the prime method for the analysis of signals whose spectral content is varying...

  20. 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.

  1. 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  

  2. 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

  3. Stream computing for biomedical signal processing: A QRS complex detection case-study.

    Science.gov (United States)

    Murphy, B M; O'Driscoll, C; Boylan, G B; Lightbody, G; Marnane, W P

    2015-01-01

    Recent developments in "Big Data" have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data.

  4. 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

  5. Windowing of THz time-domain spectroscopy signals: A study based on lactose

    Science.gov (United States)

    Vázquez-Cabo, José; Chamorro-Posada, Pedro; Fraile-Peláez, Francisco Javier; Rubiños-López, Óscar; López-Santos, José María; Martín-Ramos, Pablo

    2016-05-01

    Time-domain spectroscopy has established itself as a reference method for determining material parameters in the terahertz spectral range. This procedure requires the processing of the measured time-domain signals in order to estimate the spectral data. In this work, we present a thorough study of the properties of the signal windowing, a step previous to the parameter extraction algorithm, that permits to improve the accuracy of the results. Lactose has been used as sample material in the study.

  6. 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....

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. Data processing system for real-time control

    International Nuclear Information System (INIS)

    Oasa, K.; Mochizuki, O.; Toyokawa, R.; Yahiro, K.

    1983-01-01

    Real-time control, for large Tokamak JT-60, requires various data processings between diagnostic devices to control system. These processings require to high speed performance so that it aims at giving information necessary for feedback control during discharges. Then, the architecture of this system has hierachical structure of processors. These processors are connected each other by the CAMAC modules and the optical communication network, which is the 5 M bytes/second CAMAC serial highway. This system has two kinds of intelligences for this purpose. One is ACM-PU pairs in some torus hall crates which has a microcomputerized auxiliary controller and a preprocessing unit. Other is real-time processor which has a minicomputer and preprocessing unit. Most of the real-time processing, for example Abel inversion are characteristic to the diagnostic devices. Such a processing is carried out by an ACM-PU pair in the crate dedicated to the diagnostic device. Some processings, however, are also necessary which compute secondary parameters as functions of primary parameters. A typical example is Zeff, which is a function of Te, Ne and bremsstrahluny intensity. The real-time processor is equipped for such secondary processings and transfer the results. Preprocessing unit -PU- attached to ACM and real-time processor contains a signal processor, which executes in parallel such function as move, add and multiply during one micro-instruction cycle of 200 nsec. According to the progress of the experiment, more high speed processing are required, so the authors developed the PU-X module that contains multi signal processors. After a shot, inter-shot-processor which consists of general-purpose computers, gathers data into the database, then analyze them, and improve these processes to more effective

  12. 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.

  13. An open-loop system design for deep space signal processing applications

    Science.gov (United States)

    Tang, Jifei; Xia, Lanhua; Mahapatra, Rabi

    2018-06-01

    A novel open-loop system design with high performance is proposed for space positioning and navigation signal processing. Divided by functions, the system has four modules, bandwidth selectable data recorder, narrowband signal analyzer, time-delay difference of arrival estimator and ANFIS supplement processor. A hardware-software co-design approach is made to accelerate computing capability and improve system efficiency. Embedded with the proposed signal processing algorithms, the designed system is capable of handling tasks with high accuracy over long period of continuous measurements. The experiment results show the Doppler frequency tracking root mean square error during 3 h observation is 0.0128 Hz, while the TDOA residue analysis in correlation power spectrum is 0.1166 rad.

  14. The role of lossless systems in modern digital signal processing: a tutorial

    OpenAIRE

    Vaidyanathan, P. P.; Doğanata, Zinnur

    1989-01-01

    A self-contained discussion of discrete-time lossless systems and their properties and relevance in digital signal processing is presented. The basic concept of losslessness is introduced, and several algebraic properties of lossless systems are studied. An understanding of these properties is crucial in order to exploit the rich usefulness of lossless systems in digital signal processing. Since lossless systems typically have many input and output terminals, a brief review of multiinput mult...

  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. Optical signal processing techniques and applications of optical phase modulation in high-speed communication systems

    Science.gov (United States)

    Deng, Ning

    In recent years, optical phase modulation has attracted much research attention in the field of fiber optic communications. Compared with the traditional optical intensity-modulated signal, one of the main merits of the optical phase-modulated signal is the better transmission performance. For optical phase modulation, in spite of the comprehensive study of its transmission performance, only a little research has been carried out in terms of its functions, applications and signal processing for future optical networks. These issues are systematically investigated in this thesis. The research findings suggest that optical phase modulation and its signal processing can greatly facilitate flexible network functions and high bandwidth which can be enjoyed by end users. In the thesis, the most important physical-layer technology, signal processing and multiplexing, are investigated with optical phase-modulated signals. Novel and advantageous signal processing and multiplexing approaches are proposed and studied. Experimental investigations are also reported and discussed in the thesis. Optical time-division multiplexing and demultiplexing. With the ever-increasing demand on communication bandwidth, optical time division multiplexing (OTDM) is an effective approach to upgrade the capacity of each wavelength channel in current optical systems. OTDM multiplexing can be simply realized, however, the demultiplexing requires relatively complicated signal processing and stringent timing control, and thus hinders its practicability. To tackle this problem, in this thesis a new OTDM scheme with hybrid DPSK and OOK signals is proposed. Experimental investigation shows this scheme can greatly enhance the demultiplexing timing misalignment and improve the demultiplexing performance, and thus make OTDM more practical and cost effective. All-optical signal processing. In current and future optical communication systems and networks, the data rate per wavelength has been approaching

  17. System and method for traffic signal timing estimation

    KAUST Repository

    Dumazert, Julien; Claudel, Christian G.

    2015-01-01

    A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

  18. System and method for traffic signal timing estimation

    KAUST Repository

    Dumazert, Julien

    2015-12-30

    A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

  19. 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…

  20. Ultra-high throughput real-time instruments for capturing fast signals and rare events

    Science.gov (United States)

    Buckley, Brandon Walter

    Wide-band signals play important roles in the most exciting areas of science, engineering, and medicine. To keep up with the demands of exploding internet traffic, modern data centers and communication networks are employing increasingly faster data rates. Wide-band techniques such as pulsed radar jamming and spread spectrum frequency hopping are used on the battlefield to wrestle control of the electromagnetic spectrum. Neurons communicate with each other using transient action potentials that last for only milliseconds at a time. And in the search for rare cells, biologists flow large populations of cells single file down microfluidic channels, interrogating them one-by-one, tens of thousands of times per second. Studying and enabling such high-speed phenomena pose enormous technical challenges. For one, parasitic capacitance inherent in analog electrical components limits their response time. Additionally, converting these fast analog signals to the digital domain requires enormous sampling speeds, which can lead to significant jitter and distortion. State-of-the-art imaging technologies, essential for studying biological dynamics and cells in flow, are limited in speed and sensitivity by finite charge transfer and read rates, and by the small numbers of photo-electrons accumulated in short integration times. And finally, ultra-high throughput real-time digital processing is required at the backend to analyze the streaming data. In this thesis, I discuss my work in developing real-time instruments, employing ultrafast optical techniques, which overcome some of these obstacles. In particular, I use broadband dispersive optics to slow down fast signals to speeds accessible to high-bit depth digitizers and signal processors. I also apply telecommunication multiplexing techniques to boost the speeds of confocal fluorescence microscopy. The photonic time stretcher (TiSER) uses dispersive Fourier transformation to slow down analog signals before digitization and

  1. Investigation of signal processing algorithms for an embedded microcontroller-based wearable pulse oximeter.

    Science.gov (United States)

    Johnston, W S; Mendelson, Y

    2006-01-01

    Despite steady progress in the miniaturization of pulse oximeters over the years, significant challenges remain since advanced signal processing must be implemented efficiently in real-time by a relatively small size wearable device. The goal of this study was to investigate several potential digital signal processing algorithms for computing arterial oxygen saturation (SpO(2)) and heart rate (HR) in a battery-operated wearable reflectance pulse oximeter that is being developed in our laboratory for use by medics and first responders in the field. We found that a differential measurement approach, combined with a low-pass filter (LPF), yielded the most suitable signal processing technique for estimating SpO(2), while a signal derivative approach produced the most accurate HR measurements.

  2. 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.

  3. 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.

  4. 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

  5. Unified and Modular Modeling and Functional Verification Framework of Real-Time Image Signal Processors

    Directory of Open Access Journals (Sweden)

    Abhishek Jain

    2016-01-01

    Full Text Available In VLSI industry, image signal processing algorithms are developed and evaluated using software models before implementation of RTL and firmware. After the finalization of the algorithm, software models are used as a golden reference model for the image signal processor (ISP RTL and firmware development. In this paper, we are describing the unified and modular modeling framework of image signal processing algorithms used for different applications such as ISP algorithms development, reference for hardware (HW implementation, reference for firmware (FW implementation, and bit-true certification. The universal verification methodology- (UVM- based functional verification framework of image signal processors using software reference models is described. Further, IP-XACT based tools for automatic generation of functional verification environment files and model map files are described. The proposed framework is developed both with host interface and with core using virtual register interface (VRI approach. This modeling and functional verification framework is used in real-time image signal processing applications including cellphone, smart cameras, and image compression. The main motivation behind this work is to propose the best efficient, reusable, and automated framework for modeling and verification of image signal processor (ISP designs. The proposed framework shows better results and significant improvement is observed in product verification time, verification cost, and quality of the designs.

  6. Session 3, Measurement systems and signal validation/processing: Rapporteur's report

    International Nuclear Information System (INIS)

    Shepard, R.L.

    1991-01-01

    Eight papers scheduled for presentation dealt with in-core flux and temperature detectors and the interpretation of their signals. Our theme discussed was how core models could be used to validate in-core detector signals, and conversely, how the detector signals could validate the core models. Methods were proposed for distinguishing between detector malfunction (invalid signals) and actual changes in core conditions. It it necessary to reconcile these conflicting possibilities so that accurate and timely assessments of the present and future state of the core may be made during reactor operation, particularly during upset conditions. A second theme addressed the advantages and disadvantages of fixed vs movable in-core detectors -- their characteristics, employment, and signal interpretation. The economic and operating tradeoffs of fixed and movable detectors were addressed. A third theme was the use of signal processing to distinguish between gamma noise and neutron flux signals and how to improve the response times of in-core detectors. The discussion in this session relates to a broader discussion of the relative merits of self-powered neutron detectors and gamma thermometers for in-core flux monitoring which took place at the Cadarache meeting in 1988, and which was continued in Session 1 of this meeting

  7. Advances in biomedical signal and image processing – A systematic review

    Directory of Open Access Journals (Sweden)

    J. Rajeswari

    Full Text Available Biomedical signal and image processing establish a dynamic area of specialization in both academic as well as research aspects of biomedical engineering. The concepts of signal and image processing have been widely used for extracting the physiological information in implementing many clinical procedures for sophisticated medical practices and applications. In this paper, the relationship between electrophysiological signals, i.e., electrocardiogram (ECG, electromyogram (EMG, electroencephalogram (EEG and functional image processing and their derived interactions have been discussed. Examples have been investigated in various case studies such as neurosciences, functional imaging, and cardiovascular system, by using different algorithms and methods. The interaction between the extracted information obtained from multiple signals and modalities seems to be very promising. The advanced algorithms and methods in the area of information retrieval based on time-frequency representation have been investigated. Finally, some examples of algorithms have been discussed in which the electrophysiological signals and functional images have been properly extracted and have a significant impact on various biomedical applications. Keywords: Biomedical signals and images, Processing, Analysis

  8. Coherent time-stretch transformation for real-time capture of wideband signals.

    Science.gov (United States)

    Buckley, Brandon W; Madni, Asad M; Jalali, Bahram

    2013-09-09

    Time stretch transformation of wideband waveforms boosts the performance of analog-to-digital converters and digital signal processors by slowing down analog electrical signals before digitization. The transform is based on dispersive Fourier transformation implemented in the optical domain. A coherent receiver would be ideal for capturing the time-stretched optical signal. Coherent receivers offer improved sensitivity, allow for digital cancellation of dispersion-induced impairments and optical nonlinearities, and enable decoding of phase-modulated optical data formats. Because time-stretch uses a chirped broadband (>1 THz) optical carrier, a new coherent detection technique is required. In this paper, we introduce and demonstrate coherent time stretch transformation; a technique that combines dispersive Fourier transform with optically broadband coherent detection.

  9. 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

  10. 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

  11. State–time spectrum of signal transduction logic models

    International Nuclear Information System (INIS)

    MacNamara, Aidan; Terfve, Camille; Henriques, David; Bernabé, Beatriz Peñalver; Saez-Rodriguez, Julio

    2012-01-01

    Despite the current wealth of high-throughput data, our understanding of signal transduction is still incomplete. Mathematical modeling can be a tool to gain an insight into such processes. Detailed biochemical modeling provides deep understanding, but does not scale well above relatively a few proteins. In contrast, logic modeling can be used where the biochemical knowledge of the system is sparse and, because it is parameter free (or, at most, uses relatively a few parameters), it scales well to large networks that can be derived by manual curation or retrieved from public databases. Here, we present an overview of logic modeling formalisms in the context of training logic models to data, and specifically the different approaches to modeling qualitative to quantitative data (state) and dynamics (time) of signal transduction. We use a toy model of signal transduction to illustrate how different logic formalisms (Boolean, fuzzy logic and differential equations) treat state and time. Different formalisms allow for different features of the data to be captured, at the cost of extra requirements in terms of computational power and data quality and quantity. Through this demonstration, the assumptions behind each formalism are discussed, as well as their advantages and disadvantages and possible future developments. (paper)

  12. 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)

  13. Discrete-Time Biomedical Signal Encryption

    Directory of Open Access Journals (Sweden)

    Victor Grigoraş

    2017-12-01

    Full Text Available Chaotic modulation is a strong method of improving communication security. Analog and discrete chaotic systems are presented in actual literature. Due to the expansion of digital communication, discrete-time systems become more efficient and closer to actual technology. The present contribution offers an in-depth analysis of the effects chaos encryption produce on 1D and 2D biomedical signals. The performed simulations show that modulating signals are precisely recovered by the synchronizing receiver if discrete systems are digitally implemented and the coefficients precisely correspond. Channel noise is also applied and its effects on biomedical signal demodulation are highlighted.

  14. 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...

  15. Time-Frequency Analysis and Hermite Projection Method Applied to Swallowing Accelerometry Signals

    Directory of Open Access Journals (Sweden)

    Ervin Sejdić

    2010-01-01

    Full Text Available Fast Hermite projections have been often used in image-processing procedures such as image database retrieval, projection filtering, and texture analysis. In this paper, we propose an innovative approach for the analysis of one-dimensional biomedical signals that combines the Hermite projection method with time-frequency analysis. In particular, we propose a two-step approach to characterize vibrations of various origins in swallowing accelerometry signals. First, by using time-frequency analysis we obtain the energy distribution of signal frequency content in time. Second, by using fast Hermite projections we characterize whether the analyzed time-frequency regions are associated with swallowing or other phenomena (vocalization, noise, bursts, etc.. The numerical analysis of the proposed scheme clearly shows that by using a few Hermite functions, vibrations of various origins are distinguishable. These results will be the basis for further analysis of swallowing accelerometry to detect swallowing difficulties.

  16. 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...

  17. 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.

  18. Mathematical methods in time series analysis and digital image processing

    CERN Document Server

    Kurths, J; Maass, P; Timmer, J

    2008-01-01

    The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed. This volume coherently summarizes work carried out in the field of theoretical signal and image processing. It focuses on non-linear and non-parametric models for time series as well as on adaptive methods in image processing.

  19. Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

    Directory of Open Access Journals (Sweden)

    Chin-Teng Lin

    2018-01-01

    Full Text Available Electroencephalogram (EEG signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA, feature extraction, and the Gaussian mixture model (GMM to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research.

  20. 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.

  1. Robust real-time extraction of respiratory signals from PET list-mode data

    Science.gov (United States)

    Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

    2018-06-01

    Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard

  2. A phase-equalized digital multirate filter for 50 Hz signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Vainio, O. [Tampere University of Technology, Signal Processing Laboratory, Tampere (Finland)

    1997-12-31

    A new multistage digital filter is proposed for 50 Hz line frequency signal processing in zero-crossing detectors and synchronous power systems. The purpose of the filter is to extract the fundamental sinusoidal signal from noise and impulsive disturbances so that the output is accurately in phase with the primary input signal. This is accomplished with a cascade of a median filter, a linear-phase FIR filter, and a phase corrector. A 10 kHz output timing resolution is achieved by up-sampling with a customized interpolation filter. (orig.) 15 refs.

  3. 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.

  4. 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...

  5. 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

  6. 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...

  7. 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

  8. Multi-Gigahertz radar range processing of baseband and RF carrier modulated signals in Tm:YAG

    International Nuclear Information System (INIS)

    Merkel, K.D.; Krishna Mohan, R.; Cole, Z.; Chang, T.; Olson, A.; Babbitt, W.R.

    2004-01-01

    An optical device is described and demonstrated that uses a spatial-spectral holographic material to perform coherent signal processing operations on analog, high-bandwidth optical signals with large time-bandwidth-products. Signal processing is performed as the material records the coherent spectral interference (or cross-power spectrum) of modulated optical signals as a spatial-spectral population grating between electronic transition states. Multiple exposures of processing pulse sequences are integrated with increasing grating strength. The device, coined as the Spatial-Spectral Coherent Holographic Integrating Processor (or S 2 -CHIP), is described as currently envisioned for a broadband, mid-to-high pulse repetition frequency range-Doppler radar signal processing system. Experiments were performed in Tm:YAG (0.1 at% at 5 K) to demonstrate time delay variation, integration dynamics, and effects of coding as applied to a radar range processor. These demonstrations used baseband modulation with a 1 gigabit per second (GPBS) bit rate and code length of 512 bits (512 ns), where delays up to 1.0 μs were resolved with greater than a 40 dB peak to RMS sidelobe ratio after 800 processing shots. Multi-GHz processing was demonstrated using a bit rate of 2.5 GBPS (baseband modulation) and code length of 2048 bits (819.2 ns). Processing of double-sideband modulated signals on a radio frequency (RF) carrier was demonstrated, where 512 bit, 1.0 GBPS codes were modulated on a 1.75 GHz carrier and then modulated on the optical carrier

  9. 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)

  10. Some Aspects of Process Computers Configuration Control in Nuclear Power Plant Krsko - Process Computer Signal Configuration Database (PCSCDB)

    International Nuclear Information System (INIS)

    Mandic, D.; Kocnar, R.; Sucic, B.

    2002-01-01

    During the operation of NEK and other nuclear power plants it has been recognized that certain issues related to the usage of digital equipment and associated software in NPP technological process protection, control and monitoring, is not adequately addressed in the existing programs and procedures. The term and the process of Process Computers Configuration Control joins three 10CFR50 Appendix B quality requirements of Process Computers application in NPP: Design Control, Document Control and Identification and Control of Materials, Parts and Components. This paper describes Process Computer Signal Configuration Database (PCSCDB), that was developed and implemented in order to resolve some aspects of Process Computer Configuration Control related to the signals or database points that exist in the life cycle of different Process Computer Systems (PCS) in Nuclear Power Plant Krsko. PCSCDB is controlled, master database, related to the definition and description of the configurable database points associated with all Process Computer Systems in NEK. PCSCDB holds attributes related to the configuration of addressable and configurable real time database points and attributes related to the signal life cycle references and history data such as: Input/Output signals, Manually Input database points, Program constants, Setpoints, Calculated (by application program or SCADA calculation tools) database points, Control Flags (example: enable / disable certain program feature) Signal acquisition design references to the DCM (Document Control Module Application software for document control within Management Information System - MIS) and MECL (Master Equipment and Component List MIS Application software for identification and configuration control of plant equipment and components) Usage of particular database point in particular application software packages, and in the man-machine interface features (display mimics, printout reports, ...) Signals history (EEAR Engineering

  11. Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution

    Science.gov (United States)

    Zoladz, T. F.; Jones, J. H.; Jong, J.

    1992-01-01

    A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.

  12. 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

  13. 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.

  14. SIBYLLE: an expert system for the interpretation in real time of mono-dimensional signals; application to vocal signal

    International Nuclear Information System (INIS)

    Minault, Sophie

    1987-01-01

    This report presents an interactive tool for computer aided building of signals processing and interpretation systems. This tool includes three main parts: - an expert system, - a rule compiler, - a real time procedural system. The expert system allows the acquisition of knowledge about the signal. Knowledge has to be formalized as a set of rewriting rules (or syntaxical rules) and is introduced with an interactive interface. The compiler makes a compilation of the knowledge base (the set of rules) and generates a procedural system, which is equivalent to the expert system. The generated procedural system is a fixed one but is much faster than the expert system: it can work in real time. The expert system is used along the experimental phase on a small corpus of data: the knowledge base is then tested and possibly modified thanks to the interactive interface. Once the knowledge base is steady enough, the procedural system is generated and tested on a bigger data corpus. This allows to perform significant statistical studies which generally induce some corrections at the expert system level. The overall constitutes a tool which conciliates the expert systems flexibility with the procedural systems speed. It has been used for building a set of recognition rules modules on vocal signal - module of sound-silence detection - module of voiced-unvoiced segmentation - module of synchronous pitch detection. Its possibilities are not limited to the study of vocal signal, but can be enlarged to any mono-dimensional signal processing. A feasibility study has been realised for an electrocardiograms application. (author) [fr

  15. 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

  16. 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.

  17. 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

  18. All-Optical Signal processing using Highly Nonlinear Photonic Crystal Fiber

    DEFF Research Database (Denmark)

    Andersen, Peter Andreas

    2006-01-01

    -optical regeneration is the only possible way of regenerating a signal with the current technology. Transforming the current telecommunication network into an all-optical network will require an all-optical regeneration of the optical signal. At the current time (May 2005) all-optical regeneration is a tool only used......The use of HNL-PCF in optical communication systems has been investigated in this thesis. The investigation has been done with respect to the future of telecommunications in an all-optical system. The PCFs used have all been used for all-optical signal processing as part of an optical component...... and the possibility of large differences between the refractive indices of the core and the cladding by using air-holes, makes PCFs suited for custom made components. By testing a HNL-PCF as a medium for supercontinuum generation at various dispersion values and at the same time using that supercontinuum...

  19. 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...

  20. Some factors affecting time reversal signal reconstruction

    Czech Academy of Sciences Publication Activity Database

    Převorovský, Zdeněk; Kober, Jan

    2015-01-01

    Roč. 70, September (2015), s. 604-608 ISSN 1875-3892. [ICU International Congress on Ultrasonics 2015. Metz, 10.05.2015-15.05.2015] Institutional support: RVO:61388998 Keywords : nondestructive testing * time reversal signal processing * ultrasonic source reconstruction * acoustic emission * coda wave interferometry Subject RIV: BI - Acoustic s http://ac.els-cdn.com/S1875389215007762/1-s2.0-S1875389215007762-main.pdf?_tid=1513a4a2-9e5b-11e5-9693-00000aab0f27&acdnat=1449655153_455a4e32a1135236d0796c3f973ff58e

  1. CHIRP-Like Signals: Estimation, Detection and Processing A Sequential Model-Based Approach

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J. V. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-08-04

    Chirp signals have evolved primarily from radar/sonar signal processing applications specifically attempting to estimate the location of a target in surveillance/tracking volume. The chirp, which is essentially a sinusoidal signal whose phase changes instantaneously at each time sample, has an interesting property in that its correlation approximates an impulse function. It is well-known that a matched-filter detector in radar/sonar estimates the target range by cross-correlating a replicant of the transmitted chirp with the measurement data reflected from the target back to the radar/sonar receiver yielding a maximum peak corresponding to the echo time and therefore enabling the desired range estimate. In this application, we perform the same operation as a radar or sonar system, that is, we transmit a “chirp-like pulse” into the target medium and attempt to first detect its presence and second estimate its location or range. Our problem is complicated by the presence of disturbance signals from surrounding broadcast stations as well as extraneous sources of interference in our frequency bands and of course the ever present random noise from instrumentation. First, we discuss the chirp signal itself and illustrate its inherent properties and then develop a model-based processing scheme enabling both the detection and estimation of the signal from noisy measurement data.

  2. 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...

  3. 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.

  4. Improvement of the real-time processor in JT-60 data processing system

    International Nuclear Information System (INIS)

    Sakata, S.; Kiyono, K.; Sato, M.; Kominato, T.; Sueoka, M.; Hosoyama, H.; Kawamata, Y.

    2009-01-01

    Real-time processor, RTP is a basic subsystem in the JT-60 data processing system and plays an important role in JT-60 feedback control for plasma experiment. During the experiment, RTP acquires various diagnostic signals, processes them into a form of physical values, and transfers them as sensor signals to the particle supply and heating control supervisor for feedback control via reflective memory synchronization with 1 ms clock signals. After the start of RTP operation in 1997, to meet the demand for advanced plasma experiment, RTP had been improved continuously such as by addition of diagnostic signals with faster digitizers, reducing time for data transfer utilizing reflective memory instead of CAMAC. However, it is becoming increasingly difficult to maintain, manage, and improve the outdated RTP with limited system CPU capability. Currently, a prototype RTP system is being developed for the next real-time processing system, which is composed of clustered system utilizing VxWorks computer. The processes on the existing RTP system will be decentralized to the VxWorks computer to solve the issues of the existing RTP system. The prototype RTP system will start to operate in August 2008.

  5. 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.

  6. 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

  7. Study of time-domain digital pulse shaping algorithms for nuclear signals

    International Nuclear Information System (INIS)

    Zhou Jianbin; Tuo Xianguo; Zhu Xing; Liu Yi; Zhou Wei; Lei Jiarong

    2012-01-01

    With the development on high-speed integrated circuit, fast high resolution sampling ADC and digital signal processors are replacing analog shaping amplifier circuit. This paper firstly presents the numerical analysis and simulation on R-C shaping circuit model and C-R shaping circuit model. Mathematic models are established based on 1 st order digital differential method and Kirchhoff Current Law in time domain, and a simulation and error evaluation experiment on an ideal digital signal are carried out with Excel VBA. A digital shaping test for a semiconductor X-ray detector in real time is also presented. Then a numerical analysis for Sallen-Key(S-K) low-pass filter circuit model is implemented based on the analysis of digital R-C and digital C-R shaping methods. By applying the 2 nd order non-homogeneous differential equation,the authors implement a digital Gaussian filter model for a standard exponential-decaying signal and a nuclear pulse signal. Finally, computer simulations and experimental tests are carried out and the results show the possibility of the digital pulse processing algorithms. (authors)

  8. Tracking radar advanced signal processing and computing for Kwajalein Atoll (KA) application

    Science.gov (United States)

    Cottrill, Stanley D.

    1992-11-01

    Two means are examined whereby the operations of KMR during mission execution may be improved through the introduction of advanced signal processing techniques. In the first approach, the addition of real time coherent signal processing technology to the FPQ-19 radar is considered. In the second approach, the incorporation of the MMW radar, with its very fine range precision, to the MMS system is considered. The former appears very attractive and a Phase 2 SBIR has been proposed. The latter does not appear promising enough to warrant further development.

  9. Real-time video signal processing by generalized DDA and control memories: three-dimensional rotation and mapping

    Science.gov (United States)

    Hama, Hiromitsu; Yamashita, Kazumi

    1991-11-01

    A new method for video signal processing is described in this paper. The purpose is real-time image transformations at low cost, low power, and small size hardware. This is impossible without special hardware. Here generalized digital differential analyzer (DDA) and control memory (CM) play a very important role. Then indentation, which is called jaggy, is caused on the boundary of a background and a foreground accompanied with the processing. Jaggy does not occur inside the transformed image because of adopting linear interpretation. But it does occur inherently on the boundary of the background and the transformed images. It causes deterioration of image quality, and must be avoided. There are two well-know ways to improve image quality, blurring and supersampling. The former does not have much effect, and the latter has the much higher cost of computing. As a means of settling such a trouble, a method is proposed, which searches for positions that may arise jaggy and smooths such points. Computer simulations based on the real data from VTR, one scene of a movie, are presented to demonstrate our proposed scheme using DDA and CMs and to confirm the effectiveness on various transformations.

  10. Application of Data Smoothing Method in Signal Processing for Vortex Flow Meters

    Directory of Open Access Journals (Sweden)

    Zhang Jun

    2017-01-01

    Full Text Available Vortex flow meter is typical flow measure equipment. Its measurement output signals can easily be impaired by environmental conditions. In order to obtain an improved estimate of the time-averaged velocity from the vortex flow meter, a signal filter method is applied in this paper. The method is based on a simple Savitzky-Golay smoothing filter algorithm. According with the algorithm, a numerical program is developed in Python with the scientific library numerical Numpy. Two sample data sets are processed through the program. The results demonstrate that the processed data is available accepted compared with the original data. The improved data of the time-averaged velocity is obtained within smoothing curves. Finally the simple data smoothing program is useable and stable for this filter.

  11. 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

  12. Assessment of Measurement Distortions in GNSS Antenna Array Space-Time Processing

    Directory of Open Access Journals (Sweden)

    Thyagaraja Marathe

    2016-01-01

    Full Text Available Antenna array processing techniques are studied in GNSS as effective tools to mitigate interference in spatial and spatiotemporal domains. However, without specific considerations, the array processing results in biases and distortions in the cross-ambiguity function (CAF of the ranging codes. In space-time processing (STP the CAF misshaping can happen due to the combined effect of space-time processing and the unintentional signal attenuation by filtering. This paper focuses on characterizing these degradations for different controlled signal scenarios and for live data from an antenna array. The antenna array simulation method introduced in this paper enables one to perform accurate analyses in the field of STP. The effects of relative placement of the interference source with respect to the desired signal direction are shown using overall measurement errors and profile of the signal strength. Analyses of contributions from each source of distortion are conducted individually and collectively. Effects of distortions on GNSS pseudorange errors and position errors are compared for blind, semi-distortionless, and distortionless beamforming methods. The results from characterization can be useful for designing low distortion filters that are especially important for high accuracy GNSS applications in challenging environments.

  13. 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

  14. 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.

  15. 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.

  16. Emergency automatic signalling system using time scheduling

    Science.gov (United States)

    Rayavel, P.; Surenderanath, S.; Rathnavel, P.; Prakash, G.

    2018-04-01

    It is difficult to handle traffic congestion and maintain roads during traffic mainly in India. As the people migrate from rural to urban and sub-urban areas, it becomes still more critical. Presently Roadways is a standout amongst the most vital transportation. At the point when a car crash happens, crisis vehicles, for example, ambulances and fire trucks must rush to the mischance scene. There emerges a situation where a portion of the crisis vehicles may cause another car crash. Therefore it becomes still more difficult for emergency vehicle to reach the destination within a predicted time. To avoid that kind of problem we have come out with an effective idea which can reduce the potential in the traffic system. The traffic system is been modified using a wireless technology and high speed micro controller to provide smooth and clear flow of traffic for ambulance to reach the destination on time. This is achieved by using RFID Tag at the ambulance and RFID Reader at the traffic system i.e., traffic signal. This mainly deals with identifying the emergency vehicle and providing a green signal to traffic signal at time of traffic jam. — By assigning priorities to various traffic movements, we can control the traffic jam. In some moments like ambulance emergency, high delegates arrive people facing lot of trouble. To overcome this problem in this paper we propose a time priority based traffic system achieved by using RFID transmitter at the emergency vehicle and RFID receiver at the traffic system i.e., traffic signal. The signal from the emergency vehicle is sent to traffic system which after detecting it sends it to microcontroller which controls the traffic signal. If any emergency vehicle is detected the system goes to emergency system mode where signal switch to green and if it is not detected normal system mode.

  17. Robust real-time extraction of respiratory signals from PET list-mode data.

    Science.gov (United States)

    Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

    2018-05-01

    Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU

  18. Estimation of Saturation Flow Rate and Start-Up Lost Time for Signal Timing Based on Headway Distribution

    Directory of Open Access Journals (Sweden)

    Yi Zhao

    2015-01-01

    Full Text Available This study aimed to calibrate saturation flow rate (SFR and start-up lost time (SLT when developing signal timing. In current commonly used methods, SFR for one given lane is usually calibrated from many subjective adjustment factors and a fixed result. SLT is calculated based on the fixed SFR, which prevents local applications in China. Considering the importance of traffic behavior (headway in determining SFR and SLT, this study started from headway distribution and attempted to specify the relationships between headway and vehicle position directly. A common intersection in Nanjing, China, was selected to implement field study and data from 920 queues was collected. Headway distribution was explored and the 78th percentile of headway at each position was selected to build model. Based on the developed relationships, SFR and SLT were calibrated. The results showed that SFR and SLT were correlated with queue length. Moreover, the results showed that it was difficult to reach saturated state even with a long queue length. This paper provides a new perspective on calibrating important parameters in signal timing, which will be useful for traffic agencies to complete signal timing by making the process simpler.

  19. 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....

  20. Evaluation of signal processing for boiling noise detection. Further analysis of BOR-60 reactor noise data

    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 BOR 60 reactor in the USSR. 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. A proposal for in-service boiling monitoring by acoustic means is described. (author). 3 refs, 16 figs

  1. Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

    Science.gov (United States)

    Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong

    2016-01-01

    Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267

  2. Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

    Directory of Open Access Journals (Sweden)

    Kyungsoo Kim

    2016-06-01

    Full Text Available Electroencephalograms (EEGs measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE schemes based on a joint maximum likelihood (ML criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°.

  3. 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.

  4. 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...

  5. 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.

  6. Development of FPGA-based digital signal processing system for radiation spectroscopy

    International Nuclear Information System (INIS)

    Lee, Pil Soo; Lee, Chun Sik; Lee, Ju Hahn

    2013-01-01

    We have developed an FPGA-based digital signal processing system that performs both online digital signal filtering and pulse-shape analysis for both particle and gamma-ray spectroscopy. Such functionalities were made possible by a state-of-the-art programmable logic device and system architectures employed. The system performance as measured, for example, in the system dead time and accuracy for pulse-height and rise-time determination, was evaluated with standard alpha- and gamma-ray sources using a CsI(Tl) scintillation detector. It is resulted that the present system has shown its potential application to various radiation-related fields such as particle identification, radiography, and radiation imaging. - Highlights: ► An FPGA-based digital processing system was developed for radiation spectroscopy. ► Our digital system has a 14-bit resolution and a 100-MHz sampling rate. ► The FPGA implements the online digital filtering and pulse-shape analysis. ► The pileup rejection is implemented in trigger logic before digital filtering process. ► Our digital system was verified in alpha-gamma measurements using a CsI detector

  7. 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.

  8. Signal encoding method for a time-of-flight PET detector using a silicon photomultiplier array

    Science.gov (United States)

    Kwon, Sun Il; Lee, Jae Sung

    2014-10-01

    The silicon photomultiplier (SiPM) is a promising photosensor for magnetic resonance (MR) compatible time-of-flight (TOF) positron emission tomography (PET) scanners. The compact size of the SiPM allows direct one-to-one coupling between the scintillation crystal and the photosensor, yielding better timing and energy resolutions than the light sharing methods that have to be used in photomultiplier tube (PMT) PET systems. However, the one-to-one coupling scheme requires a huge volume of readout and processing electronics if no electric signal multiplexing or encoding scheme is properly applied. In this paper, we develop an electric signal encoding scheme for SiPM array based TOF PET detector blocks with the aim of reducing the complexity and volume of the signal readout and processing electronics. In an M×N SiPM array, the output signal of each channel in the SiPM array is divided into two signal lines. These output lines are then tied together in row and column lines. The row and column signals are used to measure the energy and timing information (or vice versa) of each incident gamma-ray event, respectively. Each SiPM channel was directly coupled to a 3×3×20 mm3 LGSO crystal. The reference detector, which was used to measure timing, consisted of an R9800 PMT and a 4×4×10 mm3 LYSO crystal and had a single time resolution of ~200 ps (FWHM). Leading edge discriminators were used to determine coincident events. Dedicated front-end electronics were developed, and the timing and energy resolutions of SiPM arrays with different array sizes (4×4, 8×8, and 12×12) were compared. Breakdown voltage of each SiPM channel was measured using energy spectra within various bias voltages. Coincidence events were measured using a 22Na point source. The average coincidence time resolution of 4×4, 8×8, and 12×12 SiPM arrays were 316 ps, 320 ps, and 335 ps (FWHM), respectively. The energy resolution of 4×4, 8×8, and 12×12 SiPM arrays were 11.8%, 12.5%, and 12.8% (FWHM

  9. General Time-Division AltBOC Modulation Technique for GNSS Signals

    Directory of Open Access Journals (Sweden)

    Z. Zhou

    2018-04-01

    Full Text Available In this paper, a general time-division alternate binary offset carrier (GTD-AltBOC modulation method is proposed, which is an extension of TD-AltBOC and time-multiplexed offset-carrier quadrature phase shift keying (TMOC-QPSK with high design flexibility. In this method, binary complex subcarriers and a time-division technique with flexible time slot assignment are used to achieve constant envelope modulation of the signal components with a variable power allocation ratio (PAR. The underlying principle of GTD-AltBOC and the constraints related to the PAR are investigated. For the generation of GTD-AltBOC signals, a lookup table (LUT-based scheme is presented; the minimum required clock rate is half or less of that for existing non-time-division methods. The receiver processing complexities are analyzed for three typical receiving modes, and the power spectral densities (PSDs, cross-correlation functions, multiplexing efficiencies and code-tracking performance are simulated; the results show that GTD-AltBOC enables a significant decrease in receiving complexity compared with existing methods while maintaining high performance in terms of multiplexing efficiency and code tracking.

  10. Ultrasonic signal processing and B-SCAN imaging for nondestructive testing. Application to under - cladding - cracks

    International Nuclear Information System (INIS)

    Theron, G.

    1988-02-01

    Crack propagation under the stainless steel cladding of nuclear reactor vessels is monitored by ultrasonic testing. This work study signal processing to improve detection and sizing of defects. Two possibilities are examined: processing of each individual signal and simultaneous processing of all the signals giving a B-SCAN image. The bibliographic study of time-frequency methods shows that they are not suitable for pulses. Then decomposition in instantaneous frequency and envelope is used. Effect of interference of 2 close echoes on instantaneous frequency is studies. The deconvolution of B-SCAN images is obtained by the transducer field. A point-by-point deconvolution method, less noise sensitive, is developed. B-SCAN images are processed in 2 phases: interface signal processing and deconvolution. These calculations improve image accuracy and dynamics. Water-stell interface and ferritic-austenitic interface are separated. Echoes of crack top are visualized and crack-hole differentiation is improved [fr

  11. 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...

  12. 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

  13. 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....

  14. 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.

  15. Division Multiplexing of 10 Gbit/s Ethernet Signals Synchronized by All-Optical Signal Processing Based on a Time-Lens

    DEFF Research Database (Denmark)

    Areal, Janaina Laguardia

    This Thesis presents 3 years work of an optical circuit that performs both pulse compression and frame synchronization and retiming. Our design aims at directly multiplexing several 10G Ethernet data packets (frames) to a high-speed OTDM link. This scheme is optically trans-parent and does not re...... coupler, completing the OTDM signal generation. We demonstrate the effectiveness of the design by laboratory experi-ments and simulations with VPI and MatLab....... not require clock recovery, resulting in a potentially very efficient solution. The scheme uses a time-lens, implemented through a sinusoidally driven optical phase modulation, combined with a linear dispersion element. As time-lenses are also used for pulse compression, we de-sign the circuit also to perform...

  16. 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.

  17. 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

  18. 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

  19. System and method for constructing filters for detecting signals whose frequency content varies with time

    Science.gov (United States)

    Qian, S.; Dunham, M.E.

    1996-11-12

    A system and method are disclosed for constructing a bank of filters which detect the presence of signals whose frequency content varies with time. The present invention includes a novel system and method for developing one or more time templates designed to match the received signals of interest and the bank of matched filters use the one or more time templates to detect the received signals. Each matched filter compares the received signal x(t) with a respective, unique time template that has been designed to approximate a form of the signals of interest. The robust time domain template is assumed to be of the order of w(t)=A(t)cos(2{pi}{phi}(t)) and the present invention uses the trajectory of a joint time-frequency representation of x(t) as an approximation of the instantaneous frequency function {phi}{prime}(t). First, numerous data samples of the received signal x(t) are collected. A joint time frequency representation is then applied to represent the signal, preferably using the time frequency distribution series. The joint time-frequency transformation represents the analyzed signal energy at time t and frequency f, P(t,f), which is a three-dimensional plot of time vs. frequency vs. signal energy. Then P(t,f) is reduced to a multivalued function f(t), a two dimensional plot of time vs. frequency, using a thresholding process. Curve fitting steps are then performed on the time/frequency plot, preferably using Levenberg-Marquardt curve fitting techniques, to derive a general instantaneous frequency function {phi}{prime}(t) which best fits the multivalued function f(t). Integrating {phi}{prime}(t) along t yields {phi}{prime}(t), which is then inserted into the form of the time template equation. A suitable amplitude A(t) is also preferably determined. Once the time template has been determined, one or more filters are developed which each use a version or form of the time template. 7 figs.

  20. Nonlinear time-series analysis of current signal in cathodic contact glow discharge electrolysis

    International Nuclear Information System (INIS)

    Allagui, Anis; Abdelkareem, Mohammad Ali; Rojas, Andrea Espinel; Bonny, Talal; Elwakil, Ahmed S.

    2016-01-01

    In the standard two-electrode configuration employed in electrolytic process, when the control dc voltage is brought to a critical value, the system undergoes a transition from conventional electrolysis to contact glow discharge electrolysis (CGDE), which has also been referred to as liquid-submerged micro-plasma, glow discharge plasma electrolysis, electrode effect, electrolytic plasma, etc. The light-emitting process is associated with the development of an irregular and erratic current time-series which has been arbitrarily labelled as “random,” and thus dissuaded further research in this direction. Here, we examine the current time-series signals measured in cathodic CGDE configuration in a concentrated KOH solution at different dc bias voltages greater than the critical voltage. We show that the signals are, in fact, not random according to the NIST SP. 800-22 test suite definition. We also demonstrate that post-processing low-pass filtered sequences requires less time than the native as-measured sequences, suggesting a superposition of low frequency chaotic fluctuations and high frequency behaviors (which may be produced by more than one possible source of entropy). Using an array of nonlinear time-series analyses for dynamical systems, i.e., the computation of largest Lyapunov exponents and correlation dimensions, and re-construction of phase portraits, we found that low-pass filtered datasets undergo a transition from quasi-periodic to chaotic to quasi-hyper-chaotic behavior, and back again to chaos when the voltage controlling-parameter is increased. The high frequency part of the signals is discussed in terms of highly nonlinear turbulent motion developed around the working electrode.

  1. 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....

  2. 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...

  3. 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.

  4. 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

  5. A high precision position sensor design and its signal processing algorithm for a maglev train.

    Science.gov (United States)

    Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

    2012-01-01

    High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

  6. A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train

    Directory of Open Access Journals (Sweden)

    Wensen Chang

    2012-04-01

    Full Text Available High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

  7. 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

  8. Signal Timing Optimization Based on Fuzzy Compromise Programming for Isolated Signalized Intersection

    Directory of Open Access Journals (Sweden)

    Dexin Yu

    2016-01-01

    Full Text Available In order to optimize the signal timing for isolated intersection, a new method based on fuzzy programming approach is proposed in this paper. Considering the whole operation efficiency of the intersection comprehensively, traffic capacity, vehicle cycle delay, cycle stops, and exhaust emission are chosen as optimization goals to establish a multiobjective function first. Then fuzzy compromise programming approach is employed to give different weight coefficients to various optimization objectives for different traffic flow ratios states. And then the multiobjective function is converted to a single objective function. By using genetic algorithm, the optimized signal cycle and effective green time can be obtained. Finally, the performance of the traditional method and new method proposed in this paper is compared and analyzed through VISSIM software. It can be concluded that the signal timing optimized in this paper can effectively reduce vehicle delays and stops, which can improve traffic capacity of the intersection as well.

  9. 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...

  10. 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

  11. 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

  12. 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...

  13. 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.

  14. Thickness measurement by using cepstrum ultrasonic signal processing

    International Nuclear Information System (INIS)

    Choi, Young Chul; Yoon, Chan Hoon; Choi, Heui Joo; Park, Jong Sun

    2014-01-01

    Ultrasonic thickness measurement is a non-destructive method to measure the local thickness of a solid element, based on the time taken for an ultrasound wave to return to the surface. When an element is very thin, it is difficult to measure thickness with the conventional ultrasonic thickness method. This is because the method measures the time delay by using the peak of a pulse, and the pulses overlap. To solve this problem, we propose a method for measuring thickness by using the power cepstrum and the minimum variance cepstrum. Because the cepstrums processing can divides the ultrasound into an impulse train and transfer function, where the period of the impulse train is the traversal time, the thickness can be measured exactly. To verify the proposed method, we performed experiments with steel and, acrylic plates of variable thickness. The conventional method is not able to estimate the thickness, because of the overlapping pulses. However, the cepstrum ultrasonic signal processing that divides a pulse into an impulse and a transfer function can measure the thickness exactly.

  15. 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

  16. Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

    Directory of Open Access Journals (Sweden)

    Yeqing Zhang

    2018-02-01

    Full Text Available For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully.

  17. Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

    Science.gov (United States)

    Zhang, Yeqing; Wang, Meiling; Li, Yafeng

    2018-01-01

    For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. PMID:29495301

  18. 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

  19. 2012 Proceedings of the International Conference on Communications, Signal Processing, and Systems

    CERN Document Server

    Wang, Wei; Mu, Jiasong; Liang, Jing; Zhang, Baoju; Pi, Yiming; Zhao, Chenglin

    2012-01-01

    Communications, Signal Processing, and Systems is a collection of contributions coming out of the International Conference on Communications, Signal Processing, and Systems (CSPS) held October 2012. This book provides the state-of-art developments of Communications, Signal Processing, and Systems, and their interactions in multidisciplinary fields, such as Smart Grid. The book also examines Radar Systems, Sensor Networks, Radar Signal Processing, Design and Implementation of Signal Processing Systems and Applications. Written by experts and students in the fields of Communications, Signal Processing, and Systems.

  20. 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.

  1. Robust high-resolution quantification of time signals encoded by in vivo magnetic resonance spectroscopy

    Science.gov (United States)

    Belkić, Dževad; Belkić, Karen

    2018-01-01

    This paper on molecular imaging emphasizes improving specificity of magnetic resonance spectroscopy (MRS) for early cancer diagnostics by high-resolution data analysis. Sensitivity of magnetic resonance imaging (MRI) is excellent, but specificity is insufficient. Specificity is improved with MRS by going beyond morphology to assess the biochemical content of tissue. This is contingent upon accurate data quantification of diagnostically relevant biomolecules. Quantification is spectral analysis which reconstructs chemical shifts, amplitudes and relaxation times of metabolites. Chemical shifts inform on electronic shielding of resonating nuclei bound to different molecular compounds. Oscillation amplitudes in time signals retrieve the abundance of MR sensitive nuclei whose number is proportional to metabolite concentrations. Transverse relaxation times, the reciprocal of decay probabilities of resonances, arise from spin-spin coupling and reflect local field inhomogeneities. In MRS single voxels are used. For volumetric coverage, multi-voxels are employed within a hybrid of MRS and MRI called magnetic resonance spectroscopic imaging (MRSI). Common to MRS and MRSI is encoding of time signals and subsequent spectral analysis. Encoded data do not provide direct clinical information. Spectral analysis of time signals can yield the quantitative information, of which metabolite concentrations are the most clinically important. This information is equivocal with standard data analysis through the non-parametric, low-resolution fast Fourier transform and post-processing via fitting. By applying the fast Padé transform (FPT) with high-resolution, noise suppression and exact quantification via quantum mechanical signal processing, advances are made, presented herein, focusing on four areas of critical public health importance: brain, prostate, breast and ovarian cancers.

  2. Process-specific analysis in episodic memory retrieval using fast optical signals and hemodynamic signals in the right prefrontal cortex

    Science.gov (United States)

    Dong, Sunghee; Jeong, Jichai

    2018-02-01

    Objective. Memory is formed by the interaction of various brain functions at the item and task level. Revealing individual and combined effects of item- and task-related processes on retrieving episodic memory is an unsolved problem because of limitations in existing neuroimaging techniques. To investigate these issues, we analyze fast and slow optical signals measured from a custom-built continuous wave functional near-infrared spectroscopy (CW-fNIRS) system. Approach. In our work, we visually encode the words to the subjects and let them recall the words after a short rest. The hemodynamic responses evoked by the episodic memory are compared with those evoked by the semantic memory in retrieval blocks. In the fast optical signal, we compare the effects of old and new items (previously seen and not seen) to investigate the item-related process in episodic memory. The Kalman filter is simultaneously applied to slow and fast optical signals in different time windows. Main results. A significant task-related HbR decrease was observed in the episodic memory retrieval blocks. Mean amplitude and peak latency of a fast optical signal are dependent upon item types and reaction time, respectively. Moreover, task-related hemodynamic and item-related fast optical responses are correlated in the right prefrontal cortex. Significance. We demonstrate that episodic memory is retrieved from the right frontal area by a functional connectivity between the maintained mental state through retrieval and item-related transient activity. To the best of our knowledge, this demonstration of functional NIRS research is the first to examine the relationship between item- and task-related memory processes in the prefrontal area using single modality.

  3. Process-specific analysis in episodic memory retrieval using fast optical signals and hemodynamic signals in the right prefrontal cortex.

    Science.gov (United States)

    Dong, Sunghee; Jeong, Jichai

    2018-02-01

    Memory is formed by the interaction of various brain functions at the item and task level. Revealing individual and combined effects of item- and task-related processes on retrieving episodic memory is an unsolved problem because of limitations in existing neuroimaging techniques. To investigate these issues, we analyze fast and slow optical signals measured from a custom-built continuous wave functional near-infrared spectroscopy (CW-fNIRS) system. In our work, we visually encode the words to the subjects and let them recall the words after a short rest. The hemodynamic responses evoked by the episodic memory are compared with those evoked by the semantic memory in retrieval blocks. In the fast optical signal, we compare the effects of old and new items (previously seen and not seen) to investigate the item-related process in episodic memory. The Kalman filter is simultaneously applied to slow and fast optical signals in different time windows. A significant task-related HbR decrease was observed in the episodic memory retrieval blocks. Mean amplitude and peak latency of a fast optical signal are dependent upon item types and reaction time, respectively. Moreover, task-related hemodynamic and item-related fast optical responses are correlated in the right prefrontal cortex. We demonstrate that episodic memory is retrieved from the right frontal area by a functional connectivity between the maintained mental state through retrieval and item-related transient activity. To the best of our knowledge, this demonstration of functional NIRS research is the first to examine the relationship between item- and task-related memory processes in the prefrontal area using single modality.

  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. 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.

  6. 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.

  7. A sensor-based wrist pulse signal processing and lung cancer recognition.

    Science.gov (United States)

    Zhang, Zhichao; Zhang, Yuan; Yao, Lina; Song, Houbing; Kos, Anton

    2018-03-01

    Pulse diagnosis is an efficient method in traditional Chinese medicine for detecting the health status of a person in a non-invasive and convenient way. Jin's pulse diagnosis (JPD) is a very efficient recent development that is gradually recognized and well validated by the medical community in recent years. However, no acceptable results have been achieved for lung cancer recognition in the field of biomedical signal processing using JPD. More so, there is no standard JPD pulse feature defined with respect to pulse signals. Our work is designed mainly for care giving service conveniently at home to the people having lung cancer by proposing a novel wrist pulse signal processing method, having an insight from JPD. We developed an iterative slide window (ISW) algorithm to segment the de-noised signal into single periods. We analyzed the characteristics of the segmented pulse waveform and for the first time summarized 26 features to classify the pulse waveforms of healthy individuals and lung cancer patients using a cubic support vector machine (CSVM). The result achieved by the proposed method is found to be 78.13% accurate. Copyright © 2018 Elsevier Inc. All rights reserved.

  8. Signal restoration for NMR imaging using time-dependent gradients

    International Nuclear Information System (INIS)

    Frahm, J.; Haenicke, W.

    1984-01-01

    NMR imaging experiments that employ linear but time-dependent gradients for encoding spatial information in the time-domain signals result in distorted images when treated with conventional image reconstruction techniques. It is shown here that the phase and amplitude distortions can be entirely removed if the timeshape of the gradient is known. The method proposed is of great theoretical and experimental simplicity. It consists of a retransformation of the measured time-domain signal and corresponds to synchronisation of the signal sampling with the time-development of the gradient field strength. The procedure complements other treatments of periodically oscillating gradients in NMR imaging. (author)

  9. 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

  10. 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.

  11. 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.

  12. Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR.

    Science.gov (United States)

    Mobli, Mehdi; Hoch, Jeffrey C

    2014-11-01

    Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. 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

  14. 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

  15. 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.

  16. 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....

  17. Welding quality evaluation of resistance spot welding using the time-varying inductive reactance signal

    Science.gov (United States)

    Zhang, Hongjie; Hou, Yanyan; Yang, Tao; Zhang, Qian; Zhao, Jian

    2018-05-01

    In the spot welding process, a high alternating current is applied, resulting in a time-varying electromagnetic field surrounding the welder. When measuring the welding voltage signal, the impedance of the measuring circuit consists of two parts: dynamic resistance relating to weld nugget nucleation event and inductive reactance caused by mutual inductance. The aim of this study is to develop a method to acquire the dynamic reactance signal and to discuss the possibility of using this signal to evaluate the weld quality. For this purpose, a series of experiments were carried out. The reactance signals under different welding conditions were compared and the results showed that the morphological feature of the reactance signal was closely related to the welding current and it was also significantly influenced by some abnormal welding conditions. Some features were extracted from the reactance signal and combined to construct weld nugget strength and diameter prediction models based on the radial basis function (RBF) neural network. In addition, several features were also used to monitor the expulsion in the welding process by using Fisher linear discriminant analysis. The results indicated that using the dynamic reactance signal to evaluate weld quality is possible and feasible.

  18. Cross-Term Suppression in Time Order Distribution for AWGN Signal

    Directory of Open Access Journals (Sweden)

    WAQAS MAHMOOD

    2017-04-01

    Full Text Available A technique of cross-term suppression in WD (Wigner Distribution for a multi-component signal that is embedded WGN (White Gaussian Noise is proposed. In this technique, an optimized algorithm is developed for time-varying noisy signal and a CAD (Computer Aided Design simulator is designed for Numerical simulations of synthetic signal. In proposed technique, signal components are localized in tf (time frequency plane by STFT (Short Time Fourier Transform. Rectified STFT is computed and Spectral Kurtosis is used to separate a signal components from noise in t-f plane. The t-f plane is segmented and then signal components are filtered out by FFT (Fractional Fourier Transform. Finally, WD (free of cross terms of isolated signal component is computed to obtain high resolution in t-f plane.

  19. Signal Processing using Nonlinear Optical Eects in Single- and Few-Mode Fibers

    DEFF Research Database (Denmark)

    Friis, Søren Michael Mørk

    noise, loss, and pump depletion on the noise properties of parametric frequency conversion and phase-insensitive and phase-sensitive parametric amplification. An important part of realizing space-division multiplexing is the ability of optical signal processing so the second part of this thesis......-wave mixing in two-mode fibers acvi counting for six simultaneous processes is derived, and the conversion efficiency from signal to idler in the four-wave mixing processes of phase conjugation and Bragg scattering in two two-mode fibers with different phase matching properties are experimentally investigated......The stagnating increase in data transmission capacity in optical communication systems combined with the ever growing demand of transmission bandwidth is leading to an impending capacity crunch, referring to the point in time after which the available bandwidth of the individual user starts...

  20. The time course of individual face recognition: A pattern analysis of ERP signals.

    Science.gov (United States)

    Nemrodov, Dan; Niemeier, Matthias; Mok, Jenkin Ngo Yin; Nestor, Adrian

    2016-05-15

    An extensive body of work documents the time course of neural face processing in the human visual cortex. However, the majority of this work has focused on specific temporal landmarks, such as N170 and N250 components, derived through univariate analyses of EEG data. Here, we take on a broader evaluation of ERP signals related to individual face recognition as we attempt to move beyond the leading theoretical and methodological framework through the application of pattern analysis to ERP data. Specifically, we investigate the spatiotemporal profile of identity recognition across variation in emotional expression. To this end, we apply pattern classification to ERP signals both in time, for any single electrode, and in space, across multiple electrodes. Our results confirm the significance of traditional ERP components in face processing. At the same time though, they support the idea that the temporal profile of face recognition is incompletely described by such components. First, we show that signals associated with different facial identities can be discriminated from each other outside the scope of these components, as early as 70ms following stimulus presentation. Next, electrodes associated with traditional ERP components as well as, critically, those not associated with such components are shown to contribute information to stimulus discriminability. And last, the levels of ERP-based pattern discrimination are found to correlate with recognition accuracy across subjects confirming the relevance of these methods for bridging brain and behavior data. Altogether, the current results shed new light on the fine-grained time course of neural face processing and showcase the value of novel methods for pattern analysis to investigating fundamental aspects of visual recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. HSP v2: Haptic Signal Processing with Extensions for Physical Modeling

    DEFF Research Database (Denmark)

    Overholt, Daniel; Kontogeorgakopoulos, Alexandros; Berdahl, Edgar

    2010-01-01

    The Haptic Signal Processing (HSP) platform aims to enable musicians to easily design and perform with digital haptic musical instruments [1]. In this paper, we present some new objects introduced in version v2 for modeling of musical dynamical systems such as resonators and vibrating strings. To....... To our knowledge, this is the first time that these diverse physical modeling elements have all been made available for a modular, real-time haptics platform....

  2. 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

  3. 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

  4. Real-time traffic signal optimization model based on average delay time per person

    Directory of Open Access Journals (Sweden)

    Pengpeng Jiao

    2015-10-01

    Full Text Available Real-time traffic signal control is very important for relieving urban traffic congestion. Many existing traffic control models were formulated using optimization approach, with the objective functions of minimizing vehicle delay time. To improve people’s trip efficiency, this article aims to minimize delay time per person. Based on the time-varying traffic flow data at intersections, the article first fits curves of accumulative arrival and departure vehicles, as well as the corresponding functions. Moreover, this article transfers vehicle delay time to personal delay time using average passenger load of cars and buses, employs such time as the objective function, and proposes a signal timing optimization model for intersections to achieve real-time signal parameters, including cycle length and green time. This research further implements a case study based on practical data collected at an intersection in Beijing, China. The average delay time per person and queue length are employed as evaluation indices to show the performances of the model. The results show that the proposed methodology is capable of improving traffic efficiency and is very effective for real-world applications.

  5. Signal processing for molecular and cellular biological physics: an emerging field.

    Science.gov (United States)

    Little, Max A; Jones, Nick S

    2013-02-13

    Recent advances in our ability to watch the molecular and cellular processes of life in action--such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer--raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

  6. Real-time implementations of acoustic signal enhancement techniques for aerial based surveillance and rescue applications

    Science.gov (United States)

    Ramos, Antonio L. L.; Shao, Zhili; Holthe, Aleksander; Sandli, Mathias F.

    2017-05-01

    The introduction of the System-on-Chip (SoC) technology has brought exciting new opportunities for the development of smart low cost embedded systems spanning a wide range of applications. Currently available SoC devices are capable of performing high speed digital signal processing tasks in software while featuring relatively low development costs and reduced time-to-market. Unmanned aerial vehicles (UAV) are an application example that has shown tremendous potential in an increasing number of scenarios, ranging from leisure to surveillance as well as in search and rescue missions. Video capturing from UAV platforms is a relatively straightforward task that requires almost no preprocessing. However, that does not apply to audio signals, especially in cases where the data is to be used to support real-time decision making. In fact, the enormous amount of acoustic interference from the surroundings, including the noise from the UAVs propellers, becomes a huge problem. This paper discusses a real-time implementation of the NLMS adaptive filtering algorithm applied to enhancing acoustic signals captured from UAV platforms. The model relies on a combination of acoustic sensors and a computational inexpensive algorithm running on a digital signal processor. Given its simplicity, this solution can be incorporated into the main processing system of an UAV using the SoC technology, and run concurrently with other required tasks, such as flight control and communications. Simulations and real-time DSP-based implementations have shown significant signal enhancement results by efficiently mitigating the interference from the noise generated by the UAVs propellers as well as from other external noise sources.

  7. 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...

  8. 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

  9. Mine detection using SF-GPR: A signal processing approach for resolution enhancement and clutter reduction

    DEFF Research Database (Denmark)

    Karlsen, Brian; Jakobsen, Kaj Bjarne; Larsen, Jan

    2001-01-01

    Proper clutter reduction is essential for Ground Penetrating Radar data since low signal-to-clutter ratio prevent correct detection of mine objects. A signal processing approach for resolution enhancement and clutter reduction used on Stepped-Frequency Ground Penetrating Radar (SF-GPR) data is pr....... The clutter reduction method is based on basis function decomposition of the SF-GPR time-series from which the clutter and the signal are separated....

  10. Data acquisition and real time signal processing of plasma diagnostics on ASDEX Upgrade using LabVIEW RT

    Energy Technology Data Exchange (ETDEWEB)

    Giannone, L.; Scarabosio, A.; Eich, T.; Fuchs, C.; Haas, G.; Kallenbach, A.; McCarthy, P.; Mlynek, A.; Neu, G.; Reich, M.; Schneider, W.; Schuhbeck, K.; Treutterer, W.; Zehetbauer, T.; Asdex, Upgrade Team [Max-Planck-Institut fur Plasmaphysik, Garching (Germany); Cerna, M.; Wenzel, L.; Concezzi, S.; Debelle, T.; Marker, B.; Munroe, M.; Petersen, N.; Vrancic, A. [National Instruments Corporation, Austin (United States); Marquardt, M.; Sachtleben, J. [Max-Planck-Institute for Plasmaphysics, Teilinstitut Greifswald (Germany)

    2009-07-01

    There are 5 plasma diagnostics using LabVIEW RT for data acquisition and control on ASDEX Upgrade. These diagnostics are integrated into the VxWorks control system by the exchange of XML files. Real time communication to the control system is possible by Ethernet using UDP or by reflective memory using a dedicated fiber optic cable. The bolometer and manometer data acquisition systems are described, they use FPGA cards to process raw data in real time. The absorbed power of the bolometer foil is calculated in real time on the FPGA. The radiation peaking factor is also calculated in real time and is used for feedback control of the discharge. The manometer uses 8 analog inputs and 4 analog outputs of a FPGA card to provide PID control of the electron current emission of a filament. The electron and ion currents are acquired at 750 kHz and the neutral gas pressures of 4 manometers are calculated in real time on a FPGA card at up to 10 kHz. The magnetic equilibrium diagnostic acquires 80 magnetic probe and flux loop signals at 10 kHz. The 95 plasma position and shape parameters and magnetic flux surfaces are calculated in real time. The function parameterization algorithm used to calculate the magnetic flux surfaces in real time requires the multiplication of a matrix of dimension 2691*231 with a vector of length 231. This matrix and vector multiplication is solved through parallel computing on a dual quad-core computer and the execution time of this operation is reduced by a factor of four compared to calculation on a single core. This document is composed of an abstract followed by a poster. (authors)

  11. 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

  12. 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....

  13. 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

  14. First year progress report on the co-ordinated research programme on signal processing techniques for sodium boiling noise detection

    International Nuclear Information System (INIS)

    Singh, O.P.; Prabhakar, R.; John, T.M.; Vyjayanthi, R.K.; Reddy, C.P.; Parikh, M.V.; Ponpandi, S.

    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). 3 refs, 5 figs, 5 tabs

  15. Using hyperentanglement to enhance resolution, signal-to-noise ratio, and measurement time

    Science.gov (United States)

    Smith, James F.

    2017-03-01

    A hyperentanglement-based atmospheric imaging/detection system involving only a signal and an ancilla photon will be considered for optical and infrared frequencies. Only the signal photon will propagate in the atmosphere and its loss will be classical. The ancilla photon will remain within the sensor experiencing low loss. Closed form expressions for the wave function, normalization, density operator, reduced density operator, symmetrized logarithmic derivative, quantum Fisher information, quantum Cramer-Rao lower bound, coincidence probabilities, probability of detection, probability of false alarm, probability of error after M measurements, signal-to-noise ratio, quantum Chernoff bound, time-on-target expressions related to probability of error, and resolution will be provided. The effect of noise in every mode will be included as well as loss. The system will provide the basic design for an imaging/detection system functioning at optical or infrared frequencies that offers better than classical angular and range resolution. Optimization for enhanced resolution will be included. The signal-to-noise ratio will be increased by a factor equal to the number of modes employed during the hyperentanglement process. Likewise, the measurement time can be reduced by the same factor. The hyperentanglement generator will typically make use of entanglement in polarization, energy-time, orbital angular momentum and so on. Mathematical results will be provided describing the system's performance as a function of loss mechanisms and noise.

  16. Signal processing for ultrasonic testing of stainless steel with coarse structure

    International Nuclear Information System (INIS)

    Dahlgren, Sven; Ericsson, Lars

    2000-03-01

    Ultrasonic testing of materials with coarse grains often gives poor signal-to-noise-ratio due to backscattering from the grain boundaries. The influence of the back-scattering, being strongly dependent on the size of the grains and the wavelength used, can be reduced by suitable choice of inspection frequencies used. The actual choice can be made flexible using broad band probes in combination with digital signal processing. Furthermore, with such an approach it might be possible both to detect and size defects from the same scan. One well-known signal processing method is Split Spectrum Processing (SSP). This method can significantly reduce grain noise, but finding the optimal choice of parameters involved is difficult. The introduction of the Consecutive Polarity Coincidence (CPC) as SSP target extraction algorithm more or less solved this problem but other draw-backs such as reduced temporal resolution is inherent in SSP. Based on the experiences with SSP a new approach to grain noise reduction, based on non coherent detection (NCD), was developed at Uppsala University. The technique is evaluated, in this investigation. The NCD algorithm has for a long time been used within the field of telecommunication and is based upon detection of bandpass signals in additive Gaussian noise. To adapt the algorithm for use in NDE a two parameter transient model is used. The construction of an NCD filter includes three steps: estimation of the autocorrelation of the noise; specification of the two parameters, lower and upper frequency, of the signal prototype; computation of the filter. During the project two algorithms, based on signal entropy and signal-to-noise-ratio enhancement (SNRE), have been developed to determine the two parameters in an automated procedure. UTdata to evaluate the NCD algorithm were collected in three phases: Phase 1: Manual scanning was performed on CSS-block with ideal reflectors (laboratory environment). Tuning of the two NCD parameters was done

  17. Time dependent auto-correlation, autospectrum and decay ratio estimation of transient signals in JET soft X-ray records

    International Nuclear Information System (INIS)

    Por, G.

    1999-08-01

    A program package was developed to estimate the time dependent auto-correlation function (ACF) from the time signals of soft X-ray records taken along the various lines-of-sights in JET-SHOTS, and also to estimate the time dependent Decay Ratio (DR) from that. On the basis of ACF the time dependent auto-power spectral density (APSD) was also calculated. The steps and objectives of this work were: eliminating the white detection noise, trends and slow variation from the time signals, since ordinary methods can give good estimate of the time dependent ACF and DR only for 'nearly' stationary signals, developing an automatic algorithm for finding the maxima and minima of ACF, since they are the basis for DR estimation, evaluating and testing different DR estimators for JET-SHOT, with the aim of finding parts of the signals, where the oscillating character is strong, estimating time dependent ACF and APSD that can follow the relatively fast variation in the time signal. The methods that we have developed for data processing of transient signals are: White detection noise removal and preparation for trend removal - weak components, white detection noise and high frequency components are filtered from the signal using the so-called soft-threshold wavelet filter. Removal of trends and slow variation - Three-point differentiation of the pre-filtered signal is used to remove trends and slow variation. Here we made use of the DERIV function of IDL program language. This leads to a filtered signal that has zero mean value in each time step. Calculation of the time dependent ACF - The signal treated by the two previous steps is used as the input. Calculated ACF value is added in each new time step, but the previously accumulated ACF value is multiplied by a weighting factor. Thus the new sample has 100% contribution, while the contributions from the previous samples are forgotten quickly. DR calculation - DR is a measure of the decay of oscillating ACF. This parameter was shown

  18. 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.)

  19. 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

  20. Stochastic resonance in a bistable system subject to multi-time-delayed feedback and aperiodic signal

    International Nuclear Information System (INIS)

    Li Jianlong; Zeng Lingzao

    2010-01-01

    We discuss in detail the effects of the multi-time-delayed feedback driven by an aperiodic signal on the output of a stochastic resonance (SR) system. The effective potential function and dynamical probability density function (PDF) are derived. To measure the performance of the SR system in the presence of a binary random signal, the bit error rate (BER) defined by the dynamical PDF is employed, as is commonly used in digital communications. We find that the delay time, strength of the feedback, and number of time-delayed terms can change the effective potential function and the effective amplitude of the signal, and then affect the BER of the SR system. The numerical simulations strongly support the theoretical results. The goal of this investigation is to explore the effects of the multi-time-delayed feedback on SR and give a guidance to nonlinear systems in the application of information processing.

  1. Dynamic time warping and machine learning for signal quality assessment of pulsatile signals

    International Nuclear Information System (INIS)

    Li, Q; Clifford, G D

    2012-01-01

    In this work, we describe a beat-by-beat method for assessing the clinical utility of pulsatile waveforms, primarily recorded from cardiovascular blood volume or pressure changes, concentrating on the photoplethysmogram (PPG). Physiological blood flow is nonstationary, with pulses changing in height, width and morphology due to changes in heart rate, cardiac output, sensor type and hardware or software pre-processing requirements. Moreover, considerable inter-individual and sensor-location variability exists. Simple template matching methods are therefore inappropriate, and a patient-specific adaptive initialization is therefore required. We introduce dynamic time warping to stretch each beat to match a running template and combine it with several other features related to signal quality, including correlation and the percentage of the beat that appeared to be clipped. The features were then presented to a multi-layer perceptron neural network to learn the relationships between the parameters in the presence of good- and bad-quality pulses. An expert-labeled database of 1055 segments of PPG, each 6 s long, recorded from 104 separate critical care admissions during both normal and verified arrhythmic events, was used to train and test our algorithms. An accuracy of 97.5% on the training set and 95.2% on test set was found. The algorithm could be deployed as a stand-alone signal quality assessment algorithm for vetting the clinical utility of PPG traces or any similar quasi-periodic signal. (paper)

  2. Dynamic time warping and machine learning for signal quality assessment of pulsatile signals.

    Science.gov (United States)

    Li, Q; Clifford, G D

    2012-09-01

    In this work, we describe a beat-by-beat method for assessing the clinical utility of pulsatile waveforms, primarily recorded from cardiovascular blood volume or pressure changes, concentrating on the photoplethysmogram (PPG). Physiological blood flow is nonstationary, with pulses changing in height, width and morphology due to changes in heart rate, cardiac output, sensor type and hardware or software pre-processing requirements. Moreover, considerable inter-individual and sensor-location variability exists. Simple template matching methods are therefore inappropriate, and a patient-specific adaptive initialization is therefore required. We introduce dynamic time warping to stretch each beat to match a running template and combine it with several other features related to signal quality, including correlation and the percentage of the beat that appeared to be clipped. The features were then presented to a multi-layer perceptron neural network to learn the relationships between the parameters in the presence of good- and bad-quality pulses. An expert-labeled database of 1055 segments of PPG, each 6 s long, recorded from 104 separate critical care admissions during both normal and verified arrhythmic events, was used to train and test our algorithms. An accuracy of 97.5% on the training set and 95.2% on test set was found. The algorithm could be deployed as a stand-alone signal quality assessment algorithm for vetting the clinical utility of PPG traces or any similar quasi-periodic signal.

  3. The short time Fourier transform and local signals

    Science.gov (United States)

    Okumura, Shuhei

    In this thesis, I examine the theoretical properties of the short time discrete Fourier transform (STFT). The STFT is obtained by applying the Fourier transform by a fixed-sized, moving window to input series. We move the window by one time point at a time, so we have overlapping windows. I present several theoretical properties of the STFT, applied to various types of complex-valued, univariate time series inputs, and their outputs in closed forms. In particular, just like the discrete Fourier transform, the STFT's modulus time series takes large positive values when the input is a periodic signal. One main point is that a white noise time series input results in the STFT output being a complex-valued stationary time series and we can derive the time and time-frequency dependency structure such as the cross-covariance functions. Our primary focus is the detection of local periodic signals. I present a method to detect local signals by computing the probability that the squared modulus STFT time series has consecutive large values exceeding some threshold after one exceeding observation following one observation less than the threshold. We discuss a method to reduce the computation of such probabilities by the Box-Cox transformation and the delta method, and show that it works well in comparison to the Monte Carlo simulation method.

  4. Improved real-time dosimetry using the radioluminescence signal from Al2O3:C

    International Nuclear Information System (INIS)

    Damkjaer, S.M.S.; Andersen, C.E.; Aznar, M.C.

    2008-01-01

    Carbon-doped aluminum oxide (Al 2 O 3 :C) is a highly sensitive luminescence material for ionizing radiation dosimetry, and it is well established that the optically stimulated luminescence (OSL) signal from Al 2 O 3 :C can be used for absorbed-dose measurements. During irradiation, Al 2 O 3 :C also emits prompt radioluminescence (RL) which allows for real-time dose verification. The RL-signal is not linear in the absorbed dose due to sensitivity changes and the presence of shallow traps. Despite this the signal can be processed to obtain a reliable dose rate signal in real time. Previously a simple algorithm for correcting the RL-signal has been published and here we report two improvements: a better and more stable calibration method which is independent of a reference dose rate and a correction for the effect of the shallow traps. Good agreement was found between reference doses and doses derived from the RL-signal using the new algorithm (the standard deviation of the residuals were ∼2% including phantom positioning errors). The RL-algorithm was found to greatly reduce the influence of shallow traps in the range from 0 to 3 Gy and the RL dose-rate measurements with a time resolution of 0.1 s closely matched dose-rate changes monitored with an ionization chamber

  5. SignalR real-time application cookbook

    CERN Document Server

    Vespa, Roberto

    2014-01-01

    This book contains illustrated code examples to help you create real-time, asynchronous, and bi-directional client-server applications. Each recipe will concentrate on one specific aspect of application development with SignalR showing you how that aspect can be used proficiently. Different levels of developers will find this book useful. Beginners will be able to learn all the fundamental concepts of SignalR, quickly becoming productive in a difficult arena. Experienced programmers will find in this book a handy and useful collection of ready-made solutions to common use cases, which they wil

  6. A preferential design approach for energy-efficient and robust implantable neural signal processing hardware.

    Science.gov (United States)

    Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup

    2009-01-01

    For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.

  7. Time-Frequency Analysis of Signals Generated by Rotating Machines

    Directory of Open Access Journals (Sweden)

    R. Zetik

    1999-06-01

    Full Text Available This contribution is devoted to the higher order time-frequency analyses of signals. Firstly, time-frequency representations of higher order (TFRHO are defined. Then L-Wigner distribution (LWD is given as a special case of TFRHO. Basic properties of LWD are illustrated based on the analysis of mono-component and multi-component synthetic signals and acoustical signals generated by rotating machine. The obtained results confirm usefulness of LWD application for the purpose of rotating machine condition monitoring.

  8. 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...

  9. Searching for patterns in TJ-II time evolution signals

    International Nuclear Information System (INIS)

    Farias, G.; Dormido-Canto, S.; Vega, J.; Sanchez, J.; Duro, N.; Dormido, R.; Ochando, M.; Santos, M.; Pajares, G.

    2006-01-01

    Since fusion plasma experiments generate hundreds of signals, it is important for their analysis to have automatic mechanisms for searching for similarities and retrieving specific data from the signal database. This paper describes a technique for searching in the TJ-II database that combines support vector machines and similarity query methods. Firstly, plasma signals are pre-processed by wavelet transform or discrete Fourier transform to reduce the dimensionality of the problem and to extract their main features. Secondly, support vector machines are used to classify a set of signals by reference to an input signal. Finally, similarity query methods (Euclidean distance and bounding envelope) are used to search the set of signals that best matches the input signal

  10. 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...

  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. 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....

  13. Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals.

    Science.gov (United States)

    Zhang, Y; Huang, S L; Wang, S; Zhao, W

    2016-05-01

    The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert-Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of wave detection signals.

  14. Real-Time Audio Processing on the T-CREST Multicore Platform

    DEFF Research Database (Denmark)

    Ausin, Daniel Sanz; Pezzarossa, Luca; Schoeberl, Martin

    2017-01-01

    of the audio signal. This paper presents a real-time multicore audio processing system based on the T-CREST platform. T-CREST is a time-predictable multicore processor for real-time embedded systems. Multiple audio effect tasks have been implemented, which can be connected together in different configurations...... forming sequential and parallel effect chains, and using a network-onchip for intercommunication between processors. The evaluation of the system shows that real-time processing of multiple effect configurations is possible, and that the estimation and control of latency ensures real-time behavior.......Multicore platforms are nowadays widely used for audio processing applications, due to the improvement of computational power that they provide. However, some of these systems are not optimized for temporally constrained environments, which often leads to an undesired increase in the latency...

  15. 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...

  16. Signal sciences workshop proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Candy, J.V.

    1997-05-01

    This meeting is aimed primarily at signal processing and controls. The technical program for the 1997 Workshop includes a variety of efforts in the Signal Sciences with applications in the Microtechnology Area a new program at LLNL and a future area of application for both Signal/Image Sciences. Special sessions organized by various individuals in Seismic and Optical Signal Processing as well as Micro-Impulse Radar Processing highlight the program, while the speakers at the Signal Processing Applications session discuss various applications of signal processing/control to real world problems. For the more theoretical, a session on Signal Processing Algorithms was organized as well as for the more pragmatic, featuring a session on Real-Time Signal Processing.

  17. Signal sciences workshop. Proceedings

    International Nuclear Information System (INIS)

    Candy, J.V.

    1997-01-01

    This meeting is aimed primarily at signal processing and controls. The technical program for the 1997 Workshop includes a variety of efforts in the Signal Sciences with applications in the Microtechnology Area a new program at LLNL and a future area of application for both Signal/Image Sciences. Special sessions organized by various individuals in Seismic and Optical Signal Processing as well as Micro-Impulse Radar Processing highlight the program, while the speakers at the Signal Processing Applications session discuss various applications of signal processing/control to real world problems. For the more theoretical, a session on Signal Processing Algorithms was organized as well as for the more pragmatic, featuring a session on Real-Time Signal Processing

  18. Method and apparatus for signal processing in a sensor system for use in spectroscopy

    Science.gov (United States)

    O'Connor, Paul [Bellport, NY; DeGeronimo, Gianluigi [Nesconset, NY; Grosholz, Joseph [Natrona Heights, PA

    2008-05-27

    A method for processing pulses arriving randomly in time on at least one channel using multiple peak detectors includes asynchronously selecting a non-busy peak detector (PD) in response to a pulse-generated trigger signal, connecting the channel to the selected PD in response to the trigger signal, and detecting a pulse peak amplitude. Amplitude and time of arrival data are output in first-in first-out (FIFO) sequence. An apparatus includes trigger comparators to generate the trigger signal for the pulse-receiving channel, PDs, a switch for connecting the channel to the selected PD, and logic circuitry which maintains the write pointer. Also included, time-to-amplitude converters (TACs) convert time of arrival to analog voltage and an analog multiplexer provides FIFO output. A multi-element sensor system for spectroscopy includes detector elements, channels, trigger comparators, PDs, a switch, and a logic circuit with asynchronous write pointer. The system includes TACs, a multiplexer and analog-to-digital converter.

  19. K-mean clustering algorithm for processing signals from compound semiconductor detectors

    International Nuclear Information System (INIS)

    Tada, Tsutomu; Hitomi, Keitaro; Wu, Yan; Kim, Seong-Yun; Yamazaki, Hiromichi; Ishii, Keizo

    2011-01-01

    The K-mean clustering algorithm was employed for processing signal waveforms from TlBr detectors. The signal waveforms were classified based on its shape reflecting the charge collection process in the detector. The classified signal waveforms were processed individually to suppress the pulse height variation of signals due to the charge collection loss. The obtained energy resolution of a 137 Cs spectrum measured with a 0.5 mm thick TlBr detector was 1.3% FWHM by employing 500 clusters.

  20. Novel ultra-wideband photonic signal generation and transmission featuring digital signal processing bit error rate measurements

    DEFF Research Database (Denmark)

    Gibbon, Timothy Braidwood; Yu, Xianbin; Tafur Monroy, Idelfonso

    2009-01-01

    We propose the novel generation of photonic ultra-wideband signals using an uncooled DFB laser. For the first time we experimentally demonstrate bit-for-bit DSP BER measurements for transmission of a 781.25 Mbit/s photonic UWB signal.......We propose the novel generation of photonic ultra-wideband signals using an uncooled DFB laser. For the first time we experimentally demonstrate bit-for-bit DSP BER measurements for transmission of a 781.25 Mbit/s photonic UWB signal....

  1. Beam induced transit time signals at SPEAR

    International Nuclear Information System (INIS)

    McConnell, R.A.

    1975-01-01

    Beam induced signals at frequencies related to inter-cavity transit times have been detected at SPEAR. Whether this effect enters significantly into beam instabilities has not yet been determined. Preliminary experiments suggest that under certain conditions at low energy (1.5 GeV) , when μ/sub s/, passes through one of the transit time resonances, some current is lost. Care must be taken, however, not to confuse this effect, if it exists, with synchrobetatron resonances and with an as yet unexplained vertical instability in SPEAR. At high energy (3.7 GeV), no effect has been shown to exist, though detectable signals are present. 2 refs., 2 tabs

  2. 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.

  3. 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

  4. Time-resolved single-shot terahertz time-domain spectroscopy for ultrafast irreversible processes

    Science.gov (United States)

    Zhai, Zhao-Hui; Zhong, Sen-Cheng; Li, Jun; Zhu, Li-Guo; Meng, Kun; Li, Jiang; Liu, Qiao; Peng, Qi-Xian; Li, Ze-Ren; Zhao, Jian-Heng

    2016-09-01

    Pulsed terahertz spectroscopy is suitable for spectroscopic diagnostics of ultrafast events. However, the study of irreversible or single shot ultrafast events requires ability to record transient properties at multiple time delays, i.e., time resolved at single shot level, which is not available currently. Here by angular multiplexing use of femtosecond laser pulses, we developed and demonstrated a time resolved, transient terahertz time domain spectroscopy technique, where burst mode THz pulses were generated and then detected in a single shot measurement manner. The burst mode THz pulses contain 2 sub-THz pulses, and the time gap between them is adjustable up to 1 ns with picosecond accuracy, thus it can be used to probe the single shot event at two different time delays. The system can detect the sub-THz pulses at 0.1 THz-2.5 THz range with signal to noise ratio (SNR) of ˜400 and spectrum resolution of 0.05 THz. System design was described here, and optimizations of single shot measurement of THz pulses were discussed in detail. Methods to improve SNR were also discussed in detail. A system application was demonstrated where pulsed THz signals at different time delays of the ultrafast process were successfully acquired within single shot measurement. This time resolved transient terahertz time domain spectroscopy technique provides a new diagnostic tool for irreversible or single shot ultrafast events where dynamic information can be extracted at terahertz range within one-shot experiment.

  5. 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

  6. Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Y., E-mail: thuzhangyu@foxmail.com; Huang, S. L., E-mail: huangsling@tsinghua.edu.cn; Wang, S.; Zhao, W. [State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084 (China)

    2016-05-15

    The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.

  7. Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals

    International Nuclear Information System (INIS)

    Zhang, Y.; Huang, S. L.; Wang, S.; Zhao, W.

    2016-01-01

    The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.

  8. Master Clock and Time-Signal-Distribution System

    Science.gov (United States)

    Tjoelker, Robert; Calhoun, Malcolm; Kuhnle, Paul; Sydnor, Richard; Lauf, John

    2007-01-01

    A timing system comprising an electronic master clock and a subsystem for distributing time signals from the master clock to end users is undergoing development to satisfy anticipated timing requirements of NASA s Deep Space Network (DSN) for the next 20 to 30 years. This system has a modular, flexible, expandable architecture that is easier to operate and maintain than the present frequency and timing subsystem (FTS).

  9. 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.

  10. Simultaneous hit finding and timing method for pulse shape analysis of drift chamber signals

    Energy Technology Data Exchange (ETDEWEB)

    Schaile, D; Schaile, O; Schwarz, J

    1986-01-01

    An algorithm for the analysis of the digitized signal waveform of drift chamber pulses is described which yields a good multihit resolution and an accurate drift time determination with little processing time. The method has been tested and evaluated with measured pulse shapes from the full size prototype of the OPAL central detector which were digitized by 100 MHz FADCs. (orig.).

  11. Simultaneous hit finding and timing method for pulse shape analysis of drift chamber signals

    Energy Technology Data Exchange (ETDEWEB)

    Schaile, D; Schaile, O; Schwarz, J

    1986-01-01

    An algorithm for the analysis of the digitized signal waveform of drift chamber pulses is described which yields a good multihit resolution and an accurate drift time determination with little processing time. The method has been tested and evaluated with measured pulse shapes from the full size prototype of the OPAL central detector which were digitized by 100 MHz FADCs.

  12. Signal processing and electronics for nuclear spectrometry. Proceedings of a technical meeting

    International Nuclear Information System (INIS)

    2009-12-01

    The IAEA has responded to Member States needs by implementing programmatic activities that provide interested Member States, particularly those in developing countries, with support to increase, and in some cases establish national and regional capabilities for the proper operation, calibration, maintenance and utilization of instruments in nuclear spectrometry applications. Technological advances in instrumentation, as well as the consequent high rate of obsolescence, make it important for nuclear instrumentation laboratories in Member States to keep their knowledge and skills up to date. This publication reviews the current status, developments and trends in electronics and digital methods for nuclear spectrometry, providing useful information for interested Member States to keep pace with new and evolving technologies. All nuclear spectrometry systems contain electronic circuits and devices, commonly referred to as front-end electronics, which accept and process the electrical signals produced by radiation detectors. This front-end electronics are composed of a chain of signal processing subsystems that filter, amplify, shape, and digitise these electrical signals to finally produce digitally encoded information about the type and nature of the radiation that stimulated the radiation detector. The design objective of front-end electronics is to obtain maximum information about the radiation and with the highest possible accuracy. Historically, the front-end electronics has consisted of all analog components. The performance delivered has increased continually over time through the development and implementation of new and improved analog electronics and electronic designs. The development of digital electronics, programmable logic, and digital signal processing techniques has now enabled most of the analog front-end electronics to be replaced by digital electronics, opening up new opportunities and delivering new benefits not previously achievable. Digital

  13. 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

  14. Signal Processing of Ground Penetrating Radar Using Spectral Estimation Techniques to Estimate the Position of Buried Targets

    Directory of Open Access Journals (Sweden)

    Shanker Man Shrestha

    2003-11-01

    Full Text Available Super-resolution is very important for the signal processing of GPR (ground penetration radar to resolve closely buried targets. However, it is not easy to get high resolution as GPR signals are very weak and enveloped by the noise. The MUSIC (multiple signal classification algorithm, which is well known for its super-resolution capacity, has been implemented for signal and image processing of GPR. In addition, conventional spectral estimation technique, FFT (fast Fourier transform, has also been implemented for high-precision receiving signal level. In this paper, we propose CPM (combined processing method, which combines time domain response of MUSIC algorithm and conventional IFFT (inverse fast Fourier transform to obtain a super-resolution and high-precision signal level. In order to support the proposal, detailed simulation was performed analyzing SNR (signal-to-noise ratio. Moreover, a field experiment at a research field and a laboratory experiment at the University of Electro-Communications, Tokyo, were also performed for thorough investigation and supported the proposed method. All the simulation and experimental results are presented.

  15. 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

  16. Comparative of signal processing techniques for micro-Doppler signature extraction with automotive radar systems

    Science.gov (United States)

    Rodriguez-Hervas, Berta; Maile, Michael; Flores, Benjamin C.

    2014-05-01

    In recent years, the automotive industry has experienced an evolution toward more powerful driver assistance systems that provide enhanced vehicle safety. These systems typically operate in the optical and microwave regions of the electromagnetic spectrum and have demonstrated high efficiency in collision and risk avoidance. Microwave radar systems are particularly relevant due to their operational robustness under adverse weather or illumination conditions. Our objective is to study different signal processing techniques suitable for extraction of accurate micro-Doppler signatures of slow moving objects in dense urban environments. Selection of the appropriate signal processing technique is crucial for the extraction of accurate micro-Doppler signatures that will lead to better results in a radar classifier system. For this purpose, we perform simulations of typical radar detection responses in common driving situations and conduct the analysis with several signal processing algorithms, including short time Fourier Transform, continuous wavelet or Kernel based analysis methods. We take into account factors such as the relative movement between the host vehicle and the target, and the non-stationary nature of the target's movement. A comparison of results reveals that short time Fourier Transform would be the best approach for detection and tracking purposes, while the continuous wavelet would be the best suited for classification purposes.

  17. 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.

  18. Ictal time-irreversible intracranial EEG signals as markers of the epileptogenic zone.

    Science.gov (United States)

    Schindler, Kaspar; Rummel, Christian; Andrzejak, Ralph G; Goodfellow, Marc; Zubler, Frédéric; Abela, Eugenio; Wiest, Roland; Pollo, Claudio; Steimer, Andreas; Gast, Heidemarie

    2016-09-01

    To show that time-irreversible EEG signals recorded with intracranial electrodes during seizures can serve as markers of the epileptogenic zone. We use the recently developed method of mapping time series into directed horizontal graphs (dHVG). Each node of the dHVG represents a time point in the original intracranial EEG (iEEG) signal. Statistically significant differences between the distributions of the nodes' number of input and output connections are used to detect time-irreversible iEEG signals. In 31 of 32 seizure recordings we found time-irreversible iEEG signals. The maximally time-irreversible signals always occurred during seizures, with highest probability in the middle of the first seizure half. These signals spanned a large range of frequencies and amplitudes but were all characterized by saw-tooth like shaped components. Brain regions removed from patients who became post-surgically seizure-free generated significantly larger time-irreversibilities than regions removed from patients who still had seizures after surgery. Our results corroborate that ictal time-irreversible iEEG signals can indeed serve as markers of the epileptogenic zone and can be efficiently detected and quantified in a time-resolved manner by dHVG based methods. Ictal time-irreversible EEG signals can help to improve pre-surgical evaluation in patients suffering from pharmaco-resistant epilepsies. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  19. Silicon nanowires for ultra-fast and ultrabroadband optical signal processing

    DEFF Research Database (Denmark)

    Ji, Hua; Hu, Hao; Pu, Minhao

    2015-01-01

    In this paper, we present recent research on silicon nanowires for ultra-fast and ultra-broadband optical signal processing at DTU Fotonik. The advantages and limitations of using silicon nanowires for optical signal processing are revealed through experimental demonstrations of various optical...

  20. 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

  1. Real-time bicycle detection at signalized intersections using thermal imaging technology

    Science.gov (United States)

    Collaert, Robin

    2013-02-01

    More and more governments and authorities around the world are promoting the use of bicycles in cities, as this is healthy for the bicyclist and improves the quality of life in general. Safety and efficiency of bicyclists has become a major focus. To achieve this, there is a need for a smarter approach towards the control of signalized intersections. Various traditional detection technologies, such as video, microwave radar and electromagnetic loops, can be used to detect vehicles at signalized intersections, but none of these can consistently separate bikes from other traffic, day and night and in various weather conditions. As bikes should get a higher priority and also require longer green time to safely cross the signalized intersection, traffic managers are looking for alternative detection systems that can make the distinction between bicycles and other vehicles near the stop bar. In this paper, the drawbacks of a video-based approach are presented, next to the benefits of a thermal-video-based approach for vehicle presence detection with separation of bicycles. Also, the specific technical challenges are highlighted in developing a system that combines thermal image capturing, image processing and output triggering to the traffic light controller in near real-time and in a single housing.

  2. Fourth year progress report on the co-ordinated research programme on signal processing techniques for sodium boiling noise detection

    International Nuclear Information System (INIS)

    Singh, O.P.; Prabhakar, R.; Reddy, C.P.; Vyjayanthi, R.K.; Srinivasan, G.S.

    1989-01-01

    The present paper deals with investigations of acoustic signals from a boiling experiment performed on the BOR 60 reactor in the USSR. 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. A proposal for in-service boiling monitoring by acoustic means is described. (author). 4 refs, 11 figs, 5 tabs

  3. Third year progress report on the co-ordinated research programme on signal processing techniques for sodium boiling noise detection

    International Nuclear Information System (INIS)

    Singh, O.P.; Prabhakar, R.; Reddy, C.P.; Vyjayanthi, R.K.; Srinivasan, G.S.

    1989-01-01

    The present paper deals with investigations of acoustic signals from a boiling experiment performed on the BOR 60 reactor in the USSR. 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. A proposal for in-service boiling monitoring by acoustic means is described. (author). 1 ref., 13 figs, 4 tabs

  4. Signal processing issues for the exploitation of pulse-to-pulse encoding SAR transponders

    DEFF Research Database (Denmark)

    Merryman Boncori, John Peter; Schiavon, Giovanni

    2008-01-01

    -encoding point scatterers and distributed ones. A time-domain processing algorithm and a code synchronization procedure are proposed and validated on simulated data and on a European Remote Sensing Satellite-2 data set containing prototypes of such a device. The interaction of the transponder signal with terrain...

  5. Signal process and profile reconstruction of stress corrosion crack by eddy current test

    International Nuclear Information System (INIS)

    Zhang Siquan; Chen Tiequn; Liu Guixiong

    2008-01-01

    The reconstruction of crack profiles is very important in the NDE (nondestructive evaluation) of critical structures, such as pressure vessel and tubes in heat exchangers. First a wavelet transform signal processing technique is used to reduce noise and other non-defect signals from the signals of crack, and then based on an artificial neural network method, the crack profiles are reconstructed. Although the results reveal that this method is with many advantages such as a short CPU time and precision for reconstruction,it does have some drawbacks, for example, the database generation and network training is a much time consuming work. Moreover, this approach does not expressly reconstruct the distribution of conductivity inside a crack, so the reliability of a reconstructed crack shape is unknown. But in practical application, if we do not consider the multiple cracks, this method can be used to reconstruct the natural crack. (authors)

  6. Tidal Analysis Using Time–Frequency Signal Processing and Information Clustering

    Directory of Open Access Journals (Sweden)

    Antonio M. Lopes

    2017-07-01

    Full Text Available Geophysical time series have a complex nature that poses challenges to reaching assertive conclusions, and require advanced mathematical and computational tools to unravel embedded information. In this paper, time–frequency methods and hierarchical clustering (HC techniques are combined for processing and visualizing tidal information. In a first phase, the raw data are pre-processed for estimating missing values and obtaining dimensionless reliable time series. In a second phase, the Jensen–Shannon divergence is adopted for measuring dissimilarities between data collected at several stations. The signals are compared in the frequency and time–frequency domains, and the HC is applied to visualize hidden relationships. In a third phase, the long-range behavior of tides is studied by means of power law functions. Numerical examples demonstrate the effectiveness of the approach when dealing with a large volume of real-world data.

  7. 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

  8. PAU/GNSS-R: Implementation, Performance and First Results of a Real-Time Delay-Doppler Map Reflectometer Using Global Navigation Satellite System Signals

    Directory of Open Access Journals (Sweden)

    Enric Valencia

    2008-05-01

    Full Text Available Signals from Global Navigation Satellite Systems (GNSS were originally conceived for position and speed determination, but they can be used as signals of opportunity as well. The reflection process over a given surface modifies the properties of the scattered signal, and therefore, by processing the reflected signal, relevant geophysical data regarding the surface under study (land, sea, ice… can be retrieved. In essence, a GNSS-R receiver is a multi-channel GNSS receiver that computes the received power from a given satellite at a number of different delay and Doppler bins of the incoming signal. The first approaches to build such a receiver consisted of sampling and storing the scattered signal for later post-processing. However, a real-time approach to the problem is desirable to obtain immediately useful geophysical variables and reduce the amount of data. The use of FPGA technology makes this possible, while at the same time the system can be easily reconfigured. The signal tracking and processing constraints made necessary to fully design several new blocks. The uniqueness of the implemented system described in this work is the capability to compute in real-time Delay-Doppler maps (DDMs either for four simultaneous satellites or just one, but with a larger number of bins. The first tests have been conducted from a cliff over the sea and demonstrate the successful performance of the instrument to compute DDMs in real-time from the measured reflected GNSS/R signals. The processing of these measurements shall yield quantitative relationships between the sea state (mainly driven by the surface wind and the swell and the overall DDM shape. The ultimate goal is to use the DDM shape to correct the sea state influence on the L-band brightness temperature to improve the retrieval of the sea surface salinity (SSS.

  9. An Application of Reassigned Time-Frequency Representations for Seismic Noise/Signal Decomposition

    Science.gov (United States)

    Mousavi, S. M.; Langston, C. A.

    2016-12-01

    Seismic data recorded by surface arrays are often strongly contaminated by unwanted noise. This background noise makes the detection of small magnitude events difficult. An automatic method for seismic noise/signal decomposition is presented based upon an enhanced time-frequency representation. Synchrosqueezing is a time-frequency reassignment method aimed at sharpening a time-frequency picture. Noise can be distinguished from the signal and suppressed more easily in this reassigned domain. The threshold level is estimated using a general cross validation approach that does not rely on any prior knowledge about the noise level. Efficiency of thresholding has been improved by adding a pre-processing step based on higher order statistics and a post-processing step based on adaptive hard-thresholding. In doing so, both accuracy and speed of the denoising have been improved compared to our previous algorithms (Mousavi and Langston, 2016a, 2016b; Mousavi et al., 2016). The proposed algorithm can either kill the noise (either white or colored) and keep the signal or kill the signal and keep the noise. Hence, It can be used in either normal denoising applications or in ambient noise studies. Application of the proposed method on synthetic and real seismic data shows the effectiveness of the method for denoising/designaling of local microseismic, and ocean bottom seismic data. References: Mousavi, S.M., C. A. Langston., and S. P. Horton (2016), Automatic Microseismic Denoising and Onset Detection Using the Synchrosqueezed-Continuous Wavelet Transform. Geophysics. 81, V341-V355, doi: 10.1190/GEO2015-0598.1. Mousavi, S.M., and C. A. Langston (2016a), Hybrid Seismic Denoising Using Higher-Order Statistics and Improved Wavelet Block Thresholding. Bull. Seismol. Soc. Am., 106, doi: 10.1785/0120150345. Mousavi, S.M., and C.A. Langston (2016b), Adaptive noise estimation and suppression for improving microseismic event detection, Journal of Applied Geophysics., doi: http

  10. 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....

  11. The Time-Frequency Signatures of Advanced Seismic Signals Generated by Debris Flows

    Science.gov (United States)

    Chu, C. R.; Huang, C. J.; Lin, C. R.; Wang, C. C.; Kuo, B. Y.; Yin, H. Y.

    2014-12-01

    The seismic monitoring is expected to reveal the process of debris flow from the initial area to alluvial fan, because other field monitoring techniques, such as the video camera and the ultrasonic sensor, are limited by detection range. For this reason, seismic approaches have been used as the detection system of debris flows over the past few decades. The analysis of the signatures of the seismic signals in time and frequency domain can be used to identify the different phases of debris flow. This study dedicates to investigate the different stages of seismic signals due to debris flow, including the advanced signal, the main front, and the decaying tail. Moreover, the characteristics of the advanced signals forward to the approach of main front were discussed for the warning purpose. This study presents a permanent system, composed by two seismometers, deployed along the bank of Ai-Yu-Zi Creek in Nantou County, which is one of the active streams with debris flow in Taiwan. The three axes seismometer with frequency response of 7 sec - 200 Hz was developed by the Institute of Earth Sciences (IES), Academia Sinica for the purpose to detect debris flow. The original idea of replacing the geophone system with the seismometer technique was for catching the advanced signals propagating from the upper reach of the stream before debris flow arrival because of the high sensitivity. Besides, the low frequency seismic waves could be also early detected because of the low attenuation. However, for avoiding other unnecessary ambient vibrations, the sensitivity of seismometer should be lower than the general seismometer for detecting teleseism. Three debris flows with different mean velocities were detected in 2013 and 2014. The typical triangular shape was obviously demonstrated in time series data and the spectrograms of the seismic signals from three events. The frequency analysis showed that enormous debris flow bearing huge boulders would induce low frequency seismic

  12. Algorithm for removing scalp signals from functional near-infrared spectroscopy signals in real time using multidistance optodes.

    Science.gov (United States)

    Kiguchi, Masashi; Funane, Tsukasa

    2014-11-01

    A real-time algorithm for removing scalp-blood signals from functional near-infrared spectroscopy signals is proposed. Scalp and deep signals have different dependencies on the source-detector distance. These signals were separated using this characteristic. The algorithm was validated through an experiment using a dynamic phantom in which shallow and deep absorptions were independently changed. The algorithm for measurement of oxygenated and deoxygenated hemoglobins using two wavelengths was explicitly obtained. This algorithm is potentially useful for real-time systems, e.g., brain-computer interfaces and neuro-feedback systems.

  13. The design of photoelectric signal processing system for a nuclear magnetic resonance gyroscope based on FPGA

    Science.gov (United States)

    Zhang, Xian; Zhou, Binquan; Li, Hong; Zhao, Xinghua; Mu, Weiwei; Wu, Wenfeng

    2017-10-01

    Navigation technology is crucial to the national defense and military, which can realize the measurement of orientation, positioning, attitude and speed for moving object. Inertial navigation is not only autonomous, real-time, continuous, hidden, undisturbed but also no time-limited and environment-limited. The gyroscope is the core component of the inertial navigation system, whose precision and size are the bottleneck of the performance. However, nuclear magnetic resonance gyroscope is characteristic of the advantage of high precision and small size. Nuclear magnetic resonance gyroscope can meet the urgent needs of high-tech weapons and equipment development of new generation. This paper mainly designs a set of photoelectric signal processing system for nuclear magnetic resonance gyroscope based on FPGA, which process and control the information of detecting laser .The photoelectric signal with high frequency carrier is demodulated by in-phase and quadrature demodulation method. Finally, the processing system of photoelectric signal can compensate the residual magnetism of the shielding barrel and provide the information of nuclear magnetic resonance gyroscope angular velocity.

  14. Complex on the base of the ISKRA 226.6 personal computer for nuclear quadrupole resonance signal processing

    International Nuclear Information System (INIS)

    Morgunov, V.G.; Kravchenko, Eh.A.

    1988-01-01

    Complex, designed to conduct investigations by means of nuclear quadrupole resonance (NQR) method, which includes radiospectrometer, multichannel spectrum analyzer and ISKRA 226.6 personal computer, is developed. Analog-to-digital converter (ADC) with buffer storage device, interface and microcomputer are used to process NQR-signals. ADS conversion time is no more, than 50 ns, linearity - 1%. Programs on Fourier analysis of NQR-signals and calculation of relaxation times are developed

  15. Precise timing correlation in telemetry recording and processing systems

    Science.gov (United States)

    Pickett, R. B.; Matthews, F. L.

    1973-01-01

    Independent PCM telemetry data signals received from missiles must be correlated to within + or - 100 microseconds for comparison with radar data. Tests have been conducted to determine RF antenna receiving system delays; delays associated with wideband analog tape recorders used in the recording, dubbing and repdocuing processes; and uncertainties associated with computer processed time tag data. Several methods used in the recording of timing are evaluated. Through the application of a special time tagging technique, the cumulative timing bias from all sources is determined and the bias removed from final data. Conclusions show that relative time differences in receiving, recording, playback and processing of two telemetry links can be accomplished with a + or - 4 microseconds accuracy. In addition, the absolute time tag error (with respect to UTC) can be reduced to less than 15 microseconds. This investigation is believed to be the first attempt to identify the individual error contributions within the telemetry system and to describe the methods of error reduction within the telemetry system and to describe the methods of error reduction and correction.

  16. Digital timing: sampling frequency, anti-aliasing filter and signal interpolation filter dependence on timing resolution

    International Nuclear Information System (INIS)

    Cho, Sanghee; Grazioso, Ron; Zhang Nan; Aykac, Mehmet; Schmand, Matthias

    2011-01-01

    The main focus of our study is to investigate how the performance of digital timing methods is affected by sampling rate, anti-aliasing and signal interpolation filters. We used the Nyquist sampling theorem to address some basic questions such as what will be the minimum sampling frequencies? How accurate will the signal interpolation be? How do we validate the timing measurements? The preferred sampling rate would be as low as possible, considering the high cost and power consumption of high-speed analog-to-digital converters. However, when the sampling rate is too low, due to the aliasing effect, some artifacts are produced in the timing resolution estimations; the shape of the timing profile is distorted and the FWHM values of the profile fluctuate as the source location changes. Anti-aliasing filters are required in this case to avoid the artifacts, but the timing is degraded as a result. When the sampling rate is marginally over the Nyquist rate, a proper signal interpolation is important. A sharp roll-off (higher order) filter is required to separate the baseband signal from its replicates to avoid the aliasing, but in return the computation will be higher. We demonstrated the analysis through a digital timing study using fast LSO scintillation crystals as used in time-of-flight PET scanners. From the study, we observed that there is no significant timing resolution degradation down to 1.3 Ghz sampling frequency, and the computation requirement for the signal interpolation is reasonably low. A so-called sliding test is proposed as a validation tool checking constant timing resolution behavior of a given timing pick-off method regardless of the source location change. Lastly, the performance comparison for several digital timing methods is also shown.

  17. Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

    Science.gov (United States)

    Tam, Wing-Kin; Yang, Zhi

    2018-05-01

    Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Antipersistent dynamics in short time scale variability of self-potential signals

    Directory of Open Access Journals (Sweden)

    M. Ragosta

    2000-06-01

    Full Text Available Time scale properties of self-potential signals are investigated through the analysis of the second order structure function (variogram, a powerful tool to investigate the spatial and temporal variability of observational data. In this work we analyse two sequences of self-potential values measured by means of a geophysical monitoring array located in a seismically active area of Southern Italy. The range of scales investigated goes from a few minutes to several days. It is shown that signal fluctuations are characterised by two time scale ranges in which self-potential variability appears to follow slightly different dynamical behaviours. Results point to the presence of fractal, non stationary features expressing a long term correlation with scaling coefficients which are the clue of stabilising mechanisms. In the scale ranges in which the series show scale invariant behaviour, self-potentials evolve like fractional Brownian motions with anticorrelated increments typical of processes regulated by negative feedback mechanisms (antipersistence. On scales below about 6 h the strength of such an antipersistence appears to be slightly greater than that observed on larger time scales where the fluctuations are less efficiently stabilised.

  19. Low-Latency Digital Signal Processing for Feedback and Feedforward in Quantum Computing and Communication

    Science.gov (United States)

    Salathé, Yves; Kurpiers, Philipp; Karg, Thomas; Lang, Christian; Andersen, Christian Kraglund; Akin, Abdulkadir; Krinner, Sebastian; Eichler, Christopher; Wallraff, Andreas

    2018-03-01

    Quantum computing architectures rely on classical electronics for control and readout. Employing classical electronics in a feedback loop with the quantum system allows us to stabilize states, correct errors, and realize specific feedforward-based quantum computing and communication schemes such as deterministic quantum teleportation. These feedback and feedforward operations are required to be fast compared to the coherence time of the quantum system to minimize the probability of errors. We present a field-programmable-gate-array-based digital signal processing system capable of real-time quadrature demodulation, a determination of the qubit state, and a generation of state-dependent feedback trigger signals. The feedback trigger is generated with a latency of 110 ns with respect to the timing of the analog input signal. We characterize the performance of the system for an active qubit initialization protocol based on the dispersive readout of a superconducting qubit and discuss potential applications in feedback and feedforward algorithms.

  20. APNEA list mode data acquisition and real-time event processing

    Energy Technology Data Exchange (ETDEWEB)

    Hogle, R.A.; Miller, P. [GE Corporate Research & Development Center, Schenectady, NY (United States); Bramblett, R.L. [Lockheed Martin Specialty Components, Largo, FL (United States)

    1997-11-01

    The LMSC Active Passive Neutron Examinations and Assay (APNEA) Data Logger is a VME-based data acquisition system using commercial-off-the-shelf hardware with the application-specific software. It receives TTL inputs from eighty-eight {sup 3}He detector tubes and eight timing signals. Two data sets are generated concurrently for each acquisition session: (1) List Mode recording of all detector and timing signals, timestamped to 3 microsecond resolution; (2) Event Accumulations generated in real-time by counting events into short (tens of microseconds) and long (seconds) time bins following repetitive triggers. List Mode data sets can be post-processed to: (1) determine the optimum time bins for TRU assay of waste drums, (2) analyze a given data set in several ways to match different assay requirements and conditions and (3) confirm assay results by examining details of the raw data. Data Logger events are processed and timestamped by an array of 15 TMS320C40 DSPs and delivered to an embedded controller (PowerPC604) for interim disk storage. Three acquisition modes, corresponding to different trigger sources are provided. A standard network interface to a remote host system (Windows NT or SunOS) provides for system control, status, and transfer of previously acquired data. 6 figs.

  1. Digital signal processing and spectral analysis for scientists concepts and applications

    CERN Document Server

    Alessio, Silvia Maria

    2016-01-01

    This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the ne...

  2. An analyzer for pulse-interval times to study high-order effects in the processing of nuclear detector signals

    International Nuclear Information System (INIS)

    Denecke, B.; Jonge, S. de

    1998-01-01

    An electronic device to measure interval time density distributions of subsequent pulses in nuclear detectors and their electronics is described. The device has a pair-pulse resolution of 10 ns and 25 ns for 3 subsequent input signals. The conversion range is 4096 channels and the lowest channel width is 10 ns. Counter dead times, single and in series were studied and compared with the statistical model. True count rates were obtained from an exponential fit through the interval-time distribution

  3. EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone.

    Science.gov (United States)

    Blum, Sarah; Debener, Stefan; Emkes, Reiner; Volkening, Nils; Fudickar, Sebastian; Bleichner, Martin G

    2017-01-01

    Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.

  4. EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone

    Directory of Open Access Journals (Sweden)

    Sarah Blum

    2017-01-01

    Full Text Available Objective. Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android supports a standardized communication interface to exchange information with external software and hardware. Approach. In order to implement a closed-loop brain-computer interface (BCI on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.

  5. EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone

    Science.gov (United States)

    Debener, Stefan; Emkes, Reiner; Volkening, Nils; Fudickar, Sebastian; Bleichner, Martin G.

    2017-01-01

    Objective Our aim was the development and validation of a modular signal processing and classification application enabling online electroencephalography (EEG) signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and CLassification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach In order to implement a closed-loop brain-computer interface (BCI) on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. Main Results We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms. PMID:29349070

  6. Advanced pulse oximeter signal processing technology compared to simple averaging. I. Effect on frequency of alarms in the operating room.

    Science.gov (United States)

    Rheineck-Leyssius, A T; Kalkman, C J

    1999-05-01

    To determine the effect of a new signal processing technique (Oxismart, Nellcor, Inc., Pleasanton, CA) on the incidence of false pulse oximeter alarms in the operating room (OR). Prospective observational study. Nonuniversity hospital. 53 ASA physical status I, II, and III consecutive patients undergoing general anesthesia with tracheal intubation. In the OR we compared the number of alarms produced by a recently developed third generation pulse oximeter (Nellcor Symphony N-3000) with Oxismart signal processing technique and a conventional pulse oximeter (Criticare 504). Three pulse oximeters were used simultaneously in each patient: a Nellcor pulse oximeter, a Criticare with the signal averaging time set at 3 seconds (Criticareaverage3s) and a similar unit with the signal averaging time set at 21 seconds (Criticareaverage21s). For each pulse oximeter, the number of false (artifact) alarms was counted. One false alarm was produced by the Nellcor (duration 55 sec) and one false alarm by the Criticareaverage21s monitor (5 sec). The incidence of false alarms was higher in Criticareaverage3s. In eight patients, Criticareaverage3s produced 20 false alarms (p signal processing compared with the Criticare monitor with the longer averaging time of 21 seconds.

  7. 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.

  8. Implementation of an Antenna Array Signal Processing Breadboard for the Deep Space Network

    Science.gov (United States)

    Navarro, Robert

    2006-01-01

    The Deep Space Network Large Array will replace/augment 34 and 70 meter antenna assets. The array will mainly be used to support NASA's deep space telemetry, radio science, and navigation requirements. The array project will deploy three complexes in the western U.S., Australia, and European longitude each with 400 12m downlink antennas and a DSN central facility at JPL. THis facility will remotely conduct all real-time monitor and control for the network. Signal processing objectives include: provide a means to evaluate the performance of the Breadboard Array's antenna subsystem; design and build prototype hardware; demonstrate and evaluate proposed signal processing techniques; and gain experience with various technologies that may be used in the Large Array. Results are summarized..

  9. Prototype real-time baseband signal combiner. [deep space network

    Science.gov (United States)

    Howard, L. D.

    1980-01-01

    The design and performance of a prototype real-time baseband signal combiner, used to enhance the received Voyager 2 spacecraft signals during the Jupiter flyby, is described. Hardware delay paths, operating programs, and firmware are discussed.

  10. 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.

  11. Detectability of Granger causality for subsampled continuous-time neurophysiological processes.

    Science.gov (United States)

    Barnett, Lionel; Seth, Anil K

    2017-01-01

    Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity

  12. 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...

  13. An integrated nonlinear optical loop mirror in silicon photonics for all-optical signal processing

    Directory of Open Access Journals (Sweden)

    Zifei Wang

    2018-02-01

    Full Text Available The nonlinear optical loop mirror (NOLM has been studied for several decades and has attracted considerable attention for applications in high data rate optical communications and all-optical signal processing. The majority of NOLM research has focused on silica fiber-based implementations. While various fiber designs have been considered to increase the nonlinearity and manage dispersion, several meters to hundreds of meters of fiber are still required. On the other hand, there is increasing interest in developing photonic integrated circuits for realizing signal processing functions. In this paper, we realize the first-ever passive integrated NOLM in silicon photonics and demonstrate its application for all-optical signal processing. In particular, we show wavelength conversion of 10 Gb/s return-to-zero on-off keying (RZ-OOK signals over a wavelength range of 30 nm with error-free operation and a power penalty of less than 2.5 dB, we achieve error-free nonreturn to zero (NRZ-to-RZ modulation format conversion at 10 Gb/s also with a power penalty of less than 2.8 dB, and we obtain error-free all-optical time-division demultiplexing of a 40 Gb/s RZ-OOK data signal into its 10 Gb/s tributary channels with a maximum power penalty of 3.5 dB.

  14. 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...

  15. Acoustic Emission Signal Processing Technique to Characterize Reactor In-Pile Phenomena

    Energy Technology Data Exchange (ETDEWEB)

    Vivek Agarwal; Magdy Samy Tawfik; James A Smith

    2014-07-01

    Existing and developing advanced sensor technologies and instrumentation will allow non-intrusive in-pile measurement of temperature, extension, and fission gases when coupled with advanced signal processing algorithms. The transmitted measured sensor signals from inside to the outside of containment structure are corrupted by noise and are attenuated, thereby reducing the signal strength and signal-to-noise ratio. Identification and extraction of actual signal (representative of an in-pile phenomenon) is a challenging and complicated process. In this paper, empirical mode decomposition technique is proposed to reconstruct actual sensor signal by partially combining intrinsic mode functions. Reconstructed signal corresponds to phenomena and/or failure modes occurring inside the reactor. In addition, it allows accurate non-intrusive monitoring and trending of in-pile phenomena.

  16. 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

  17. 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

  18. Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator.

    Science.gov (United States)

    Wang, Zhiqiang; Li, Xiaolong; Xie, Yunde; Long, Zhiqiang

    2018-05-24

    In a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concerns, an architecture based on a new type of nonlinear second-order discrete tracking differentiator is proposed. The function of this signal processing architecture includes filtering signal noise and acquiring needed signals for levitation purposes. The proposed tracking differentiator possesses the advantages of quick convergence, no fluttering, and simple calculation. Tracking differentiator's frequency characteristics at different parameter values are studied in this paper. The performance of this new type of tracking differentiator is tested in a MATLAB simulation and this tracking-differentiator is implemented in Very-High-Speed Integrated Circuit Hardware Description Language (VHDL). In the end, experiments are conducted separately on a test board and a maglev train model. Simulation and experiment results show that the performance of this novel signal processing architecture can fulfill the real system requirement.

  19. Maglev Train Signal Processing Architecture Based on Nonlinear Discrete Tracking Differentiator

    Directory of Open Access Journals (Sweden)

    Zhiqiang Wang

    2018-05-01

    Full Text Available In a maglev train levitation system, signal processing plays an important role for the reason that some sensor signals are prone to be corrupted by noise due to the harsh installation and operation environment of sensors and some signals cannot be acquired directly via sensors. Based on these concerns, an architecture based on a new type of nonlinear second-order discrete tracking differentiator is proposed. The function of this signal processing architecture includes filtering signal noise and acquiring needed signals for levitation purposes. The proposed tracking differentiator possesses the advantages of quick convergence, no fluttering, and simple calculation. Tracking differentiator’s frequency characteristics at different parameter values are studied in this paper. The performance of this new type of tracking differentiator is tested in a MATLAB simulation and this tracking-differentiator is implemented in Very-High-Speed Integrated Circuit Hardware Description Language (VHDL. In the end, experiments are conducted separately on a test board and a maglev train model. Simulation and experiment results show that the performance of this novel signal processing architecture can fulfill the real system requirement.

  20. The high accuracy data processing system of laser interferometry signals based on MSP430

    Science.gov (United States)

    Qi, Yong-yue; Lin, Yu-chi; Zhao, Mei-rong

    2009-07-01

    Generally speaking there are two orthogonal signals used in single-frequency laser interferometer for differentiating direction and electronic subdivision. However there usually exist three errors with the interferential signals: zero offsets error, unequal amplitude error and quadrature phase shift error. These three errors have a serious impact on subdivision precision. Based on Heydemann error compensation algorithm, it is proposed to achieve compensation of the three errors. Due to complicated operation of the Heydemann mode, a improved arithmetic is advanced to decrease the calculating time effectively in accordance with the special characteristic that only one item of data will be changed in each fitting algorithm operation. Then a real-time and dynamic compensatory circuit is designed. Taking microchip MSP430 as the core of hardware system, two input signals with the three errors are turned into digital quantity by the AD7862. After data processing in line with improved arithmetic, two ideal signals without errors are output by the AD7225. At the same time two original signals are turned into relevant square wave and imported to the differentiating direction circuit. The impulse exported from the distinguishing direction circuit is counted by the timer of the microchip. According to the number of the pulse and the soft subdivision the final result is showed by LED. The arithmetic and the circuit are adopted to test the capability of a laser interferometer with 8 times optical path difference and the measuring accuracy of 12-14nm is achieved.

  1. Third year supplementary progress report on the co-ordinated research programme on signal processing techniques for sodium boiling noise detection

    International Nuclear Information System (INIS)

    Singh, O.P.; Prabhakar, R.; Reddy, C.P.; Vyjayanthi, R.K.; Srinivasan, G.S.

    1989-01-01

    The present paper deals with investigations of acoustic signals from a boiling experiment performed on the BOR 60 reactor in the USSR. 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. A proposal for in-service boiling monitoring by acoustic means is described. (author). 3 refs, 12 figs, 12 tabs

  2. 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...

  3. A scintillation detector signal processing technique with active pileup prevention for extending scintillation count rates

    International Nuclear Information System (INIS)

    Wong, W.H.; Li, H.

    1998-01-01

    A new method for processing signals from scintillation detectors is proposed for very high count-rate situations where multiple-event pileups are the norm. This method is designed to sort out and recover every impinging event from multiple-event pileups while maximizing the collection of scintillation signal for every event to achieve optimal accuracy in determining the energy of the event. For every detected event, this method cancels the remnant signals from previous events, and excludes the pileup of signals from following events. With this technique, pileup events can be recovered and the energy of every recovered event can be optimally measured despite multiple pileups. A prototype circuit demonstrated that the maximum count rates have been increased by more than 10 times, comparing to the standard pulse-shaping method, while the energy resolution is as good as that of the pulse shaping (or the fixed integration) method at normal count rates. At 2 x 10 6 events/sec for NaI(Tl), the true counts acquired are 3 times more than the delay-line clipping method (commonly used in fast processing designs) due to events recovered from pileups. Pulse-height spectra up to 3.5 x 10 6 events/sec have been studied

  4. 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...

  5. 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...

  6. Optics based signal processing methods for intraoperative blood vessel detection and quantification in real time (Conference Presentation)

    Science.gov (United States)

    Chaturvedi, Amal; Shukair, Shetha A.; Le Rolland, Paul; Vijayvergia, Mayank; Subramanian, Hariharan; Gunn, Jonathan W.

    2016-03-01

    Minimally invasive operations require surgeons to make difficult cuts to blood vessels and other tissues with impaired tactile and visual feedback. This leads to inadvertent cuts to blood vessels hidden beneath tissue, causing serious health risks to patients and a non-reimbursable financial burden to hospitals. Intraoperative imaging technologies have been developed, but these expensive systems can be cumbersome and provide only a high-level view of blood vessel networks. In this research, we propose a lean reflectance-based system, comprised of a dual wavelength LED, photodiode, and novel signal processing algorithms for rapid vessel characterization. Since this system takes advantage of the inherent pulsatile light absorption characteristics of blood vessels, no contrast agent is required for its ability to detect the presence of a blood vessel buried deep inside any tissue type (up to a cm) in real time. Once a vessel is detected, the system is able to estimate the distance of the vessel from the probe and the diameter size of the vessel (with a resolution of ~2mm), as well as delineate the type of tissue surrounding the vessel. The system is low-cost, functions in real-time, and could be mounted on already existing surgical tools, such as Kittner dissectors or laparoscopic suction irrigation cannulae. Having been successfully validated ex vivo, this technology will next be tested in a live porcine study and eventually in clinical trials.

  7. 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...

  8. Application of wavelet analysis to signal processing methods for eddy-current test

    International Nuclear Information System (INIS)

    Chen, G.; Yoneyama, H.; Yamaguchi, A.; Uesugi, N.

    1998-01-01

    This study deals with the application of wavelet analysis to detection and characterization of defects from eddy-current and ultrasonic testing signals of a low signal-to-noise ratio. Presented in this paper are the methods for processing eddy-current testing signals of heat exchanger tubes of a steam generator in a nuclear power plant. The results of processing eddy-current testing signals of tube testpieces with artificial flaws show that the flaw signals corrupted by noise and/or non-defect signals can be effectively detected and characterized by using the wavelet methods. (author)

  9. Time-Frequency Characterization of Cerebral Hemodynamics of Migraine Sufferers as Assessed by NIRS Signals

    Directory of Open Access Journals (Sweden)

    Filippo Molinari

    2010-01-01

    Full Text Available Near-infrared spectroscopy (NIRS is a noninvasive system for the real-time monitoring of the concentration of oxygenated (O2Hb and reduced (HHb hemoglobin in the brain cortex. O2Hb and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20–40 mHz and of the low frequencies (LF: 40–140 mHz. Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.

  10. Time-Frequency Characterization of Cerebral Hemodynamics of Migraine Sufferers as Assessed by NIRS Signals

    Directory of Open Access Journals (Sweden)

    Liboni William

    2010-01-01

    Full Text Available Abstract Near-infrared spectroscopy (NIRS is a noninvasive system for the real-time monitoring of the concentration of oxygenated ( and reduced (HHb hemoglobin in the brain cortex. and HHb concentrations vary in response to cerebral autoregulation. Sixty-eight women (14 migraineurs without aura, 49 migraineurs with aura, and 5 controls performed breath-holding and hyperventilation during NIRS recordings. Signals were processed using the Choi-Williams time-frequency transform in order to measure the power variation of the very-low frequencies (VLF: 20–40 mHz and of the low frequencies (LF: 40–140 mHz. Results showed that migraineurs without aura present different LF and VLF power levels than controls and migraineurs with aura. The accurate power measurement of the time-frequency analysis allowed for the discrimination of the subjects' hemodynamic patterns. The time-frequency analysis of NIRS signals can be used in clinical practice to assess cerebral hemodynamics.

  11. The time light signals of New Zealand: yet another way of communicating time in the pre-wireless era

    Science.gov (United States)

    Kinns, Roger

    2017-08-01

    The signalling of exact time using an array of lights appears to have been unique to New Zealand. It was a simple and effective solution for calibration of marine chronometers when transmission of time signals by wireless was in its infancy. Three lights, coloured green, red and white, were arranged in a vertical array. They were switched on in a defined sequence during the evening and then extinguished together to signal exact time. Time lights were first operated at the Dominion Observatory in Wellington during February 1912 and on the Ferry Building in Auckland during October 1915. The Wellington lights were immediately adjacent to the observatory buildings, but those in Auckland were operated using telegraph signals from Wellington. The timings varied over the years, but the same physical arrangement was retained at each location. The time light service was withdrawn during 1937, when wireless signals had become almost universally available for civil and navigation purposes.

  12. 2nd International Symposium on Signal Processing and Intelligent Recognition Systems

    CERN Document Server

    Bandyopadhyay, Sanghamitra; Krishnan, Sri; Li, Kuan-Ching; Mosin, Sergey; Ma, Maode

    2016-01-01

    This Edited Volume contains a selection of refereed and revised papers originally presented at the second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The program committee received 175 submissions. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 59 papers were finally selected. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas. .

  13. Detection and classification of defects in ultrasonic NDE signals using time-frequency representations

    Science.gov (United States)

    Qidwai, Uvais; Costa, Antonio H.; Chen, C. H.

    2000-05-01

    The ultrasonic wave, generated by a piezoelectric transducer coupled to the test specimen, propagates through the material and part of its energy is reflected when it encounters an non-homogeneity or discontinuity in its path, while the remainder is reflected by the back surface of the test specimen. Defect echo signals are masked by the characteristics of the measuring instruments, the propagation paths taken by the ultrasonic wave, and are corrupted by additive noise. This leads to difficulties in comparing and analyzing signals, particularly in automated defect identification systems employing different transducers. Further, the multi-component nature of material defects can add to the complexity of the defect identification criteria. With many one-dimensional (1-D) approaches, the multi-component defects can not be detected. Another drawback is that these techniques are not very robust for sharp ultrasonic peaks especially in a very hazardous environment. This paper proposes a technique based on the time-frequency representations (TFRs) of the real defect signals corresponding to artificially produced defects of various geometries in metals. Cohen's class (quadratic) TFRs with Gaussian kernels are then used to represent the signals in the time-frequency (TF) plane. Once the TFR is obtained, various image processing morphological techniques are applied to the TFR (e.g. region of interest masking, edge detection, and profile separation). Based on the results of these operations, a binary image is produced which, in turn, leads to a novel set of features. Using these new features, defects have not only been detected but also classified as flat-cut, angular-cut, and circular-drills. Moreover, with some modifications of the threshold levels of the TFR kernel design, our technique can be used in relatively hostile environments with SNRs as low as 0 dB. Another important characteristic of our approach is the detection of multiple defects. This consists of detection of

  14. A customizable system for real-time image processing using the Blackfin DSProcessor and the MicroC/OS-II real-time kernel

    Science.gov (United States)

    Coffey, Stephen; Connell, Joseph

    2005-06-01

    This paper presents a development platform for real-time image processing based on the ADSP-BF533 Blackfin processor and the MicroC/OS-II real-time operating system (RTOS). MicroC/OS-II is a completely portable, ROMable, pre-emptive, real-time kernel. The Blackfin Digital Signal Processors (DSPs), incorporating the Analog Devices/Intel Micro Signal Architecture (MSA), are a broad family of 16-bit fixed-point products with a dual Multiply Accumulate (MAC) core. In addition, they have a rich instruction set with variable instruction length and both DSP and MCU functionality thus making them ideal for media based applications. Using the MicroC/OS-II for task scheduling and management, the proposed system can capture and process raw RGB data from any standard 8-bit greyscale image sensor in soft real-time and then display the processed result using a simple PC graphical user interface (GUI). Additionally, the GUI allows configuration of the image capture rate and the system and core DSP clock rates thereby allowing connectivity to a selection of image sensors and memory devices. The GUI also allows selection from a set of image processing algorithms based in the embedded operating system.

  15. Pulsar timing signal from ultralight scalar dark matter

    International Nuclear Information System (INIS)

    Khmelnitsky, Andrei; Rubakov, Valery

    2014-01-01

    An ultralight free scalar field with mass around 10 −23 −10 −22 eV is a viable dark mater candidate, which can help to resolve some of the issues of the cold dark matter on sub-galactic scales. We consider the gravitational field of the galactic halo composed out of such dark matter. The scalar field has oscillating in time pressure, which induces oscillations of gravitational potential with amplitude of the order of 10 −15 and frequency in the nanohertz range. This frequency is in the range of pulsar timing array observations. We estimate the magnitude of the pulse arrival time residuals induced by the oscillating gravitational potential. We find that for a range of dark matter masses, the scalar field dark matter signal is comparable to the stochastic gravitational wave signal and can be detected by the planned SKA pulsar timing array experiment

  16. Simulation-based robust optimization for signal timing and setting.

    Science.gov (United States)

    2009-12-30

    The performance of signal timing plans obtained from traditional approaches for : pre-timed (fixed-time or actuated) control systems is often unstable under fluctuating traffic : conditions. This report develops a general approach for optimizing the ...

  17. 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.

  18. 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

  19. 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

  20. 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)

  1. 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...

  2. 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).

  3. Techware: www.sspnet.eu: A Web Portal for Social Signal Processing

    NARCIS (Netherlands)

    Vinciarelli, Alessandro; Ortega, A.; Pantic, Maja

    In this issue, “Best of the Web‿ focuses on introducing the social signal processing network (SSPNet), a large European collaboration aimed at establishing a research community in social signal processing (SSP), the new, emerging domain aimed at bringing social intelligence in computers.

  4. Attitude Control of a Satellite by using Digital Signal Processing

    Directory of Open Access Journals (Sweden)

    Adirelle C. Santana

    2012-03-01

    Full Text Available This article has discussed the development of a three-axis attitude digital controller for an artificial satellite using a digital signal processor. The main motivation of this study is the attitude control system of the satellite Multi-Mission Platform, developed by the Brazilian National Institute for Space Research for application in different sort of missions. The controller design was based on the theory of the Linear Quadratic Gaussian Regulator, synthesized from the linearized model of the motion of the satellite, i.e., the kinematics and dynamics of attitude. The attitude actuators considered in this study are pairs of cold gas jets powered by a pulse width/pulse frequency modulator. In the first stage of the project development, a system controller for continuous time was studied with the aim of testing the adequacy of the adopted control. The next steps had included an analysis of discretization techniques, the setting time of sampling rate, and the testing of the digital version of the Linear Quadratic Gaussian Regulator controller in the MATLAB/SIMULINK. To fulfill the study, the controller was implemented in a digital signal processor, specifically the Blackfin BF537 from Analog Devices, along with the pulse width/pulse frequency modulator. The validation tests used a scheme of co-simulation, where the model of the satellite was simulated in MATLAB/SIMULINK, while the controller and modulator were processed in the digital signal processor with a tool called Processor-In-the-Loop, which acted as a data communication link between both environments.function and required time to achieve a given mission accuracy are determined, and results are provided as illustration.

  5. 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.

  6. Free-running ADC- and FPGA-based signal processing method for brain PET using GAPD arrays

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Wei [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710 (Korea, Republic of); Choi, Yong, E-mail: ychoi.image@gmail.com [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Hong, Key Jo [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Kang, Jihoon [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710 (Korea, Republic of); Jung, Jin Ho [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Huh, Youn Suk [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710 (Korea, Republic of); Lim, Hyun Keong; Kim, Sang Su [Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, Seoul 121-742 (Korea, Republic of); Kim, Byung-Tae [Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Gangnam-Gu, Seoul 135-710 (Korea, Republic of); Chung, Yonghyun [Department of Radiological Science, Yonsei University College of Health Science, 234 Meaji, Heungup Wonju, Kangwon-Do 220-710 (Korea, Republic of)

    2012-02-01

    Currently, for most photomultiplier tube (PMT)-based PET systems, constant fraction discriminators (CFD) and time to digital converters (TDC) have been employed to detect gamma ray signal arrival time, whereas anger logic circuits and peak detection analog-to-digital converters (ADCs) have been implemented to acquire position and energy information of detected events. As compared to PMT the Geiger-mode avalanche photodiodes (GAPDs) have a variety of advantages, such as compactness, low bias voltage requirement and MRI compatibility. Furthermore, the individual read-out method using a GAPD array coupled 1:1 with an array scintillator can provide better image uniformity than can be achieved using PMT and anger logic circuits. Recently, a brain PET using 72 GAPD arrays (4 Multiplication-Sign 4 array, pixel size: 3 mm Multiplication-Sign 3 mm) coupled 1:1 with LYSO scintillators (4 Multiplication-Sign 4 array, pixel size: 3 mm Multiplication-Sign 3 mm Multiplication-Sign 20 mm) has been developed for simultaneous PET/MRI imaging in our laboratory. Eighteen 64:1 position decoder circuits (PDCs) were used to reduce GAPD channel number and three off-the-shelf free-running ADC and field programmable gate array (FPGA) combined data acquisition (DAQ) cards were used for data acquisition and processing. In this study, a free-running ADC- and FPGA-based signal processing method was developed for the detection of gamma ray signal arrival time, energy and position information all together for each GAPD channel. For the method developed herein, three DAQ cards continuously acquired 18 channels of pre-amplified analog gamma ray signals and 108-bit digital addresses from 18 PDCs. In the FPGA, the digitized gamma ray pulses and digital addresses were processed to generate data packages containing pulse arrival time, baseline value, energy value and GAPD channel ID. Finally, these data packages were saved to a 128 Mbyte on-board synchronous dynamic random access memory (SDRAM) and

  7. 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

  8. Signal-to-noise characterization of time-gated intensifiers used for wide-field time-domain FLIM

    Energy Technology Data Exchange (ETDEWEB)

    McGinty, J; Requejo-Isidro, J; Munro, I; Talbot, C B; Dunsby, C; Neil, M A A; French, P M W [Photonics Group, Blackett Laboratory, Imperial College London, Prince Consort Road, London, SW7 2BW (United Kingdom); Kellett, P A; Hares, J D, E-mail: james.mcginty@imperial.ac.u [Kentech Instruments Ltd, Isis Building, Howbery Park, Wallingford, OX10 8BA (United Kingdom)

    2009-07-07

    Time-gated imaging using gated optical intensifiers provides a means to realize high speed fluorescence lifetime imaging (FLIM) for the study of fast events and for high throughput imaging. We present a signal-to-noise characterization of CCD-coupled micro-channel plate gated intensifiers used with this technique and determine the optimal acquisition parameters (intensifier gain voltage, CCD integration time and frame averaging) for measuring mono-exponential fluorescence lifetimes in the shortest image acquisition time for a given signal flux. We explore the use of unequal CCD integration times for different gate delays and show that this can improve the lifetime accuracy for a given total acquisition time.

  9. 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)

  10. Ultrafast signal processing in quantum dot amplifiers through effective spectral holeburning

    DEFF Research Database (Denmark)

    Berg, Tommy Winther; Mørk, Jesper; Uskov, A. V.

    2002-01-01

    suitable for ultrafast signal processing. The basis of this property is that the process of spectral hole burning (SHB) can become very effective. We consider a traveling wave optical amplifier consisting of the dot states, which interact with the optical signal (no inhomogeneous broadening included...

  11. 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

  12. Real-time embedded system for stereo video processing for multiview displays

    Science.gov (United States)

    Berretty, R.-P. M.; Riemens, A. K.; Machado, P. F.

    2007-02-01

    In video systems, the introduction of 3D video might be the next revolution after the introduction of color. Nowadays multiview auto-stereoscopic displays are entering the market. Such displays offer various views at the same time. Depending on its positions, the viewers' eyes see different images. Hence, the viewers' left eye receives a signal that is different from what his right eye gets; this gives, provided the signals have been properly processed, the impression of depth. New auto-stereoscopic products use an image-plus-depth interface. On the other hand, a growing number of 3D productions from the entertainment industry use a stereo format. In this paper, we show how to compute depth from the stereo signal to comply with the display interface format. Furthermore, we present a realisation suitable for a real-time cost-effective implementation on an embedded media processor.

  13. New signal processing methods for the evaluation of eddy current NDT data

    International Nuclear Information System (INIS)

    Anon.

    1987-01-01

    Signal processing and pattern recognition methods play a crucial role in a number of areas associated with nondestructive evaluation. Defect characterization schemes often involve mapping the signal onto an appropriate feature domain and using pattern recognition techniques for classification. In addition, signal processing methods are also used to acquire, enhance, restore, and compress data. EPRI Project RP 2673-4 is concerned with developing new signal processing and pattern recognition techniques for evaluating eddy current signals. Efforts under this project have focused on three closely related areas. The thrust has been to: (1) develop a scheme to compress eddy current signals for the purposes of storing them in a compact form, (2) develop a robust clustering algorithm capable of discarding feature vectors that fall in the gray areas between clusters, and (3) investigate the feasibility of designing and developing a digital eddyscope

  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. 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.

  16. Low-pass parabolic FFT filter for airborne and satellite lidar signal processing.

    Science.gov (United States)

    Jiao, Zhongke; Liu, Bo; Liu, Enhai; Yue, Yongjian

    2015-10-14

    In order to reduce random errors of the lidar signal inversion, a low-pass parabolic fast Fourier transform filter (PFFTF) was introduced for noise elimination. A compact airborne Raman lidar system was studied, which applied PFFTF to process lidar signals. Mathematics and simulations of PFFTF along with low pass filters, sliding mean filter (SMF), median filter (MF), empirical mode decomposition (EMD) and wavelet transform (WT) were studied, and the practical engineering value of PFFTF for lidar signal processing has been verified. The method has been tested on real lidar signal from Wyoming Cloud Lidar (WCL). Results show that PFFTF has advantages over the other methods. It keeps the high frequency components well and reduces much of the random noise simultaneously for lidar signal processing.

  17. LISA time-delay interferometry zero-signal solution: Geometrical properties

    International Nuclear Information System (INIS)

    Tinto, Massimo; Larson, Shane L.

    2004-01-01

    Time-delay interferometry (TDI) is the data processing technique needed for generating interferometric combinations of data measured by the multiple Doppler readouts available onboard the three Laser Interferometer Space Antenna (LISA) spacecraft. Within the space of all possible interferometric combinations TDI can generate, we have derived a specific combination that has zero response to the gravitational wave signal, and called it the zero-signal solution (ZSS). This is a two-parameter family of linear combinations of the generators of the TDI space, and its response to a gravitational wave becomes null when these two parameters coincide with the values of the angles of the source location in the sky. Remarkably, the ZSS does not rely on any assumptions about the gravitational waveform, and in fact it works for waveforms of any kind. Our approach is analogous to the data analysis method introduced by Guersel and Tinto in the context of networks of Earth-based, wideband, interferometric gravitational wave detectors observing in coincidence a gravitational wave burst. The ZSS should be regarded as an application of the Guersel and Tinto method to the LISA data

  18. Design and measurement of signal processing system for cavity beam position monitor

    International Nuclear Information System (INIS)

    Wang Baopeng; Leng Yongbin; Yu Luyang; Zhou Weimin; Yuan Renxian; Chen Zhichu

    2013-01-01

    In this paper, in order to achieve the output signal processing of cavity beam position monitor (CBPM), we develop a digital intermediate frequency receiver architecture based signal processing system, which consists of radio frequency (RF) front end and high speed data acquisition board. The beam position resolution in the CBPM signal processing system is superior to 1 μm. Two signal processing algorithms, fast Fourier transform (FFT) and digital down converter (DDC), are evaluated offline using MATLAB platform, and both can be used to achieve, the CW input signal, position resolutions of 0.31 μm and 0.10 μm at -16 dBm. The DDC algorithm for its good compatibility is downloaded into the FPGA to realize online measurement, reaching the position resolution of 0.49 μm due to truncation error. The whole system works well and the performance meets design target. (authors)

  19. 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.

  20. 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...

  1. Filtering and spectral processing of 1-D signals using cellular neural networks

    NARCIS (Netherlands)

    Moreira-Tamayo, O.; Pineda de Gyvez, J.

    1996-01-01

    This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

  2. 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.

  3. Feasibility of Johnson Noise Thermometry based on Digital Signal Processing Techniques

    International Nuclear Information System (INIS)

    Hwang, In Koo; Kim, Yang Mo

    2014-01-01

    This paper presents an implementation strategy of noise thermometry based on a digital signal processing technique and demonstrates its feasibilities. A key factor in its development is how to extract the small thermal noise signal from other noises, for example, random noise from amplifiers and continuous electromagnetic interference from the environment. The proposed system consists of two identical amplifiers and uses a cross correlation function to cancel the random noise of the amplifiers. Then, the external interference noises are eliminated by discriminating the difference in the peaks between the thermal signal and external noise. The gain of the amplifiers is estimated by injecting an already known pilot signal. The experimental simulation results of signal processing methods have demonstrated that the proposed approach is an effective method in eliminating an external noise signal and performing gain correction for development of the thermometry

  4. 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

  5. Processing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-art and Challenges

    Directory of Open Access Journals (Sweden)

    Mufti eMahmud

    2016-06-01

    Full Text Available In recent years multichannel neuronal signal acquisition systems have allowed scientists to focus on research questions which were otherwise impossible. They act as a powerful means to study brain (dysfunctions in in-vivo and in in-vitro animal models. Typically, each session of electrophysiological experiments with multichannel data acquisition systems generate large amount of raw data. For example, a 128 channel signal acquisition system with 16 bits A/D conversion and 20 kHz sampling rate will generate approximately 17 GB data per hour (uncompressed. This poses an important and challenging problem of inferring conclusions from the large amounts of acquired data. Thus, automated signal processing and analysis tools are becoming a key component in neuroscience research, facilitating extraction of relevant information from neuronal recordings in a reasonable time. The purpose of this review is to introduce the reader to the current state-of-the-art of open-source packages for (semiautomated processing and analysis of multichannel extracellular neuronal signals (i.e., neuronal spikes, local field potentials, electroencephalogram, etc., and the existing Neuroinformatics infrastructure for tool and data sharing. The review is concluded by pinpointing some major challenges that are to be faced, which include the development of novel benchmarking techniques, cloud-based distributed processing and analysis tools, as well as defining novel means to share and standardize data.

  6. Nuclear spectrometry signal acquisition and processing system based on LabVIEW and C

    International Nuclear Information System (INIS)

    Chen Xiaojun; Fang Fang; Chen Mingchi; Jiang Zancheng; Wang Min

    2008-01-01

    The process of designing nuclear spectrometry signal acquisition and processing system based on virtual instrument technology is showed in this article. For the deficiency of LabVIEW in big data analyzing and processing, a method is presented in which C programmer is inserted and applied in signal smoothing, peak searching and area of the peak calculating. A complete nuclear spectrometry signal acquisition, processing and document management system is implemented. (authors)

  7. Demonstration of fundamental statistics by studying timing of electronics signals in a physics-based laboratory

    Science.gov (United States)

    Beach, Shaun E.; Semkow, Thomas M.; Remling, David J.; Bradt, Clayton J.

    2017-07-01

    We have developed accessible methods to demonstrate fundamental statistics in several phenomena, in the context of teaching electronic signal processing in a physics-based college-level curriculum. A relationship between the exponential time-interval distribution and Poisson counting distribution for a Markov process with constant rate is derived in a novel way and demonstrated using nuclear counting. Negative binomial statistics is demonstrated as a model for overdispersion and justified by the effect of electronic noise in nuclear counting. The statistics of digital packets on a computer network are shown to be compatible with the fractal-point stochastic process leading to a power-law as well as generalized inverse Gaussian density distributions of time intervals between packets.

  8. A method of signal transmission path analysis for multivariate random processes

    International Nuclear Information System (INIS)

    Oguma, Ritsuo

    1984-04-01

    A method for noise analysis called ''STP (signal transmission path) analysis'' is presentd as a tool to identify noise sources and their propagation paths in multivariate random proceses. Basic idea of the analysis is to identify, via time series analysis, effective network for the signal power transmission among variables in the system and to make use of its information to the noise analysis. In the present paper, we accomplish this through two steps of signal processings; first, we estimate, using noise power contribution analysis, variables which have large contribution to the power spectrum of interest, and then evaluate the STPs for each pair of variables to identify STPs which play significant role for the generated noise to transmit to the variable under evaluation. The latter part of the analysis is executed through comparison of partial coherence function and newly introduced partial noise power contribution function. This paper presents the procedure of the STP analysis and demonstrates, using simulation data as well as Borssele PWR noise data, its effectiveness for investigation of noise generation and propagation mechanisms. (author)

  9. 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.

  10. Digital Signal Processing and Control for the Study of Gene Networks

    Science.gov (United States)

    Shin, Yong-Jun

    2016-04-01

    Thanks to the digital revolution, digital signal processing and control has been widely used in many areas of science and engineering today. It provides practical and powerful tools to model, simulate, analyze, design, measure, and control complex and dynamic systems such as robots and aircrafts. Gene networks are also complex dynamic systems which can be studied via digital signal processing and control. Unlike conventional computational methods, this approach is capable of not only modeling but also controlling gene networks since the experimental environment is mostly digital today. The overall aim of this article is to introduce digital signal processing and control as a useful tool for the study of gene networks.

  11. 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...

  12. 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

  13. 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...

  14. 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…

  15. Real-time digital signal recovery for a multi-pole low-pass transfer function system.

    Science.gov (United States)

    Lee, Jhinhwan

    2017-08-01

    In order to solve the problems of waveform distortion and signal delay by many physical and electrical systems with multi-pole linear low-pass transfer characteristics, a simple digital-signal-processing (DSP)-based method of real-time recovery of the original source waveform from the distorted output waveform is proposed. A mathematical analysis on the convolution kernel representation of the single-pole low-pass transfer function shows that the original source waveform can be accurately recovered in real time using a particular moving average algorithm applied on the input stream of the distorted waveform, which can also significantly reduce the overall delay time constant. This method is generalized for multi-pole low-pass systems and has noise characteristics of the inverse of the low-pass filter characteristics. This method can be applied to most sensors and amplifiers operating close to their frequency response limits to improve the overall performance of data acquisition systems and digital feedback control systems.

  16. Signal coupling and signal integrity in multi-strip resistive plate chambers used for timing applications

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez-Diaz, Diego, E-mail: D.Gonzalez-Diaz@gsi.de [GSI Helmholtzcenter for Heavy Ion Research, Darmstadt (Germany); Technical University, Darmstadt (Germany); Department of Engineering Physics, Tsinghua University, Beijing (China); Chen Huangshan; Wang Yi [Technical University, Darmstadt (Germany)

    2011-08-21

    We have systematically studied the transmission of electrical signals along several 2-strip Resistive Plate Chambers (RPCs) in the frequency range f=0.1-3.5GHz. Such a range was chosen to fully cover the bandwidth associated to the very short rise-times of signals originated in RPCs used for sub-100 ps timing applications. This work conveys experimental evidence of the dominant role of modal dispersion in counters built at the 1 m scale, a fact that results in large cross-talk levels and strong signal shaping. It is shown that modal dispersion appears in RPCs due to their inherent unbalance between capacitive and inductive coupling. A practical way to restore this symmetry has been introduced (hereafter 'electrostatic compensation'), allowing for a cross-talk suppression factor up to x12 and a rise-time reduction by 200 ps. Under conditions of compensation the signal transmission is only limited by dielectric losses, yielding a length-dependent cutoff frequency of around 1 GHz for propagation along 2 m in typical float glass-based RPCs. It is further shown that 'electrostatic compensation' can be achieved for an arbitrary number of strips as long as the nature of the coupling is 'short-range', that is an almost exact assumption for typical strip-line RPCs. This work extends the bandwidth of previous studies by a factor ofx20.

  17. Improving OCD time to solution using Signal Response Metrology

    Science.gov (United States)

    Fang, Fang; Zhang, Xiaoxiao; Vaid, Alok; Pandev, Stilian; Sanko, Dimitry; Ramanathan, Vidya; Venkataraman, Kartik; Haupt, Ronny

    2016-03-01

    In recent technology nodes, advanced process and novel integration scheme have challenged the precision limits of conventional metrology; with critical dimensions (CD) of device reduce to sub-nanometer region. Optical metrology has proved its capability to precisely detect intricate details on the complex structures, however, conventional RCWA-based (rigorous coupled wave analysis) scatterometry has the limitations of long time-to-results and lack of flexibility to adapt to wide process variations. Signal Response Metrology (SRM) is a new metrology technique targeted to alleviate the consumption of engineering and computation resources by eliminating geometric/dispersion modeling and spectral simulation from the workflow. This is achieved by directly correlating the spectra acquired from a set of wafers with known process variations encoded. In SPIE 2015, we presented the results of SRM application in lithography metrology and control [1], accomplished the mission of setting up a new measurement recipe of focus/dose monitoring in hours. This work will demonstrate our recent field exploration of SRM implementation in 20nm technology and beyond, including focus metrology for scanner control; post etch geometric profile measurement, and actual device profile metrology.

  18. Intensified neuronal investment in the processing of chemosensory anxiety signals in non-socially anxious and socially anxious individuals.

    Directory of Open Access Journals (Sweden)

    Bettina M Pause

    Full Text Available BACKGROUND: The ability to communicate anxiety through chemosensory signals has been documented in humans by behavioral, perceptual and brain imaging studies. Here, we investigate in a time-sensitive manner how chemosensory anxiety signals, donated by humans awaiting an academic examination, are processed by the human brain, by analyzing chemosensory event-related potentials (CSERPs, 64-channel recording with current source density analysis. METHODOLOGY/PRINCIPAL FINDINGS: In the first study cerebral stimulus processing was recorded from 28 non-socially anxious participants and in the second study from 16 socially anxious individuals. Each individual participated in two sessions, smelling sweat samples donated from either female or male donors (88 sessions; balanced session order. Most of the participants of both studies were unable to detect the stimuli olfactorily. In non-socially anxious females, CSERPs demonstrate an increased magnitude of the P3 component in response to chemosensory anxiety signals. The source of this P3 activity was allocated to medial frontal brain areas. In socially anxious females chemosensory anxiety signals require more neuronal resources during early pre-attentive stimulus processing (N1. The neocortical sources of this activity were located within medial and lateral frontal brain areas. In general, the event-related neuronal brain activity in males was much weaker than in females. However, socially anxious males processed chemosensory anxiety signals earlier (N1 latency than the control stimuli collected during an ergometer training. CONCLUSIONS/SIGNIFICANCE: It is concluded that the processing of chemosensory anxiety signals requires enhanced neuronal energy. Socially anxious individuals show an early processing bias towards social fear signals, resulting in a repression of late attentional stimulus processing.

  19. 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...

  20. Signals and systems

    CERN Document Server

    Rao, K Deergha

    2018-01-01

    This textbook covers the fundamental theories of signals and systems analysis, while incorporating recent developments from integrated circuits technology into its examples. Starting with basic definitions in signal theory, the text explains the properties of continuous-time and discrete-time systems and their representation by differential equations and state space. From those tools, explanations for the processes of Fourier analysis, the Laplace transform, and the z-Transform provide new ways of experimenting with different kinds of time systems. The text also covers the separate classes of analog filters and their uses in signal processing applications. Intended for undergraduate electrical engineering students, chapter sections include exercise for review and practice for the systems concepts of each chapter. Along with exercises, the text includes MATLAB-based examples to allow readers to experiment with signals and systems code on their own. An online repository of the MATLAB code from this textbook can...

  1. 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)

  2. Multichannel Signal Enhancement using Non-Causal, Time-Domain Filters

    DEFF Research Database (Denmark)

    Jensen, Jesper Rindom; Christensen, Mads Græsbøll; Benesty, Jacob

    2013-01-01

    In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non-causal. W......In the vast amount of time-domain filtering methods for speech enhancement, the filters are designed to be causal. Recently, however, it was shown that the noise reduction and signal distortion capabilities of such single-channel filters can be improved by allowing the filters to be non......-causal, multichannel filters for enhancement based on an orthogonal decomposition is proposed. The evaluation shows that there is a potential gain in noise reduction and signal distortion by introducing non-causality. Moreover, experiments on real-life speech show that we can improve the perceptual quality....

  3. 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.

  4. Real-time signal communication between diagnostic and control in ASDEX Upgrade

    International Nuclear Information System (INIS)

    Treutterer, Wolfgang; Neu, Gregor; Raupp, Gerhard; Zehetbauer, Thomas; Zasche, Dieter; Lueddecke, Klaus; Cole, Richard

    2010-01-01

    The ASDEX Upgrade tokamak experiment is equipped with a versatile discharge monitoring and control system. It allows to develop and use advanced control algorithms to investigate plasma physics under well-defined conditions with the objective of optimising plasma performance. The achievable quality depends on the accuracy with which the plasma state can be reconstructed from measurements under real-time conditions. Today's advanced algorithms need physics quantities - scalar entities as well as profiles. These are obtained processing huge numbers of raw measurements with complex diagnostic algorithms. Adequate network communication for the resulting signals is crucial to satisfy real-time requirements, especially when several diagnostic systems cooperate in a feedback control loop. Support for the technology of choice, however, is not easily available for all of the diverse, highly specialised diagnostic systems. We give an overview about the methods that have been explored at ASDEX Upgrade for real-time signal transfer. In particular, we investigated reflective shared memory and Ethernet technologies. Our solution strives to combine their strengths. For fast communication on dedicated computing nodes, reflective shared memory is used. For the majority of diagnostic systems producing large data blocks at moderate rates, Ethernet connections with UDP protocol are employed. Following ASDEX Upgrade's framework concept, a software layer hides the networks used from both diagnostic and control applications.

  5. Real-time synchronization of wireless sensor network by 1-PPS signal

    Science.gov (United States)

    Giammarini, Marco; Pieralisi, Marco; Isidori, Daniela; Concettoni, Enrico; Cristalli, Cristina; Fioravanti, Matteo

    2015-05-01

    The use of wireless sensor networks with different nodes is desirable in a smart environment, because the network setting up and installation on preexisting structures can be done without a fixed cabled infrastructure. The flexibility of the monitoring system is fundamental where the use of a considerable quantity of cables could compromise the normal exercise, could affect the quality of acquired signal and finally increase the cost of the materials and installation. The network is composed of several intelligent "nodes", which acquires data from different kind of sensors, and then store or transmit them to a central elaboration unit. The synchronization of data acquisition is the core of the real-time wireless sensor network (WSN). In this paper, we present a comparison between different methods proposed by literature for the real-time acquisition in a WSN and finally we present our solution based on 1-Pulse-Per-Second (1-PPS) signal generated by GPS systems. The sensor node developed is a small-embedded system based on ARM microcontroller that manages the acquisition, the timing and the post-processing of the data. The communications between the sensors and the master based on IEEE 802.15.4 protocol and managed by dedicated software. Finally, we present the preliminary results obtained on a 3 floor building simulator with the wireless sensors system developed.

  6. Real-time signal communication between diagnostic and control in ASDEX Upgrade

    Energy Technology Data Exchange (ETDEWEB)

    Treutterer, Wolfgang, E-mail: Wolfgang.Treutterer@ipp.mpg.d [Max-Planck Institut fuer Plasmaphysik, Garching, EURATOM Association (Germany); Neu, Gregor; Raupp, Gerhard; Zehetbauer, Thomas; Zasche, Dieter [Max-Planck Institut fuer Plasmaphysik, Garching, EURATOM Association (Germany); Lueddecke, Klaus; Cole, Richard [Unlimited Computer Systems, Iffeldorf (Germany)

    2010-07-15

    The ASDEX Upgrade tokamak experiment is equipped with a versatile discharge monitoring and control system. It allows to develop and use advanced control algorithms to investigate plasma physics under well-defined conditions with the objective of optimising plasma performance. The achievable quality depends on the accuracy with which the plasma state can be reconstructed from measurements under real-time conditions. Today's advanced algorithms need physics quantities - scalar entities as well as profiles. These are obtained processing huge numbers of raw measurements with complex diagnostic algorithms. Adequate network communication for the resulting signals is crucial to satisfy real-time requirements, especially when several diagnostic systems cooperate in a feedback control loop. Support for the technology of choice, however, is not easily available for all of the diverse, highly specialised diagnostic systems. We give an overview about the methods that have been explored at ASDEX Upgrade for real-time signal transfer. In particular, we investigated reflective shared memory and Ethernet technologies. Our solution strives to combine their strengths. For fast communication on dedicated computing nodes, reflective shared memory is used. For the majority of diagnostic systems producing large data blocks at moderate rates, Ethernet connections with UDP protocol are employed. Following ASDEX Upgrade's framework concept, a software layer hides the networks used from both diagnostic and control applications.

  7. Signalign: An Ontology of DNA as Signal for Comparative Gene Structure Prediction Using Information-Coding-and-Processing Techniques.

    Science.gov (United States)

    Yu, Ning; Guo, Xuan; Gu, Feng; Pan, Yi

    2016-03-01

    Conventional character-analysis-based techniques in genome analysis manifest three main shortcomings-inefficiency, inflexibility, and incompatibility. In our previous research, a general framework, called DNA As X was proposed for character-analysis-free techniques to overcome these shortcomings, where X is the intermediates, such as digit, code, signal, vector, tree, graph network, and so on. In this paper, we further implement an ontology of DNA As Signal, by designing a tool named Signalign for comparative gene structure analysis, in which DNA sequences are converted into signal series, processed by modified method of dynamic time warping and measured by signal-to-noise ratio (SNR). The ontology of DNA As Signal integrates the principles and concepts of other disciplines including information coding theory and signal processing into sequence analysis and processing. Comparing with conventional character-analysis-based methods, Signalign can not only have the equivalent or superior performance, but also enrich the tools and the knowledge library of computational biology by extending the domain from character/string to diverse areas. The evaluation results validate the success of the character-analysis-free technique for improved performances in comparative gene structure prediction.

  8. Detection of weak transitions in signal dynamics using recurrence time statistics

    International Nuclear Information System (INIS)

    Gao, J.B.; Cao Yinhe; Gu Lingyun; Harris, J.G.; Principe, J.C.

    2003-01-01

    Signal detection in noisy and nonstationary environments is very challenging. In this Letter, we study why the two types of recurrence times [Phys. Rev. Lett. 83 (1999) 3178] may be very useful for detecting weak transitions in signal dynamics. We particularly emphasize that the recurrence times of the second type may be more powerful in detecting transitions with very low energy. These features are illustrated by studying a number of speech signals with fricatives and plosives. We have also shown that the recurrence times of the first type, nevertheless, has the distinguished feature of being more robust to the noise level and less sensitive to the parameter change of the algorithm. Since throughout our study, we have not explored any features unique to the speech signals, the results shown here may indicate that these tools may be useful in many different applications

  9. 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)

  10. Neutron Detector Signal Processing to Calculate the Effective Neutron Multiplication Factor of Subcritical Assemblies

    International Nuclear Information System (INIS)

    Talamo, Alberto; Gohar, Yousry

    2016-01-01

    This report describes different methodologies to calculate the effective neutron multiplication factor of subcritical assemblies by processing the neutron detector signals using MATLAB scripts. The subcritical assembly can be driven either by a spontaneous fission neutron source (e.g. californium) or by a neutron source generated from the interactions of accelerated particles with target materials. In the latter case, when the particle accelerator operates in a pulsed mode, the signals are typically stored into two files. One file contains the time when neutron reactions occur and the other contains the times when the neutron pulses start. In both files, the time is given by an integer representing the number of time bins since the start of the counting. These signal files are used to construct the neutron count distribution from a single neutron pulse. The built-in functions of MATLAB are used to calculate the effective neutron multiplication factor through the application of the prompt decay fitting or the area method to the neutron count distribution. If the subcritical assembly is driven by a spontaneous fission neutron source, then the effective multiplication factor can be evaluated either using the prompt neutron decay constant obtained from Rossi or Feynman distributions or the Modified Source Multiplication (MSM) method.

  11. Neutron Detector Signal Processing to Calculate the Effective Neutron Multiplication Factor of Subcritical Assemblies

    Energy Technology Data Exchange (ETDEWEB)

    Talamo, Alberto [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division; Gohar, Yousry [Argonne National Lab. (ANL), Argonne, IL (United States). Nuclear Engineering Division

    2016-06-01

    This report describes different methodologies to calculate the effective neutron multiplication factor of subcritical assemblies by processing the neutron detector signals using MATLAB scripts. The subcritical assembly can be driven either by a spontaneous fission neutron source (e.g. californium) or by a neutron source generated from the interactions of accelerated particles with target materials. In the latter case, when the particle accelerator operates in a pulsed mode, the signals are typically stored into two files. One file contains the time when neutron reactions occur and the other contains the times when the neutron pulses start. In both files, the time is given by an integer representing the number of time bins since the start of the counting. These signal files are used to construct the neutron count distribution from a single neutron pulse. The built-in functions of MATLAB are used to calculate the effective neutron multiplication factor through the application of the prompt decay fitting or the area method to the neutron count distribution. If the subcritical assembly is driven by a spontaneous fission neutron source, then the effective multiplication factor can be evaluated either using the prompt neutron decay constant obtained from Rossi or Feynman distributions or the Modified Source Multiplication (MSM) method.

  12. A KST framework for correlation network construction from time series signals

    Science.gov (United States)

    Qi, Jin-Peng; Gu, Quan; Zhu, Ying; Zhang, Ping

    2018-04-01

    A KST (Kolmogorov-Smirnov test and T statistic) method is used for construction of a correlation network based on the fluctuation of each time series within the multivariate time signals. In this method, each time series is divided equally into multiple segments, and the maximal data fluctuation in each segment is calculated by a KST change detection procedure. Connections between each time series are derived from the data fluctuation matrix, and are used for construction of the fluctuation correlation network (FCN). The method was tested with synthetic simulations and the result was compared with those from using KS or T only for detection of data fluctuation. The novelty of this study is that the correlation analyses was based on the data fluctuation in each segment of each time series rather than on the original time signals, which would be more meaningful for many real world applications and for analysis of large-scale time signals where prior knowledge is uncertain.

  13. 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.

  14. Advanced Time-Frequency Representation in Voice Signal Analysis

    Directory of Open Access Journals (Sweden)

    Dariusz Mika

    2018-03-01

    Full Text Available The most commonly used time-frequency representation of the analysis in voice signal is spectrogram. This representation belongs in general to Cohen's class, the class of time-frequency energy distributions. From the standpoint of properties of the resolution spectrogram representation is not optimal. In Cohen class representations are known which have a better resolution properties. All of them are created by smoothing the Wigner-Ville'a (WVD distribution characterized by the best resolution, however, the biggest harmful interference. Used smoothing functions decide about a compromise between the properties of resolution and eliminating harmful interference term. Another class of time-frequency energy distributions is the affine class of distributions. From the point of view of readability of analysis the best properties are known so called Redistribution of energy caused by the use of a general methodology referred to as reassignment to any time-frequency representation. Reassigned distributions efficiently combine a reduction of the interference terms provided by a well adapted smoothing kernel and an increased concentration of the signal components.

  15. 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

  16. A battery-operated pilot balloon time-signal generator

    Science.gov (United States)

    Ralph H. Moltzau

    1966-01-01

    Describes the design and construction of a 1-pound, battery-operated, time-signal transmitter, which is usable with portable radio or field telephone circuits for synchronizing multi-theodolite observation of pilot balloons.

  17. Ready...go: Amplitude of the FMRI signal encodes expectation of cue arrival time.

    Directory of Open Access Journals (Sweden)

    Xu Cui

    2009-08-01

    Full Text Available What happens when the brain awaits a signal of uncertain arrival time, as when a sprinter waits for the starting pistol? And what happens just after the starting pistol fires? Using functional magnetic resonance imaging (fMRI, we have discovered a novel correlate of temporal expectations in several brain regions, most prominently in the supplementary motor area (SMA. Contrary to expectations, we found little fMRI activity during the waiting period; however, a large signal appears after the "go" signal, the amplitude of which reflects learned expectations about the distribution of possible waiting times. Specifically, the amplitude of the fMRI signal appears to encode a cumulative conditional probability, also known as the cumulative hazard function. The fMRI signal loses its dependence on waiting time in a "countdown" condition in which the arrival time of the go cue is known in advance, suggesting that the signal encodes temporal probabilities rather than simply elapsed time. The dependence of the signal on temporal expectation is present in "no-go" conditions, demonstrating that the effect is not a consequence of motor output. Finally, the encoding is not dependent on modality, operating in the same manner with auditory or visual signals. This finding extends our understanding of the relationship between temporal expectancy and measurable neural signals.

  18. A Signal Processing Module for the Analysis of Heart Sounds and Heart Murmurs

    International Nuclear Information System (INIS)

    Javed, Faizan; Venkatachalam, P A; H, Ahmad Fadzil M

    2006-01-01

    In this paper a Signal Processing Module (SPM) for the computer-aided analysis of heart sounds has been developed. The module reveals important information of cardiovascular disorders and can assist general physician to come up with more accurate and reliable diagnosis at early stages. It can overcome the deficiency of expert doctors in rural as well as urban clinics and hospitals. The module has five main blocks: Data Acquisition and Pre-processing, Segmentation, Feature Extraction, Murmur Detection and Murmur Classification. The heart sounds are first acquired using an electronic stethoscope which has the capability of transferring these signals to the near by workstation using wireless media. Then the signals are segmented into individual cycles as well as individual components using the spectral analysis of heart without using any reference signal like ECG. Then the features are extracted from the individual components using Spectrogram and are used as an input to a MLP (Multiple Layer Perceptron) Neural Network that is trained to detect the presence of heart murmurs. Once the murmur is detected they are classified into seven classes depending on their timing within the cardiac cycle using Smoothed Pseudo Wigner-Ville distribution. The module has been tested with real heart sounds from 40 patients and has proved to be quite efficient and robust while dealing with a large variety of pathological conditions

  19. A Signal Processing Module for the Analysis of Heart Sounds and Heart Murmurs

    Energy Technology Data Exchange (ETDEWEB)

    Javed, Faizan; Venkatachalam, P A; H, Ahmad Fadzil M [Signal and Imaging Processing and Tele-Medicine Technology Research Group, Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS, 31750 Tronoh, Perak (Malaysia)

    2006-04-01

    In this paper a Signal Processing Module (SPM) for the computer-aided analysis of heart sounds has been developed. The module reveals important information of cardiovascular disorders and can assist general physician to come up with more accurate and reliable diagnosis at early stages. It can overcome the deficiency of expert doctors in rural as well as urban clinics and hospitals. The module has five main blocks: Data Acquisition and Pre-processing, Segmentation, Feature Extraction, Murmur Detection and Murmur Classification. The heart sounds are first acquired using an electronic stethoscope which has the capability of transferring these signals to the near by workstation using wireless media. Then the signals are segmented into individual cycles as well as individual components using the spectral analysis of heart without using any reference signal like ECG. Then the features are extracted from the individual components using Spectrogram and are used as an input to a MLP (Multiple Layer Perceptron) Neural Network that is trained to detect the presence of heart murmurs. Once the murmur is detected they are classified into seven classes depending on their timing within the cardiac cycle using Smoothed Pseudo Wigner-Ville distribution. The module has been tested with real heart sounds from 40 patients and has proved to be quite efficient and robust while dealing with a large variety of pathological conditions.

  20. Waiting Endurance Time Estimation of Electric Two-Wheelers at Signalized Intersections

    Directory of Open Access Journals (Sweden)

    Mei Huan

    2014-01-01

    Full Text Available The paper proposed a model for estimating waiting endurance times of electric two-wheelers at signalized intersections using survival analysis method. Waiting duration times were collected by video cameras and they were assigned as censored and uncensored data to distinguish between normal crossing and red-light running behavior. A Cox proportional hazard model was introduced, and variables revealing personal characteristics and traffic conditions were defined as covariates to describe the effects of internal and external factors. Empirical results show that riders do not want to wait too long to cross intersections. As signal waiting time increases, electric two-wheelers get impatient and violate the traffic signal. There are 12.8% of electric two-wheelers with negligible wait time. 25.0% of electric two-wheelers are generally nonrisk takers who can obey the traffic rules after waiting for 100 seconds. Half of electric two-wheelers cannot endure 49.0 seconds or longer at red-light phase. Red phase time, motor vehicle volume, and conformity behavior have important effects on riders’ waiting times. Waiting endurance times would decrease with the longer red-phase time, the lower traffic volume, or the bigger number of other riders who run against the red light. The proposed model may be applicable in the design, management and control of signalized intersections in other developing cities.