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.

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.

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

Applied Fourier analysis from signal processing to medical imaging

CERN Document Server

Olson, Tim

2017-01-01

The first of its kind, this focused textbook serves as a self-contained resource for teaching from scratch the fundamental mathematics of Fourier analysis and illustrating some of its most current, interesting applications, including medical imaging and radar processing. Developed by the author from extensive classroom teaching experience, it provides a breadth of theory that allows students to appreciate the utility of the subject, but at as accessible a depth as possible. With myriad applications included, this book can be adapted to a one or two semester course in Fourier Analysis or serve as the basis for independent study. Applied Fourier Analysis assumes no prior knowledge of analysis from its readers, and begins by making the transition from linear algebra to functional analysis. It goes on to cover basic Fourier series and Fourier transforms before delving into applications in sampling and interpolation theory, digital communications, radar processing, medical i maging, and heat and wave equations. Fo...

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.

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.

Estimation of the Tool Condition by Applying the Wavelet Transform to Acoustic Emission Signals

International Nuclear Information System (INIS)

Gomez, M. P.; Piotrkowski, R.; Ruzzante, J. E.; D'Attellis, C. E.

2007-01-01

This work follows the search of parameters to evaluate the tool condition in machining processes. The selected sensing technique is acoustic emission and it is applied to a turning process of steel samples. The obtained signals are studied using the wavelet transformation. The tool wear level is quantified as a percentage of the final wear specified by the Standard ISO 3685. The amplitude and relevant scale obtained of acoustic emission signals could be related with the wear level

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)

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...

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.

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.

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.

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...

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...

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

Design and implementation of a hybrid circuit system for micro sensor signal processing

International Nuclear Information System (INIS)

Wang Zhuping; Chen Jing; Liu Ruqing

2011-01-01

This paper covers a micro sensor analog signal processing circuit system (MASPS) chip with low power and a digital signal processing circuit board implementation including hardware connection and software design. Attention has been paid to incorporate the MASPS chip into the digital circuit board. The ultimate aim is to form a hybrid circuit used for mixed-signal processing, which can be applied to a micro sensor flow monitoring system. (semiconductor integrated circuits)

Measuring methods, registration and signal processing for magnetic field research

International Nuclear Information System (INIS)

Nagiello, Z.

1981-01-01

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

Power systems signal processing for smart grids

CERN Document Server

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

2013-01-01

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

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.

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....

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

A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

Science.gov (United States)

Hernandez, Wilmar

2007-01-01

In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.

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.

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.

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...

Artificial intelligence applied to process signal analysis

Science.gov (United States)

Corsberg, Dan

1988-01-01

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

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...

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

International Nuclear Information System (INIS)

Noha Shaaban; Fukuzo Masuda; Hidetsugu Morota

2006-01-01

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

A Survey on Optimal Signal Processing Techniques Applied to Improve the Performance of Mechanical Sensors in Automotive Applications

Directory of Open Access Journals (Sweden)

Wilmar Hernandez

2007-01-01

Full Text Available In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart sensors that today’s cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher’s interest in the fusion of intelligent sensors and optimal signal processing techniques.

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

First-order Convex Optimization Methods for Signal and Image Processing

DEFF Research Database (Denmark)

Jensen, Tobias Lindstrøm

2012-01-01

In this thesis we investigate the use of first-order convex optimization methods applied to problems in signal and image processing. First we make a general introduction to convex optimization, first-order methods and their iteration complexity. Then we look at different techniques, which can...... be used with first-order methods such as smoothing, Lagrange multipliers and proximal gradient methods. We continue by presenting different applications of convex optimization and notable convex formulations with an emphasis on inverse problems and sparse signal processing. We also describe the multiple...

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.

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

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.

Sampling phased array a new technique for signal processing and ultrasonic imaging

OpenAIRE

Bulavinov, A.; Joneit, D.; Kröning, M.; Bernus, L.; Dalichow, M.H.; Reddy, K.M.

2006-01-01

Different signal processing and image reconstruction techniques are applied in ultrasonic non-destructive material evaluation. In recent years, rapid development in the fields of microelectronics and computer engineering lead to wide application of phased array systems. A new phased array technique, called "Sampling Phased Array" has been developed in Fraunhofer Institute for non-destructive testing. It realizes unique approach of measurement and processing of ultrasonic signals. The sampling...

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

Science.gov (United States)

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

1987-01-01

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

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.

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

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.

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.

High-Speed Data Acquisition and Digital Signal Processing System for PET Imaging Techniques Applied to Mammography

Science.gov (United States)

Martinez, J. D.; Benlloch, J. M.; Cerda, J.; Lerche, Ch. W.; Pavon, N.; Sebastia, A.

2004-06-01

This paper is framed into the Positron Emission Mammography (PEM) project, whose aim is to develop an innovative gamma ray sensor for early breast cancer diagnosis. Currently, breast cancer is detected using low-energy X-ray screening. However, functional imaging techniques such as PET/FDG could be employed to detect breast cancer and track disease changes with greater sensitivity. Furthermore, a small and less expensive PET camera can be utilized minimizing main problems of whole body PET. To accomplish these objectives, we are developing a new gamma ray sensor based on a newly released photodetector. However, a dedicated PEM detector requires an adequate data acquisition (DAQ) and processing system. The characterization of gamma events needs a free-running analog-to-digital converter (ADC) with sampling rates of more than 50 Ms/s and must achieve event count rates up to 10 MHz. Moreover, comprehensive data processing must be carried out to obtain event parameters necessary for performing the image reconstruction. A new generation digital signal processor (DSP) has been used to comply with these requirements. This device enables us to manage the DAQ system at up to 80 Ms/s and to execute intensive calculi over the detector signals. This paper describes our designed DAQ and processing architecture whose main features are: very high-speed data conversion, multichannel synchronized acquisition with zero dead time, a digital triggering scheme, and high throughput of data with an extensive optimization of the signal processing algorithms.

Sampling phased array - a new technique for ultrasonic signal processing and imaging

OpenAIRE

Verkooijen, J.; Boulavinov, A.

2008-01-01

Over the past 10 years, the improvement in the field of microelectronics and computer engineering has led to significant advances in ultrasonic signal processing and image construction techniques that are currently being applied to non-destructive material evaluation. A new phased array technique, called 'Sampling Phased Array', has been developed in the Fraunhofer Institute for Non-Destructive Testing([1]). It realises a unique approach of measurement and processing of ultrasonic signals. Th...

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...

Evolutionary design optimization of traffic signals applied to Quito city.

Science.gov (United States)

Armas, Rolando; Aguirre, Hernán; Daolio, Fabio; Tanaka, Kiyoshi

2017-01-01

This work applies evolutionary computation and machine learning methods to study the transportation system of Quito from a design optimization perspective. It couples an evolutionary algorithm with a microscopic transport simulator and uses the outcome of the optimization process to deepen our understanding of the problem and gain knowledge about the system. The work focuses on the optimization of a large number of traffic lights deployed on a wide area of the city and studies their impact on travel time, emissions and fuel consumption. An evolutionary algorithm with specialized mutation operators is proposed to search effectively in large decision spaces, evolving small populations for a short number of generations. The effects of the operators combined with a varying mutation schedule are studied, and an analysis of the parameters of the algorithm is also included. In addition, hierarchical clustering is performed on the best solutions found in several runs of the algorithm. An analysis of signal clusters and their geolocation, estimation of fuel consumption, spatial analysis of emissions, and an analysis of signal coordination provide an overall picture of the systemic effects of the optimization process.

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.

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

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.

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.

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

Science.gov (United States)

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

2017-10-01

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

Zero order and signal processing spectrophotometric techniques applied for resolving interference of metronidazole with ciprofloxacin in their pharmaceutical dosage form.

Science.gov (United States)

Attia, Khalid A M; Nassar, Mohammed W I; El-Zeiny, Mohamed B; Serag, Ahmed

2016-02-05

Four rapid, simple, accurate and precise spectrophotometric methods were used for the determination of ciprofloxacin in the presence of metronidazole as interference. The methods under study are area under the curve, simultaneous equation in addition to smart signal processing techniques of manipulating ratio spectra namely Savitsky-Golay filters and continuous wavelet transform. All the methods were validated according to the ICH guidelines where accuracy, precision and repeatability were found to be within the acceptable limits. The selectivity of the proposed methods was tested using laboratory prepared mixtures and assessed by applying the standard addition technique. So, they can therefore be used for the routine analysis of ciprofloxacin in quality-control laboratories. Copyright © 2015 Elsevier B.V. All rights reserved.

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

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...

Hierarchic stochastic modelling applied to intracellular Ca(2+ signals.

Directory of Open Access Journals (Sweden)

Gregor Moenke

Full Text Available Important biological processes like cell signalling and gene expression have noisy components and are very complex at the same time. Mathematical analysis of such systems has often been limited to the study of isolated subsystems, or approximations are used that are difficult to justify. Here we extend a recently published method (Thurley and Falcke, PNAS 2011 which is formulated in observable system configurations instead of molecular transitions. This reduces the number of system states by several orders of magnitude and avoids fitting of kinetic parameters. The method is applied to Ca(2+ signalling. Ca(2+ is a ubiquitous second messenger transmitting information by stochastic sequences of concentration spikes, which arise by coupling of subcellular Ca(2+ release events (puffs. We derive analytical expressions for a mechanistic Ca(2+ model, based on recent data from live cell imaging, and calculate Ca(2+ spike statistics in dependence on cellular parameters like stimulus strength or number of Ca(2+ channels. The new approach substantiates a generic Ca(2+ model, which is a very convenient way to simulate Ca(2+ spike sequences with correct spiking statistics.

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.

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.

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/...

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

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.

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.

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)

Applied probability and stochastic processes

CERN Document Server

Sumita, Ushio

1999-01-01

Applied Probability and Stochastic Processes is an edited work written in honor of Julien Keilson. This volume has attracted a host of scholars in applied probability, who have made major contributions to the field, and have written survey and state-of-the-art papers on a variety of applied probability topics, including, but not limited to: perturbation method, time reversible Markov chains, Poisson processes, Brownian techniques, Bayesian probability, optimal quality control, Markov decision processes, random matrices, queueing theory and a variety of applications of stochastic processes. The book has a mixture of theoretical, algorithmic, and application chapters providing examples of the cutting-edge work that Professor Keilson has done or influenced over the course of his highly-productive and energetic career in applied probability and stochastic processes. The book will be of interest to academic researchers, students, and industrial practitioners who seek to use the mathematics of applied probability i...

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)

Signal and Image Processing Research at the Lawrence Livermore National Laboratory

Energy Technology Data Exchange (ETDEWEB)

Roberts, R S; Poyneer, L A; Kegelmeyer, L M; Carrano, C J; Chambers, D H; Candy, J V

2009-06-29

Lawrence Livermore National Laboratory is a large, multidisciplinary institution that conducts fundamental and applied research in the physical sciences. Research programs at the Laboratory run the gamut from theoretical investigations, to modeling and simulation, to validation through experiment. Over the years, the Laboratory has developed a substantial research component in the areas of signal and image processing to support these activities. This paper surveys some of the current research in signal and image processing at the Laboratory. Of necessity, the paper does not delve deeply into any one research area, but an extensive citation list is provided for further study of the topics presented.

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.)

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

Neural redundancy applied to the parity space for signal validation

International Nuclear Information System (INIS)

Mol, Antonio Carlos de Abreu; Pereira, Claudio Marcio Nascimento Abreu; Martinez, Aquilino Senra

2005-01-01

The objective of signal validation is to provide more reliable information from the plant sensor data The method presented in this work introduces the concept of neural redundancy and applies it to the space parity method [1] to overcome an inherent deficiency of this method - the determination of the best estimative of the redundant measures when they are inconsistent. The concept of neural redundancy consists on the calculation of a redundancy through neural networks based on the time series of the own state variable. Therefore, neural networks, dynamically trained with the time series, will estimate the current value of the own measure, which will be used as referee of the redundant measures in the parity space. For this purpose the neural network should have the capacity to supply the neural redundancy in real time and with maximum error corresponding to the group deviation. The historical series should be enough to allow the estimate of the next value, during transients and at the same time, it should be optimized to facilitate the retraining of the neural network to each acquisition. In order to have the capacity to reproduce the tendency of the time series even under accident condition, the dynamic training of the neural network privileges the recent points of the time series. The tests accomplished with simulated data of a nuclear plant, demonstrated that this method applied on the parity space method improves the signal validation process. (author)

Neural redundancy applied to the parity space for signal validation

Energy Technology Data Exchange (ETDEWEB)

Mol, Antonio Carlos de Abreu; Pereira, Claudio Marcio Nascimento Abreu [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]. E-mail: cmnap@ien.gov.br; Martinez, Aquilino Senra [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia]. E-mail: aquilino@lmp.br

2005-07-01

The objective of signal validation is to provide more reliable information from the plant sensor data The method presented in this work introduces the concept of neural redundancy and applies it to the space parity method [1] to overcome an inherent deficiency of this method - the determination of the best estimative of the redundant measures when they are inconsistent. The concept of neural redundancy consists on the calculation of a redundancy through neural networks based on the time series of the own state variable. Therefore, neural networks, dynamically trained with the time series, will estimate the current value of the own measure, which will be used as referee of the redundant measures in the parity space. For this purpose the neural network should have the capacity to supply the neural redundancy in real time and with maximum error corresponding to the group deviation. The historical series should be enough to allow the estimate of the next value, during transients and at the same time, it should be optimized to facilitate the retraining of the neural network to each acquisition. In order to have the capacity to reproduce the tendency of the time series even under accident condition, the dynamic training of the neural network privileges the recent points of the time series. The tests accomplished with simulated data of a nuclear plant, demonstrated that this method applied on the parity space method improves the signal validation process. (author)

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...

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.

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

Differences between signal currents for both polarities of applied voltages on cavity ionization chambers

International Nuclear Information System (INIS)

Takata, N.

2000-01-01

It is necessary to obtain precise values of signal currents for the measurement of exposure rates for gamma rays with cavity ionization chambers. Signal currents are usually expected to have the same absolute values for both polarities of applied voltages. In the case of cylindrical cavity ionization chambers, volume recombination loss of ion pairs depends on the polarity of the applied voltage. This is because the values of mobility are different for positive and negative ions. It was found, however, that values of signal currents from a cylindrical ionization chamber change slightly more with a negative than with a positive applied voltage, even after being corrected for volume recombination loss. Moreover, absolute values of saturation currents, which are obtained by extrapolation of correction of initial recombination and diffusion loss, were larger for the negative than for the positive applied voltage. It is known from an experiment with parallel plate ionization chambers that when negative voltage is applied to the repeller electrode, the saturated signal current decreases with an increase in the applied voltage. This is because secondary electrons are accelerated and the stopping power of air for these electrons decreases. When positive voltage is applied, the reverse is true. The effects of acceleration and deceleration of secondary electrons by the electric field thus seem to cause a tendency opposite to the experimental results on the signal currents from cylindrical ionization chambers. The experimental results for the cylindrical ionization chamber can be explained as follows. When negative voltage is applied, secondary electrons are attracted to the central (collecting) electrode. Consequently, the path length of the trajectories of these secondary electrons in the ionization volume increases and signal current increases. The energy gain from the electric field by secondary electrons which stop in the ionization chamber also contributes to the

Gröbner bases in control theory and signal processing

CERN Document Server

Regensburger, Georg

2007-01-01

This volume contains survey and original articles presenting the state of the art on the application of Gröbner bases in control theory and signal processing. The contributions are based on talks delivered at the Special Semester on Gröbner Bases and Related Methods at the Johann Radon Institute of Computational and Applied Mathematics (RICAM), Linz, Austria, in May 2006.

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....

Introduction to applied statistical signal analysis guide to biomedical and electrical engineering applications

CERN Document Server

Shiavi, Richard

2007-01-01

Introduction to Applied Statistical Signal Analysis is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech.Introduction to Applied Statistical Signal Analysis intertwines theory and implementation with practical examples and exercises. Topics presented in detail include: mathematical

Digital signal processing applied to crystal identification in Positron Emission Tomography dedicated to small animals

International Nuclear Information System (INIS)

Fontaine, Rejean; Viscogliosi, Nicolas; Semmaoui, Hicham; Belanger, Francois; Lemieux, Francois; Tetrault, Marc-Andre; Michaud, Jean-Baptiste; Berard, Philippe; Cadorette, Jules; Pepin, Catherine M.; Lecomte, Roger

2007-01-01

The recent introduction of all-digital electronic architecture in Positron Emission Tomography (PET) scanners, enables new paradigms to be explored for extracting relevant information from the detector signals, such as energy, time and crystal identification. The LabPET TM small animal scanner, which implements free-running 45-MHz sampling directly at the output of the charge sensitive preamplifiers, provides an excellent platform to test such advanced digital algorithms. A real-time identification method, based on an Auto-Regressive Moving-Average (ARMA) scheme, was tested for discriminating between LYSO (t r ∼40 ns) and LGSO (t r ∼65 ns) scintillators in phoswich detectors, coupled to a single Avalanche Photodiode (APD). Even with a low energy threshold of 250 keV applied individually, error rates 10%, typically with conventional analog pulse shape discrimination techniques. Such digital crystal identification techniques can be readily implemented with phoswich detectors for improving spatial resolution in PET, either by increasing crystal pixellization or by mitigating parallax errors through depth-of-interaction determination. It also allows to reduce the event rate presented to the real-time coincidence engine by applying a low energy limit at the crystal granularity and rejecting more Compton photons

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.

Computational information geometry for image and signal processing

CERN Document Server

Critchley, Frank; Dodson, Christopher

2017-01-01

This book focuses on the application and development of information geometric methods in the analysis, classification and retrieval of images and signals. It provides introductory chapters to help those new to information geometry and applies the theory to several applications. This area has developed rapidly over recent years, propelled by the major theoretical developments in information geometry, efficient data and image acquisition and the desire to process and interpret large databases of digital information. The book addresses both the transfer of methodology to practitioners involved in database analysis and in its efficient computational implementation.

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

Science.gov (United States)

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

2013-07-01

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

Wavelet based methods for improved wind profiler signal processing

Directory of Open Access Journals (Sweden)

V. Lehmann

2001-08-01

Full Text Available In this paper, we apply wavelet thresholding for removing automatically ground and intermittent clutter (airplane echoes from wind profiler radar data. Using the concept of discrete multi-resolution analysis and non-parametric estimation theory, we develop wavelet domain thresholding rules, which allow us to identify the coefficients relevant for clutter and to suppress them in order to obtain filtered reconstructions.Key words. Meteorology and atmospheric dynamics (instruments and techniques – Radio science (remote sensing; signal processing

Clustering method to process signals from a CdZnTe detector

International Nuclear Information System (INIS)

Zhang, Lan; Takahashi, Hiroyuki; Fukuda, Daiji; Nakazawa, Masaharu

2001-01-01

The poor mobility of holes in a compound semiconductor detector results in the imperfect collection of the primary charge deposited in the detector. Furthermore the fluctuation of the charge loss efficiency due to the change in the hole collection path length seriously degrades the energy resolution of the detector. Since the charge collection efficiency varies with the signal waveform, we can expect the improvement of the energy resolution through a proper waveform signal processing method. We developed a new digital signal processing technique, a clustering method which derives typical patterns containing the information on the real situation inside a detector from measured signals. The obtained typical patterns for the detector are then used for the pattern matching method. Measured signals are classified through analyzing the practical waveform variation due to the charge trapping, the electric field and the crystal defect etc. Signals with similar shape are placed into the same cluster. For each cluster we calculate an average waveform as a reference pattern. Using these reference patterns obtained from all the clusters, we can classify other measured signal waveforms from the same detector. Then signals are independently processed according to the classified category and form corresponding spectra. Finally these spectra are merged into one spectrum by multiplying normalization coefficients. The effectiveness of this method was verified with a CdZnTe detector of 2 mm thick and a 137 Cs gamma-ray source. The obtained energy resolution as improved to about 8 keV (FWHM). Because the clustering method is only related to the measured waveforms, it can be applied to any type and size of detectors and compatible with any type of filtering methods. (author)

Identification, detection, and validation of vibrating structures: a signal processing approach

International Nuclear Information System (INIS)

Candy, J.V.; Lager, D.L.

1979-01-01

This report discusses the application of modern signal processing techniques to characterize parameters governing the vibrational response of a structure. Simulated response data is used to explore the feasibility of applying these techniques to various structural problems. On-line estimator/indentifiers are used to estimate structural parameters, validate designed structures, and detect structural failure when used with a detector

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

Digital signal processing applied to crystal identification in Positron Emission Tomography dedicated to small animals

Energy Technology Data Exchange (ETDEWEB)

Fontaine, Rejean [Department of Electrical and Computer Engineering, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada)]. E-mail: Rejean.Fontaine@Usherbrooke.ca; Viscogliosi, Nicolas [Department of Electrical and Computer Engineering, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Semmaoui, Hicham [Department of Electrical and Computer Engineering, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Belanger, Francois [Department of Electrical and Computer Engineering, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Lemieux, Francois [Department of Electrical and Computer Engineering, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Tetrault, Marc-Andre [Department of Electrical and Computer Engineering, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Michaud, Jean-Baptiste [Department of Electrical and Computer Engineering, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Berard, Philippe [Department of Nuclear Medicine and Radiobiology, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Cadorette, Jules [Department of Nuclear Medicine and Radiobiology, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Pepin, Catherine M. [Department of Nuclear Medicine and Radiobiology, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada); Lecomte, Roger [Department of Nuclear Medicine and Radiobiology, Universite de Sherbrooke, 2500 Boul. Universite, Sherbrooke, Que., J1 K 2R1 (Canada)

2007-02-01

The recent introduction of all-digital electronic architecture in Positron Emission Tomography (PET) scanners, enables new paradigms to be explored for extracting relevant information from the detector signals, such as energy, time and crystal identification. The LabPET{sup TM} small animal scanner, which implements free-running 45-MHz sampling directly at the output of the charge sensitive preamplifiers, provides an excellent platform to test such advanced digital algorithms. A real-time identification method, based on an Auto-Regressive Moving-Average (ARMA) scheme, was tested for discriminating between LYSO (t{sub r}{approx}40 ns) and LGSO (t{sub r}{approx}65 ns) scintillators in phoswich detectors, coupled to a single Avalanche Photodiode (APD). Even with a low energy threshold of 250 keV applied individually, error rates<4% can be achieved, as compared to >10%, typically with conventional analog pulse shape discrimination techniques. Such digital crystal identification techniques can be readily implemented with phoswich detectors for improving spatial resolution in PET, either by increasing crystal pixellization or by mitigating parallax errors through depth-of-interaction determination. It also allows to reduce the event rate presented to the real-time coincidence engine by applying a low energy limit at the crystal granularity and rejecting more Compton photons.

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.

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

Digital signal processing in ultrasonic based navigation system for mobile robots

Directory of Open Access Journals (Sweden)

Stączek Paweł

2017-01-01

Full Text Available A system for estimating the coordinates of automated guided vehicles (AGV was presented in this article. Ultrasonic waves for distance measurement were applied. Used hardware was characterised, as well as signal processing algorithms. The system was tested on wheeled mobile robot in model 2D environment. The results of working range and errors of position estimation were discussed.

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  

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

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

Sampling phased array, a new technique for ultrasonic signal processing and imaging now available to industry

OpenAIRE

Verkooijen, J.; Bulavinov, A.

2008-01-01

Over the past 10 years the improvement in the field of microelectronics and computer engineering has led to significant advances in ultrasonic signal processing and image construction techniques that are currently being applied to non-destructive material evaluation. A new phased array technique, called "Sampling Phased Array" has been developed in the Fraunhofer Institute for non-destructive testing [1]. It realizes a unique approach of measurement and processing of ultrasonic signals. The s...

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....

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.

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.

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

Target acquisition performance : Effects of target aspect angle, dynamic imaging and signal processing

NARCIS (Netherlands)

Beintema, J.A.; Bijl, P.; Hogervorst, M.A.; Dijk, J.

2008-01-01

In an extensive Target Acquisition (TA) performance study, we recorded static and dynamic imagery of a set of military and civilian two-handheld objects at a range of distances and aspect angles with an under-sampled uncooled thermal imager. Next, we applied signal processing techniques including

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

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.

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...

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.

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.

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

Science.gov (United States)

Wang, Avery Li-Chun

which require a small fraction of the computational power of conventional FIR implementations. This design strategy is based on truncated and stabilized IIR filters. These signal-processing methods have been applied to the problem of auditory source separation, resulting in voice separation from complex music that is significantly better than previous results at far lower computational cost.

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

Digital Signal Processing Based on a Clustering Algorithm for Ir/Au TES Microcalorimeter

Science.gov (United States)

Zen, N.; Kunieda, Y.; Takahashi, H.; Hiramoto, K.; Nakazawa, M.; Fukuda, D.; Ukibe, M.; Ohkubo, M.

2006-02-01

In recent years, cryogenic microcalorimeters using their superconducting transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction methods have been developed. Among them, a clustering method based on digital signal processing has recently been proposed. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost a 10% improvement in the energy resolution. Conversely, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will thus show how a clustering method which sorts signals by their shapes is also useful for position identification

Active voltammetric microsensors with neural signal processing.

Energy Technology Data Exchange (ETDEWEB)

Vogt, M. C.

1998-12-11

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

Active voltammetric microsensors with neural signal processing

Science.gov (United States)

Vogt, Michael C.; Skubal, Laura R.

1999-02-01

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

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

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

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

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....

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...

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.

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...

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.

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...

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)

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

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.

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...

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...

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.

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

Exploration on practice teaching reform of Photoelectric Image Processing course under applied transformation

Science.gov (United States)

Cao, Binfang; Li, Xiaoqin; Liu, Changqing; Li, Jianqi

2017-08-01

With the further applied transformation of local colleges, teachers are urgently needed to make corresponding changes in the teaching content and methods from different courses. The article discusses practice teaching reform of the Photoelectric Image Processing course in the Optoelectronic Information Science and Engineering major. The Digital Signal Processing (DSP） platform is introduced to the experimental teaching. It will mobilize and inspire students and also enhance their learning motivation and innovation through specific examples. The course via teaching practice process has become the most popular course among students, which will further drive students' enthusiasm and confidence to participate in all kinds of electronic competitions.

Process signal selection method to improve the impact mitigation of sensor broken for diagnosis using machine learning

International Nuclear Information System (INIS)

Minowa, Hirotsugu; Gofuku, Akio

2014-01-01

Accidents of industrial plants cause large loss on human, economic, social credibility. In recent, studies of diagnostic methods using techniques of machine learning are expected to detect early and correctly abnormality occurred in a plant. However, the general diagnostic machines are generated generally to require all process signals (hereafter, signals) for plant diagnosis. Thus if trouble occurs such as process sensor is broken, the diagnostic machine cannot diagnose or may decrease diagnostic performance. Therefore, we propose an important process signal selection method to improve impact mitigation without reducing the diagnostic performance by reducing the adverse effect of noises on multi-agent diagnostic system. The advantage of our method is the general-purpose property that allows to be applied to various supervised machine learning and to set the various parameters to decide termination of search. The experiment evaluation revealed that diagnostic machines generated by our method using SVM improved the impact mitigation and did not reduce performance about the diagnostic accuracy, the velocity of diagnosis, predictions of plant state near accident occurrence, in comparison with the basic diagnostic machine which diagnoses by using all signals. This paper reports our proposed method and the results evaluated which our method was applied to the simulated abnormal of the fast-breeder reactor Monju. (author)

Signal integrity applied electromagnetics and professional practice

CERN Document Server

Russ, Samuel H

2016-01-01

This textbook teaches how to design working systems at very high frequencies. It is designed to introduce computer engineers to the design of extremely high speed digital systems. Combining an intuitive, physics-based approach to electromagnetics with a focus on solving realistic problems, the author presents concepts that are essential for computer and electrical engineers today. The book emphasizes an intuitive approach to electromagnetics, and then uses this foundation to show the reader how both physical phenomena can cause signals to propagate incorrectly; and how to solve commonly encountered issues. Emphasis is placed on real problems that the author has encountered in his professional career, integrating problem-solving strategies and real signal-integrity case studies throughout the presentation. Students are challenged to think about managing complex design projects and implementing successful engineering and manufacturing processes. Each chapter includes exercises to test concepts introduced.

Correlation techniques for the improvement of signal-to-noise ratio in measurements with stochastic processes

CERN Document Server

Reddy, V R; Reddy, T G; Reddy, P Y; Reddy, K R

2003-01-01

An AC modulation technique is described to convert stochastic signal variations into an amplitude variation and its retrieval through Fourier analysis. It is shown that this AC detection of signals of stochastic processes when processed through auto- and cross-correlation techniques improve the signal-to-noise ratio; the correlation techniques serve a similar purpose of frequency and phase filtering as that of phase-sensitive detection. A few model calculations applied to nuclear spectroscopy measurements such as Angular Correlations, Mossbauer spectroscopy and Pulse Height Analysis reveal considerable improvement in the sensitivity of signal detection. Experimental implementation of the technique is presented in terms of amplitude variations of harmonics representing the derivatives of normal spectra. Improved detection sensitivity to spectral variations is shown to be significant. These correlation techniques are general and can be made applicable to all the fields of particle counting where measurements ar...

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

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).

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....

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.

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...

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.

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.

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...

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

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....

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.

Magnetic memory signals variation induced by applied magnetic field and static tensile stress in ferromagnetic steel

International Nuclear Information System (INIS)

Huang, Haihong; Yang, Cheng; Qian, Zhengchun; Han, Gang; Liu, Zhifeng

2016-01-01

Stress can induce a spontaneous magnetic field in ferromagnetic steel under the excitation of geomagnetic field. In order to investigate the impact of applied magnetic field and tensile stress on variation of the residual magnetic signals on the surface of ferromagnetic materials, static tensile tests of Q235 structural steel were carried out, with the normal component of the residual magnetic signals, H p (y), induced by applied magnetic fields with different intensities measured through the tensile tests. The H p (y), its slope coefficient K S and maximum gradient K max changing with the applied magnetic field H and tensile stress were observed. Results show that the magnitude of H p (y) and its slope coefficient K S increase linearly with the increase of stress in the elastic deformation stage. Under yield stress, H p (y) and K S reach its maximum, and then decrease slightly with further increase of stress. Applied magnetic field affects the magnitude of H p (y) instead of changing the signal curve′s profile; and the magnitude of H p (y), K S , K max and the change rate of K S increase with the increase of applied magnetic field. The phenomenon is also discussed from the viewpoint of magnetic charge in ferromagnetic materials. - Highlights: • We investigated how applied magnetic field and tensile stress impact H p (y) signals. • Magnitude of H p (y), K S and K max increase with the increase of applied magnetic field. • Both applied magnetic field and tensile stress impact material magnetic permeability. • Applied magnetic field can help to evaluate the stress distribution of components.

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

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

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....

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...

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.

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

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.

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

The Time Lens Concept Applied to Ultra-High-Speed OTDM Signal Processing

DEFF Research Database (Denmark)

Clausen, Anders; Palushani, Evarist; Mulvad, Hans Christian Hansen

2013-01-01

This survey paper presents some of the applications where the versatile time-lens concept successfully can be applied to ultra-high-speed serial systems by offering expected needed functionalities for future optical communication networks.......This survey paper presents some of the applications where the versatile time-lens concept successfully can be applied to ultra-high-speed serial systems by offering expected needed functionalities for future optical communication networks....

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...

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

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.

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.

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

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.

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

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

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

Magnetic memory signals variation induced by applied magnetic field and static tensile stress in ferromagnetic steel

Energy Technology Data Exchange (ETDEWEB)

Huang, Haihong, E-mail: huanghaihong@hfut.edu.cn; Yang, Cheng; Qian, Zhengchun; Han, Gang; Liu, Zhifeng

2016-10-15

Stress can induce a spontaneous magnetic field in ferromagnetic steel under the excitation of geomagnetic field. In order to investigate the impact of applied magnetic field and tensile stress on variation of the residual magnetic signals on the surface of ferromagnetic materials, static tensile tests of Q235 structural steel were carried out, with the normal component of the residual magnetic signals, H{sub p}(y), induced by applied magnetic fields with different intensities measured through the tensile tests. The H{sub p}(y), its slope coefficient K{sub S} and maximum gradient K{sub max} changing with the applied magnetic field H and tensile stress were observed. Results show that the magnitude of H{sub p}(y) and its slope coefficient K{sub S} increase linearly with the increase of stress in the elastic deformation stage. Under yield stress, H{sub p}(y) and K{sub S} reach its maximum, and then decrease slightly with further increase of stress. Applied magnetic field affects the magnitude of H{sub p}(y) instead of changing the signal curve′s profile; and the magnitude of H{sub p}(y), K{sub S}, K{sub max} and the change rate of K{sub S} increase with the increase of applied magnetic field. The phenomenon is also discussed from the viewpoint of magnetic charge in ferromagnetic materials. - Highlights: • We investigated how applied magnetic field and tensile stress impact H{sub p}(y) signals. • Magnitude of H{sub p}(y), K{sub S} and K{sub max} increase with the increase of applied magnetic field. • Both applied magnetic field and tensile stress impact material magnetic permeability. • Applied magnetic field can help to evaluate the stress distribution of components.

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

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).

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.

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

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.

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.

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.

An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

Science.gov (United States)

Su, Zhongqing; Ye, Lin

2004-08-01

The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

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

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

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.

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.

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

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.

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....

Automated Signal Processing Applied to Volatile-Based Inspection of Greenhouse Crops

Science.gov (United States)

Jansen, Roel; Hofstee, Jan Willem; Bouwmeester, Harro; van Henten, Eldert

2010-01-01

Gas chromatograph–mass spectrometers (GC-MS) have been used and shown utility for volatile-based inspection of greenhouse crops. However, a widely recognized difficulty associated with GC-MS application is the large and complex data generated by this instrument. As a consequence, experienced analysts are often required to process this data in order to determine the concentrations of the volatile organic compounds (VOCs) of interest. Manual processing is time-consuming, labour intensive and may be subject to errors due to fatigue. The objective of this study was to assess whether or not GC-MS data can also be automatically processed in order to determine the concentrations of crop health associated VOCs in a greenhouse. An experimental dataset that consisted of twelve data files was processed both manually and automatically to address this question. Manual processing was based on simple peak integration while the automatic processing relied on the algorithms implemented in the MetAlign™ software package. The results of automatic processing of the experimental dataset resulted in concentrations similar to that after manual processing. These results demonstrate that GC-MS data can be automatically processed in order to accurately determine the concentrations of crop health associated VOCs in a greenhouse. When processing GC-MS data automatically, noise reduction, alignment, baseline correction and normalisation are required. PMID:22163594

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

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

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

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

International Nuclear Information System (INIS)

Schaefer, R.

1975-01-01

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

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.

Investigation of model based beamforming and Bayesian inversion signal processing methods for seismic localization of underground sources

DEFF Research Database (Denmark)

Oh, Geok Lian; Brunskog, Jonas

2014-01-01

Techniques have been studied for the localization of an underground source with seismic interrogation signals. Much of the work has involved defining either a P-wave acoustic model or a dispersive surface wave model to the received signal and applying the time-delay processing technique and frequ...... that for field data, inversion for localization is most advantageous when the forward model completely describe all the elastic wave components as is the case of the FDTD 3D elastic model....

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)

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

Grey signal processing and data reconstruction in the non-diffracting beam triangulation measurement system

Science.gov (United States)

Meng, Hao; Wang, Zhongyu; Fu, Jihua

2008-12-01

The non-diffracting beam triangulation measurement system possesses the advantages of longer measurement range, higher theoretical measurement accuracy and higher resolution over the traditional laser triangulation measurement system. Unfortunately the measurement accuracy of the system is greatly degraded due to the speckle noise, the CCD photoelectric noise and the background light noise in practical applications. Hence, some effective signal processing methods must be applied to improve the measurement accuracy. In this paper a novel effective method for removing the noises in the non-diffracting beam triangulation measurement system is proposed. In the method the grey system theory is used to process and reconstruct the measurement signal. Through implementing the grey dynamic filtering based on the dynamic GM(1,1), the noises can be effectively removed from the primary measurement data and the measurement accuracy of the system can be improved as a result.

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

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....

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.

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

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.)

Fundamentals of applied probability and random processes

CERN Document Server

Ibe, Oliver

2014-01-01

The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability t

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....

Symbolic signal processing

International Nuclear Information System (INIS)

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

1993-01-01

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

Human-machine interface based on muscular and brain signals applied to a robotic wheelchair

International Nuclear Information System (INIS)

Ferreira, A; Silva, R L; Celeste, W C; Filho, T F Bastos; Filho, M Sarcinelli

2007-01-01

This paper presents a Human-Machine Interface (HMI) based on the signals generated by eye blinks or brain activity. The system structure and the signal acquisition and processing are shown. The signals used in this work are either the signal associated to the muscular movement corresponding to an eye blink or the brain signal corresponding to visual information processing. The variance is the feature extracted from such signals in order to detect the intention of the user. The classification is performed by a variance threshold which is experimentally determined for each user during the training stage. The command options, which are going to be sent to the commanded device, are presented to the user in the screen of a PDA (Personal Digital Assistant). In the experiments here reported, a robotic wheelchair is used as the device being commanded

Human-machine interface based on muscular and brain signals applied to a robotic wheelchair

Energy Technology Data Exchange (ETDEWEB)

Ferreira, A; Silva, R L; Celeste, W C; Filho, T F Bastos; Filho, M Sarcinelli [Electrical Engineering Department, Federal University of Espirito Santo (UFES), Av. Fernando Ferrari, 514, Vitoria, 29075-910 (Brazil)

2007-11-15

This paper presents a Human-Machine Interface (HMI) based on the signals generated by eye blinks or brain activity. The system structure and the signal acquisition and processing are shown. The signals used in this work are either the signal associated to the muscular movement corresponding to an eye blink or the brain signal corresponding to visual information processing. The variance is the feature extracted from such signals in order to detect the intention of the user. The classification is performed by a variance threshold which is experimentally determined for each user during the training stage. The command options, which are going to be sent to the commanded device, are presented to the user in the screen of a PDA (Personal Digital Assistant). In the experiments here reported, a robotic wheelchair is used as the device being commanded.

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...

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...

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

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....

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)

OPTIMAL REPRESENTATION OF MER SIGNALS APPLIED TO THE IDENTIFICATION OF BRAIN STRUCTURES DURING DEEP BRAIN STIMULATION

Directory of Open Access Journals (Sweden)

Hernán Darío Vargas Cardona

2015-07-01

Full Text Available Identification of brain signals from microelectrode recordings (MER is a key procedure during deep brain stimulation (DBS applied in Parkinson’s disease patients. The main purpose of this research work is to identify with high accuracy a brain structure called subthalamic nucleus (STN, since it is the target structure where the DBS achieves the best therapeutic results. To do this, we present an approach for optimal representation of MER signals through method of frames. We obtain coefficients that minimize the Euclidean norm of order two. From optimal coefficients, we extract some features from signals combining the wavelet packet and cosine dictionaries. For a comparison frame with the state of the art, we also process the signals using the discrete wavelet transform (DWT with several mother functions. We validate the proposed methodology in a real data base. We employ simple supervised machine learning algorithms, as the K-Nearest Neighbors classifier (K-NN, a linear Bayesian classifier (LDC and a quadratic Bayesian classifier (QDC. Classification results obtained with the proposed method improves significantly the performance of the DWT. We achieve a positive identification of the STN superior to 97,6%. Identification outcomes achieved by the MOF are highly accurate, as we can potentially get a false positive rate of less than 2% during the DBS.

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

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.

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

Signal processing for ultrasonic testing of stainless steel with coarse structure

International Nuclear Information System (INIS)

Dahlgren, Sven; Ericsson, Lars

2000-03-01

manually. The B-scans acquired by higher frequency probes processed with NCD filtering showed a similar detection capability as the one achieved with a reference probe with lower frequency. Phase 2: Manual scanning was performed on welded CSS-material with simulated mechanical fatigue cracks in the weld (field measurements). Automatic tuning was done using the entropy algorithm. After NCD filtering signals, reasonable to interpret as tip signals from the simulated cracks, were enhanced. Phase 3. Automatic scanning was performed on welded CSS-blocks with simulated thermal fatigue cracks in the weld (laboratory measurements). Automatic tuning was done using the SNRE algorithm. Three blocks examined were sections cut from butt-welded 60 mm thick cast stainless steel pipe. The crack in each block had an intended height of 30-40% of the block thickness. Corner signals from the crack in one of the blocks were selected as reference echoes for the NCD filter construction. The following observations were made: The two defects in the other blocks were detected, but generally no sizing was possible. The enhancement was in some cases significant after filtering. The conditions for filter construction were not ideal for the technique. The spectrum of the material noise exhibited a very distinct dip, probably due to surface roughness, which decreased the likelihood of successful filter design. A crack, rather than an ideal reflector, had to be used as a reference reflector during the filter construction. There is a risk that the constructed filter then will be too specialized emphasizing a very narrow spectral region. The performance of such a filter, when applied to other cracks might be very poor. The conditions mentioned might explain the poor signal-to-noise ratio encountered in some cases. Through the project comparisons have been made with the SSP/CPC algorithm. The time resolution, after processing, has been exemplified to be significantly lower for SSP/CPC processing than for

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

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

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.

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

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

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.

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.

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.

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.

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...

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

Development and verification of signal processing system of avalanche photo diode for the active shields onboard ASTRO-H

Energy Technology Data Exchange (ETDEWEB)

Ohno, M., E-mail: ohno@hep01.hepl.hiroshima-u.ac.jp [Department of Physical Sciences, Hiroshima University, Hiroshima 739-8526 (Japan); Kawano, T.; Edahiro, I.; Shirakawa, H.; Ohashi, N.; Okada, C.; Habata, S.; Katsuta, J.; Tanaka, Y.; Takahashi, H.; Mizuno, T.; Fukazawa, Y. [Department of Physical Sciences, Hiroshima University, Hiroshima 739-8526 (Japan); Murakami, H.; Kobayashi, S.; Miyake, K.; Ono, K.; Kato, Y.; Furuta, Y.; Murota, Y.; Okuda, K. [Department of Physics, University of Tokyo, Tokyo 113-0033 (Japan); and others

2016-09-21

The hard X-ray Imager and Soft Gamma-ray Detector onboard ASTRO-H demonstrate high sensitivity to hard X-ray (5–80 keV) and soft gamma-rays (60–600 keV), respectively. To reduce the background, both instruments are actively shielded by large, thick Bismuth Germanate scintillators. We have developed the signal processing system of the avalanche photodiode in the BGO active shields and have demonstrated its effectiveness after assembly in the flight model of the HXI/SGD sensor and after integration into the satellite. The energy threshold achieved is about 150 keV and anti-coincidence efficiency for cosmic-ray events is almost 100%. Installed in the BGO active shield, the developed signal processing system successfully reduces the room background level of the main detector. - Highlights: • A detail of development of signal processing system for ASTRO-H is presented. • Digital filer with FPGA instead of discrete analog circuit is applied. • Expected performance is verified after integration of the satellite.

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.

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

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...

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

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....

REVIEW ARTICLE: Spectrophotometric applications of digital signal processing

Science.gov (United States)

Morawski, Roman Z.

2006-09-01

Spectrophotometry is more and more often the method of choice not only in analysis of (bio)chemical substances, but also in the identification of physical properties of various objects and their classification. The applications of spectrophotometry include such diversified tasks as monitoring of optical telecommunications links, assessment of eating quality of food, forensic classification of papers, biometric identification of individuals, detection of insect infestation of seeds and classification of textiles. In all those applications, large numbers of data, generated by spectrophotometers, are processed by various digital means in order to extract measurement information. The main objective of this paper is to review the state-of-the-art methodology for digital signal processing (DSP) when applied to data provided by spectrophotometric transducers and spectrophotometers. First, a general methodology of DSP applications in spectrophotometry, based on DSP-oriented models of spectrophotometric data, is outlined. Then, the most important classes of DSP methods for processing spectrophotometric data—the methods for DSP-aided calibration of spectrophotometric instrumentation, the methods for the estimation of spectra on the basis of spectrophotometric data, the methods for the estimation of spectrum-related measurands on the basis of spectrophotometric data—are presented. Finally, the methods for preprocessing and postprocessing of spectrophotometric data are overviewed. Throughout the review, the applications of DSP are illustrated with numerous examples related to broadly understood spectrophotometry.

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....

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.

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.

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.

Intelligent Technique for Signal Processing to Identify the Brain Disorder for Epilepsy Captures Using Fuzzy Systems

Directory of Open Access Journals (Sweden)

Gurumurthy Sasikumar

2016-01-01

Full Text Available The new direction of understand the signal that is created from the brain organization is one of the main chores in the brain signal processing. Amid all the neurological disorders the human brain epilepsy is measured as one of the extreme prevalent and then programmed artificial intelligence detection technique is an essential due to the crooked and unpredictable nature of happening of epileptic seizures. We proposed an Improved Fuzzy firefly algorithm, which would enhance the classification of the brain signal efficiently with minimum iteration. An important bunching technique created on fuzzy logic is the Fuzzy C means. Together in the feature domain with the spatial domain the features gained after multichannel EEG signals remained combined by means of fuzzy algorithms. And for better precision segmentation process the firefly algorithm is applied to optimize the Fuzzy C-means membership function. Simultaneously for the efficient clustering method the convergence criteria are set. On the whole the proposed technique yields more accurate results and that gives an edge over other techniques. This proposed algorithm result compared with other algorithms like fuzzy c means algorithm and PSO algorithm.

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.

Study on signal processing in Eddy current testing for defects in spline gear

International Nuclear Information System (INIS)

Lee, Jae Ho; Park, Tae Sug; Park, Ik Keun

2016-01-01

Eddy current testing (ECT) is commonly applied for the inspection of automated production lines of metallic products, because it has a high inspection speed and a reasonable price. When ECT is applied for the inspection of a metallic object having an uneven target surface, such as the spline gear of a spline shaft, it is difficult to distinguish between the original signal obtained from the sensor and the signal generated by a defect because of the relatively large surface signals having similar frequency distributions. To facilitate the detection of defect signals from the spline gear, implementation of high-order filters is essential, so that the fault signals can be distinguished from the surrounding noise signals, and simultaneously, the pass-band of the filter can be adjusted according to the status of each production line and the object to be inspected. We will examine the infinite impulse filters (IIR filters) available for implementing an advanced filter for ECT, and attempt to detect the flaw signals through optimization of system design parameters for detecting the signals at the system level

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.

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...

Applied Behavior Analysis and Statistical Process Control?

Science.gov (United States)

Hopkins, B. L.

1995-01-01

Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…

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...

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.

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

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.

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.

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)

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...

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

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.

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.

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...

Interference Reduction Selected Measurement Signals of Ships

Directory of Open Access Journals (Sweden)

Jan Monieta

2014-08-01

Full Text Available The paper presents problems encountered at the signal processing of mechanical values with electric methods. Depending on the measured quantity, the location of the sensors and the analysis frequency band, they are differently interferences. The article presents the results of applying the analysis of parameters of working and accompanying process marine medium speed reciprocating engines in the time, amplitude, frequency domain and wavelet analysis to select a reasonable method. The applied signal acquisition program allows you to perform some analysis of signals in different areas and the transformation of the data to other programs. The ways of interference reducing at various stages of their occurrence and analysis are presented. [b]Keywords[/b]: electrical signals, domain analysis, measurement interference

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...

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)

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. .

Multiple Harmonics Fitting Algorithms Applied to Periodic Signals Based on Hilbert-Huang Transform

Directory of Open Access Journals (Sweden)

Hui Wang

2013-01-01

Full Text Available A new generation of multipurpose measurement equipment is transforming the role of computers in instrumentation. The new features involve mixed devices, such as kinds of sensors, analog-to-digital and digital-to-analog converters, and digital signal processing techniques, that are able to substitute typical discrete instruments like multimeters and analyzers. Signal-processing applications frequently use least-squares (LS sine-fitting algorithms. Periodic signals may be interpreted as a sum of sine waves with multiple frequencies: the Fourier series. This paper describes a new sine fitting algorithm that is able to fit a multiharmonic acquired periodic signal. By means of a “sinusoidal wave” whose amplitude and phase are both transient, the “triangular wave” can be reconstructed on the basis of Hilbert-Huang transform (HHT. This method can be used to test effective number of bits (ENOBs of analog-to-digital converter (ADC, avoiding the trouble of selecting initial value of the parameters and working out the nonlinear equations. The simulation results show that the algorithm is precise and efficient. In the case of enough sampling points, even under the circumstances of low-resolution signal with the harmonic distortion existing, the root mean square (RMS error between the sampling data of original “triangular wave” and the corresponding points of fitting “sinusoidal wave” is marvelously small. That maybe means, under the circumstances of any periodic signal, that ENOBs of high-resolution ADC can be tested accurately.

FFT swept filtering: a bias-free method for processing fringe signals in absolute gravimeters

Science.gov (United States)

Křen, Petr; Pálinkáš, Vojtech; Mašika, Pavel; Val'ko, Miloš

2018-05-01

Absolute gravimeters, based on laser interferometry, are widely used for many applications in geoscience and metrology. Although currently the most accurate FG5 and FG5X gravimeters declare standard uncertainties at the level of 2-3 μGal, their inherent systematic errors affect the gravity reference determined by international key comparisons based predominately on the use of FG5-type instruments. The measurement results for FG5-215 and FG5X-251 clearly showed that the measured g-values depend on the size of the fringe signal and that this effect might be approximated by a linear regression with a slope of up to 0.030 μGal/mV . However, these empirical results do not enable one to identify the source of the effect or to determine a reasonable reference fringe level for correcting g-values in an absolute sense. Therefore, both gravimeters were equipped with new measuring systems (according to Křen et al. in Metrologia 53:27-40, 2016. https://doi.org/10.1088/0026-1394/53/1/27 applied for FG5), running in parallel with the original systems. The new systems use an analogue-to-digital converter HS5 to digitize the fringe signal and a new method of fringe signal analysis based on FFT swept bandpass filtering. We demonstrate that the source of the fringe size effect is connected to a distortion of the fringe signal due to the electronic components used in the FG5(X) gravimeters. To obtain a bias-free g-value, the FFT swept method should be applied for the determination of zero-crossings. A comparison of g-values obtained from the new and the original systems clearly shows that the original system might be biased by approximately 3-5 μGal due to improperly distorted fringe signal processing.

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)

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

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

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

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)

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...

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).

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.

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.

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

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)

Digital Signal Processing for Medical Imaging Using Matlab

CERN Document Server

Gopi, E S

2013-01-01

This book describes medical imaging systems, such as X-ray, Computed tomography, MRI, etc. from the point of view of digital signal processing. Readers will see techniques applied to medical imaging such as Radon transformation, image reconstruction, image rendering, image enhancement and restoration, and more. This book also outlines the physics behind medical imaging required to understand the techniques being described. The presentation is designed to be accessible to beginners who are doing research in DSP for medical imaging. Matlab programs and illustrations are used wherever possible to reinforce the concepts being discussed.  ·         Acts as a “starter kit” for beginners doing research in DSP for medical imaging; ·         Uses Matlab programs and illustrations throughout to make content accessible, particularly with techniques such as Radon transformation and image rendering; ·         Includes discussion of the basic principles behind the various medical imaging tec...

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...

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

Application of neural computing paradigms for signal validation

International Nuclear Information System (INIS)

Upadhyaya, B.R.; Eryurek, E.; Mathai, G.

1989-01-01

Signal validation and process monitoring problems often require the prediction of one or more process variables in a system. The feasibility of applying neural network paradigms to relate one variable with a set of other related variables is studied. The backpropagation network (BPN) is applied to develop models of signals from both a commercial power plant and the EBR-II. Modification of the BPN algorithm is studied with emphasis on the speed of network training and the accuracy of prediction. The prediction of process variables in a Westinghouse PWR is presented in this paper

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

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.

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)

Diagnostic of corrosion defects in steam generator tubes using advanced signal processing from Eddy current testing

International Nuclear Information System (INIS)

Formigoni, Andre L.; Lopez, Luiz A.N.M.; Ting, Daniel K.S.

2009-01-01

Recently, the Brazilian Angra I PWR nuclear power plant went into a programmed shutdown for substitution of its Steam Generator (SG) which life was shortened due to stress corrosion in its tubes. The total cost of investment were around R$724 million. The signals generated during an Eddy-current Testing (ECT) inspection in SG tubes of nuclear plant allows for the localization and dimensioning of defects in the tubes. The defects related with corrosion generate complex signals that are difficult to analyze and are the most common cause in SG replacement in nuclear power plants around the world. The objective of this paper is the development of a methodology that allows for the characterization of corrosion signals by ECT inspections applied in the heat exchangers tubes of SG of a nuclear power plant. In this present work, the aim is to investigate distributed type defects by inducing controlled corrosion in sample tubes of different materials The ECT signals obtained from these samples tubes with corrosion implanted, will be analyzed using Zetec ECT equipment, the MIZ-17ET and its probes. The data acquisition will use a NI PC A/D CARD 700 card and the LabVIEW program. Subsequently, we will apply mathematical tools for signal processing like time windowed Fast Fourier transforms and Wavelets transforms, in MATLAB platform, which will allow effectiveness to remove the noises and to extract representative characteristics for the defect being analyzed. Previously obtained results as well as the proposal for the future work will be presented. (author)

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

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.

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...

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

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

Missile signal processing common computer architecture for rapid technology upgrade

Science.gov (United States)

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

2004-10-01

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

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....

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.

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.

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.

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...

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...

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…

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

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...

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...

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)

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.

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)

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.

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.

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.

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.

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)

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.

New challenges in signal processing in astrophysics: the SKA case

International Nuclear Information System (INIS)

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

2015-01-01

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

Probability, random variables, and random processes theory and signal processing applications

CERN Document Server

Shynk, John J

2012-01-01

Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several app

Signal processing for non-destructive testing of railway tracks

Science.gov (United States)

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

2018-04-01

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

Myoelectric signal processing for control of powered limb prostheses.

Science.gov (United States)

Parker, P; Englehart, K; Hudgins, B

2006-12-01

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

An information-theoretical approach to image resolution applied to neutron imaging detectors based upon individual discriminator signals

International Nuclear Information System (INIS)

Clergeau, Jean-Francois; Ferraton, Matthieu; Guerard, Bruno; Khaplanov, Anton; Piscitelli, Francesco; Platz, Martin; Rigal, Jean-Marie; Van Esch, Patrick; Daulle, Thibault

2013-06-01

1D or 2D neutron imaging detectors with individual wire or strip readout using discriminators have the advantage of being able to treat several neutron impacts partially overlapping in time, hence reducing global dead time. A single neutron impact usually gives rise to several discriminator signals. In this paper, we introduce an information-theoretical definition of image resolution. Two point-like spots of neutron impacts with a given distance between them act as a source of information (each neutron hit belongs to one spot or the other), and the detector plus signal treatment is regarded as an imperfect communication channel that transmits this information. The maximal mutual information obtained from this channel as a function of the distance between the spots allows to define a calibration-independent measure of resolution. We then apply this measure to quantify the power of resolution of different algorithms treating these individual discriminator signals which can be implemented in firmware. The method is then applied to different detectors existing at the ILL. Center-of-gravity methods usually improve the resolution over best-wire algorithms which are the standard way of treating these signals. (authors)

An information-theoretical approach to image resolution applied to neutron imaging detectors based upon individual discriminator signals

Energy Technology Data Exchange (ETDEWEB)

Clergeau, Jean-Francois; Ferraton, Matthieu; Guerard, Bruno; Khaplanov, Anton; Piscitelli, Francesco; Platz, Martin; Rigal, Jean-Marie; Van Esch, Patrick [Institut Laue Langevin, Neutron Detector Service, Grenoble (France); Daulle, Thibault [PHELMA Grenoble - INP Grenoble (France)

2013-06-15

1D or 2D neutron imaging detectors with individual wire or strip readout using discriminators have the advantage of being able to treat several neutron impacts partially overlapping in time, hence reducing global dead time. A single neutron impact usually gives rise to several discriminator signals. In this paper, we introduce an information-theoretical definition of image resolution. Two point-like spots of neutron impacts with a given distance between them act as a source of information (each neutron hit belongs to one spot or the other), and the detector plus signal treatment is regarded as an imperfect communication channel that transmits this information. The maximal mutual information obtained from this channel as a function of the distance between the spots allows to define a calibration-independent measure of resolution. We then apply this measure to quantify the power of resolution of different algorithms treating these individual discriminator signals which can be implemented in firmware. The method is then applied to different detectors existing at the ILL. Center-of-gravity methods usually improve the resolution over best-wire algorithms which are the standard way of treating these signals. (authors)

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

Crosstalk between Wnt Signaling and RNA Processing in Colorectal Cancer

Directory of Open Access Journals (Sweden)

Michael Bordonaro

2013-01-01

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

Crosstalk between Wnt Signaling and RNA Processing in Colorectal Cancer.

Science.gov (United States)

Bordonaro, Michael

2013-01-01

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

Combination of digital signal processing methods towards an improved analysis algorithm for structural health monitoring.

Science.gov (United States)

Pentaris, Fragkiskos P.; Makris, John P.

2013-04-01

In Structural Health Monitoring (SHM) is of great importance to reveal valuable information from the recorded SHM data that could be used to predict or indicate structural fault or damage in a building. In this work a combination of digital signal processing methods, namely FFT along with Wavelet Transform is applied, together with a proposed algorithm to study frequency dispersion, in order to depict non-linear characteristics of SHM data collected in two university buildings under natural or anthropogenic excitation. The selected buildings are of great importance from civil protection point of view, as there are the premises of a public higher education institute, undergoing high use, stress, visit from academic staff and students. The SHM data are collected from two neighboring buildings that have different age (4 and 18 years old respectively). Proposed digital signal processing methods are applied to the data, presenting a comparison of the structural behavior of both buildings in response to seismic activity, weather conditions and man-made activity. Acknowledgments This work was supported in part by the Archimedes III Program of the Ministry of Education of Greece, through the Operational Program "Educational and Lifelong Learning", in the framework of the project entitled «Interdisciplinary Multi-Scale Research of Earthquake Physics and Seismotectonics at the front of the Hellenic Arc (IMPACT-ARC) » and is co-financed by the European Union (European Social Fund) and Greek National Fund.

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

CERN Document Server

Mu, Jiasong; Wang, Wei; Zhang, Baoju

2016-01-01

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

Algorithm-Architecture Matching for Signal and Image Processing

CERN Document Server

Gogniat, Guy; Morawiec, Adam; Erdogan, Ahmet

2011-01-01

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

Optical signal acquisition and processing in future accelerator diagnostics

International Nuclear Information System (INIS)

Jackson, G.P.; Elliott, A.

1992-01-01

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

Total focusing method with correlation processing of antenna array signals

Science.gov (United States)

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

2018-03-01

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

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

Signal processing in an acousto-optical spectral colorimeter

Science.gov (United States)

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

2002-02-01

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

Unique portable signal acquisition/processing station

International Nuclear Information System (INIS)

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

1983-01-01

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

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.

Blind signal processing algorithms under DC biased Gaussian noise

Science.gov (United States)

Kim, Namyong; Byun, Hyung-Gi; Lim, Jeong-Ok

2013-05-01

Distortions caused by the DC-biased laser input can be modeled as DC biased Gaussian noise and removing DC bias is important in the demodulation process of the electrical signal in most optical communications. In this paper, a new performance criterion and a related algorithm for unsupervised equalization are proposed for communication systems in the environment of channel distortions and DC biased Gaussian noise. The proposed criterion utilizes the Euclidean distance between the Dirac-delta function located at zero on the error axis and a probability density function of biased constant modulus errors, where constant modulus error is defined by the difference between the system out and a constant modulus calculated from the transmitted symbol points. From the results obtained from the simulation under channel models with fading and DC bias noise abruptly added to background Gaussian noise, the proposed algorithm converges rapidly even after the interruption of DC bias proving that the proposed criterion can be effectively applied to optical communication systems corrupted by channel distortions and DC bias noise.

Signal processing issues in reflection tomography

Science.gov (United States)

Cadalli, Nail

2001-12-01

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

Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis.

Science.gov (United States)

Saidi, Lotfi; Ali, Jaouher Ben; Fnaiech, Farhat

2014-09-01

Empirical mode decomposition (EMD) has been widely applied to analyze vibration signals behavior for bearing failures detection. Vibration signals are almost always non-stationary since bearings are inherently dynamic (e.g., speed and load condition change over time). By using EMD, the complicated non-stationary vibration signal is decomposed into a number of stationary intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal. Bi-spectrum, a third-order statistic, helps to identify phase coupling effects, the bi-spectrum is theoretically zero for Gaussian noise and it is flat for non-Gaussian white noise, consequently the bi-spectrum analysis is insensitive to random noise, which are useful for detecting faults in induction machines. Utilizing the advantages of EMD and bi-spectrum, this article proposes a joint method for detecting such faults, called bi-spectrum based EMD (BSEMD). First, original vibration signals collected from accelerometers are decomposed by EMD and a set of IMFs is produced. Then, the IMF signals are analyzed via bi-spectrum to detect outer race bearing defects. The procedure is illustrated with the experimental bearing vibration data. The experimental results show that BSEMD techniques can effectively diagnosis bearing failures. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Distortions caused by the signal processing in analog AM modulators

International Nuclear Information System (INIS)

Njau, E.C.

1988-08-01

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

A probablistic neural network classification system for signal and image processing

Energy Technology Data Exchange (ETDEWEB)

Bowman, B. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

The Acoustical Heart Valve Analysis Package is a system for signal and image processing and classification. It is being developed in both Matlab and C, to provide an interactive, interpreted environment, and has been optimized for large scale matrix operations. It has been used successfully to classify acoustic signals from implanted prosthetic heart valves in human patients, and will be integrated into a commercial Heart Valve Screening Center. The system uses several standard signal processing algorithms, as well as supervised learning techniques using the probabilistic neural network (PNN). Although currently used for the acoustic heart valve application, the algorithms and modular design allow it to be used for other applications, as well. We will describe the signal classification system, and show results from a set of test valves.

Analog integrated circuits design for processing physiological signals.

Science.gov (United States)

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

2010-01-01

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

Statistical process control: separating signal from noise in emergency department operations.

Science.gov (United States)

Pimentel, Laura; Barrueto, Fermin

2015-05-01

Statistical process control (SPC) is a visually appealing and statistically rigorous methodology very suitable to the analysis of emergency department (ED) operations. We demonstrate that the control chart is the primary tool of SPC; it is constructed by plotting data measuring the key quality indicators of operational processes in rationally ordered subgroups such as units of time. Control limits are calculated using formulas reflecting the variation in the data points from one another and from the mean. SPC allows managers to determine whether operational processes are controlled and predictable. We review why the moving range chart is most appropriate for use in the complex ED milieu, how to apply SPC to ED operations, and how to determine when performance improvement is needed. SPC is an excellent tool for operational analysis and quality improvement for these reasons: 1) control charts make large data sets intuitively coherent by integrating statistical and visual descriptions; 2) SPC provides analysis of process stability and capability rather than simple comparison with a benchmark; 3) SPC allows distinction between special cause variation (signal), indicating an unstable process requiring action, and common cause variation (noise), reflecting a stable process; and 4) SPC keeps the focus of quality improvement on process rather than individual performance. Because data have no meaning apart from their context, and every process generates information that can be used to improve it, we contend that SPC should be seriously considered for driving quality improvement in emergency medicine. Copyright © 2015 Elsevier Inc. All rights reserved.

Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

CERN Document Server

Hu, Fei

2012-01-01

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

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

Soft-core dataflow processor architecture optimised for radar signal processing: Article

CSIR Research Space (South Africa)

Broich, R

2014-10-01

Full Text Available Current radar signal processors lack either performance or flexibility. Custom soft-core processors exhibit potential in high-performance signal processing applications, yet remain relatively unexplored in research literature. In this paper, we use...

Clay content evaluation in soils through GPR signal processing

Science.gov (United States)

Tosti, Fabio; Patriarca, Claudio; Slob, Evert; Benedetto, Andrea; Lambot, Sébastien

2013-10-01

The mechanical behavior of soils is partly affected by their clay content, which arises some important issues in many fields of employment, such as civil and environmental engineering, geology, and agriculture. This work focuses on pavement engineering, although the method applies to other fields of interest. Clay content in bearing courses of road pavement frequently causes damages and defects (e.g., cracks, deformations, and ruts). Therefore, the road safety and operability decreases, directly affecting the increase of expected accidents. In this study, different ground-penetrating radar (GPR) methods and techniques were used to non-destructively investigate the clay content in sub-asphalt compacted soils. Experimental layout provided the use of typical road materials, employed for road bearing courses construction. Three types of soils classified by the American Association of State Highway and Transportation Officials (AASHTO) as A1, A2, and A3 were used and adequately compacted in electrically and hydraulically isolated test boxes. Percentages of bentonite clay were gradually added, ranging from 2% to 25% by weight. Analyses were carried out for each clay content using two different GPR instruments. A pulse radar with ground-coupled antennae at 500 MHz centre frequency and a vector network analyzer spanning the 1-3 GHz frequency range were used. Signals were processed in both time and frequency domains, and the consistency of results was validated by the Rayleigh scattering method, the full-waveform inversion, and the signal picking techniques. Promising results were obtained for the detection of clay content affecting the bearing capacity of sub-asphalt layers.

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.

From spectral holeburning memory to spatial-spectral microwave signal processing

International Nuclear Information System (INIS)

Babbitt, Wm Randall; Barber, Zeb W; Harrington, Calvin; Mohan, R Krishna; Sharpe, Tia; Bekker, Scott H; Chase, Michael D; Merkel, Kristian D; Stiffler, Colton R; Traxinger, Aaron S; Woidtke, Alex J

2014-01-01

Many storage and processing systems based on spectral holeburning have been proposed that access the broad bandwidth and high dynamic range of spatial-spectral materials, but only recently have practical systems been developed that exceed the performance and functional capabilities of electronic devices. This paper reviews the history of the proposed applications of spectral holeburning and spatial-spectral materials, from frequency domain optical memory to microwave photonic signal processing systems. The recent results of a 20 GHz bandwidth high performance spectrum monitoring system with the additional capability of broadband direction finding demonstrates the potential for spatial-spectral systems to be the practical choice for solving demanding signal processing problems in the near future. (paper)

Postnatal Ablation of Synaptic Retinoic Acid Signaling Impairs Cortical Information Processing and Sensory Discrimination in Mice.

Science.gov (United States)

Park, Esther; Tjia, Michelle; Zuo, Yi; Chen, Lu

2018-06-06

Retinoic acid (RA) and its receptors (RARs) are well established essential transcriptional regulators during embryonic development. Recent findings in cultured neurons identified an independent and critical post-transcriptional role of RA and RARα in the homeostatic regulation of excitatory and inhibitory synaptic transmission in mature neurons. However, the functional relevance of synaptic RA signaling in vivo has not been established. Here, using somatosensory cortex as a model system and the RARα conditional knock-out mouse as a tool, we applied multiple genetic manipulations to delete RARα postnatally in specific populations of cortical neurons, and asked whether synaptic RA signaling observed in cultured neurons is involved in cortical information processing in vivo Indeed, conditional ablation of RARα in mice via a CaMKIIα-Cre or a layer 5-Cre driver line or via somatosensory cortex-specific viral expression of Cre-recombinase impaired whisker-dependent texture discrimination, suggesting a critical requirement of RARα expression in L5 pyramidal neurons of somatosensory cortex for normal tactile sensory processing. Transcranial two-photon imaging revealed a significant increase in dendritic spine elimination on apical dendrites of somatosensory cortical layer 5 pyramidal neurons in these mice. Interestingly, the enhancement of spine elimination is whisker experience-dependent as whisker trimming rescued the spine elimination phenotype. Additionally, experiencing an enriched environment improved texture discrimination in RARα-deficient mice and reduced excessive spine pruning. Thus, RA signaling is essential for normal experience-dependent cortical circuit remodeling and sensory processing. SIGNIFICANCE STATEMENT The importance of synaptic RA signaling has been demonstrated in in vitro studies. However, whether RA signaling mediated by RARα contributes to neural circuit functions in vivo remains largely unknown. In this study, using a RARα conditional

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

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.

Stochastic Signal Processing for Sound Environment System with Decibel Evaluation and Energy Observation

Directory of Open Access Journals (Sweden)

Akira Ikuta

2014-01-01

Full Text Available In real sound environment system, a specific signal shows various types of probability distribution, and the observation data are usually contaminated by external noise (e.g., background noise of non-Gaussian distribution type. Furthermore, there potentially exist various nonlinear correlations in addition to the linear correlation between input and output time series. Consequently, often the system input and output relationship in the real phenomenon cannot be represented by a simple model using only the linear correlation and lower order statistics. In this study, complex sound environment systems difficult to analyze by using usual structural method are considered. By introducing an estimation method of the system parameters reflecting correlation information for conditional probability distribution under existence of the external noise, a prediction method of output response probability for sound environment systems is theoretically proposed in a suitable form for the additive property of energy variable and the evaluation in decibel scale. The effectiveness of the proposed stochastic signal processing method is experimentally confirmed by applying it to the observed data in sound environment systems.

Interactions between visceral afferent signaling and stimulus processing

Directory of Open Access Journals (Sweden)

Hugo D Critchley

2015-08-01

Full Text Available Visceral afferent signals to the brain influence thoughts, feelings and behaviour. Here we highlight the findings of a set of empirical investigations in humans concerning body-mind interaction that focus on how feedback from states of autonomic arousal shapes cognition and emotion. There is a longstanding debate regarding the contribution of the body, to mental processes. Recent theoretical models broadly acknowledge the role of (autonomically-mediated physiological arousal to emotional, social and motivational behaviours, yet the underlying mechanisms are only partially characterized. Neuroimaging is overcoming this shortfall; first, by demonstrating correlations between autonomic change and discrete patterns of evoked, and task-independent, neural activity; second, by mapping the central consequences of clinical perturbations in autonomic response and; third, by probing how dynamic fluctuations in peripheral autonomic state are integrated with perceptual, cognitive and emotional processes. Building on the notion that an important source of the brain’s representation of physiological arousal is derived from afferent information from arterial baroreceptors, we have exploited the phasic nature of these signals to show their differential contribution to the processing of emotionally-salient stimuli. This recent work highlights the facilitation at neural and behavioral levels of fear and threat processing that contrasts with the more established observations of the inhibition of central pain processing during baroreceptors activation. The implications of this body-brain-mind axis are discussed.

Influences of excluded volume of molecules on signaling processes on the biomembrane.

Directory of Open Access Journals (Sweden)

Masashi Fujii

Full Text Available We investigate the influences of the excluded volume of molecules on biochemical reaction processes on 2-dimensional surfaces using a model of signal transduction processes on biomembranes. We perform simulations of the 2-dimensional cell-based model, which describes the reactions and diffusion of the receptors, signaling proteins, target proteins, and crowders on the cell membrane. The signaling proteins are activated by receptors, and these activated signaling proteins activate target proteins that bind autonomously from the cytoplasm to the membrane, and unbind from the membrane if activated. If the target proteins bind frequently, the volume fraction of molecules on the membrane becomes so large that the excluded volume of the molecules for the reaction and diffusion dynamics cannot be negligible. We find that such excluded volume effects of the molecules induce non-trivial variations of the signal flow, defined as the activation frequency of target proteins, as follows. With an increase in the binding rate of target proteins, the signal flow varies by i monotonically increasing; ii increasing then decreasing in a bell-shaped curve; or iii increasing, decreasing, then increasing in an S-shaped curve. We further demonstrate that the excluded volume of molecules influences the hierarchical molecular distributions throughout the reaction processes. In particular, when the system exhibits a large signal flow, the signaling proteins tend to surround the receptors to form receptor-signaling protein clusters, and the target proteins tend to become distributed around such clusters. To explain these phenomena, we analyze the stochastic model of the local motions of molecules around the receptor.

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

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.

Bayesian networks applied to process diagnostics. Applications in energy industry

Energy Technology Data Exchange (ETDEWEB)

Widarsson, Bjoern (ed.); Karlsson, Christer; Dahlquist, Erik [Maelardalen Univ., Vaesteraas (Sweden); Nielsen, Thomas D.; Jensen, Finn V. [Aalborg Univ. (Denmark)

2004-10-01

Uncertainty in process operation occurs frequently in heat and power industry. This makes it hard to find the occurrence of an abnormal process state from a number of process signals (measurements) or find the correct cause to an abnormality. Among several other methods, Bayesian Networks (BN) is a method to build a model which can handle uncertainty in both process signals and the process itself. The purpose of this project is to investigate the possibilities to use BN for fault detection and diagnostics in combined heat and power industries through execution of two different applications. Participants from Aalborg University represent the knowledge of BN and participants from Maelardalen University have the experience from modelling heat and power applications. The co-operation also includes two energy companies; Elsam A/S (Nordjyllandsverket) and Maelarenergi AB (Vaesteraas CHP-plant), where the two applications are made with support from the plant personnel. The project ended out in two quite different applications. At Nordjyllandsverket, an application based (due to the lack of process knowledge) on pure operation data is build with capability to detect an abnormal process state in a coal mill. Detection is made through a conflict analysis when entering process signals into a model built by analysing the operation database. The application at Maelarenergi is built with a combination of process knowledge and operation data and can detect various faults caused by the fuel. The process knowledge is used to build a causal network structure and the structure is then trained by data from the operation database. Both applications are made as off-online applications, but they are ready for being run on-line. The performance of fault detection and diagnostics are good, but a lack of abnormal process states with known cause reduces the evaluation possibilities. Advantages with combining expert knowledge of the process with operation data are the possibility to represent

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....

12th International Conference on Intelligent Information Hiding and Multimedia Signal Processing

CERN Document Server

Tsai, Pei-Wei; Huang, Hsiang-Cheh

2017-01-01

This volume of Smart Innovation, Systems and Technologies contains accepted papers presented in IIH-MSP-2016, the 12th International Conference on Intelligent Information Hiding and Multimedia Signal Processing. The conference this year was technically co-sponsored by Tainan Chapter of IEEE Signal Processing Society, Fujian University of Technology, Chaoyang University of Technology, Taiwan Association for Web Intelligence Consortium, Fujian Provincial Key Laboratory of Big Data Mining and Applications (Fujian University of Technology), and Harbin Institute of Technology Shenzhen Graduate School. IIH-MSP 2016 is held in 21-23, November, 2016 in Kaohsiung, Taiwan. The conference is an international forum for the researchers and professionals in all areas of information hiding and multimedia signal processing. .

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

CERN Document Server

Lerch, Alexander

2012-01-01

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

Signal analysis and processing for SmartPET

International Nuclear Information System (INIS)

Scraggs, David; Boston, Andrew; Boston, Helen; Cooper, Reynold; Hall, Chris; Mather, Andy; Nolan, Paul; Turk, Gerard

2007-01-01

Measurement of induced transient charges on spectator electrodes is a critical requirement of the SmartPET project. Such a task requires the precise measurement of small amplitude pulses. Induced charge magnitudes on the SmartPET detectors were therefore studied and the suitability of wavelet analysis applied to de-noising signals was investigated. It was found that the absolute net maximum induced charge magnitudes from the two adjacent electrodes to the collecting electrode is 17% of the real charge magnitude for the AC side and 20% for the DC side. It was also found that wavelet analysis could identify induced charges of comparable magnitude to system noise

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.

Laser Doppler Blood Flow Imaging Using a CMOS Imaging Sensor with On-Chip Signal Processing

Directory of Open Access Journals (Sweden)

Cally Gill

2013-09-01

Full Text Available The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.

Laser doppler blood flow imaging using a CMOS imaging sensor with on-chip signal processing.

Science.gov (United States)

He, Diwei; Nguyen, Hoang C; Hayes-Gill, Barrie R; Zhu, Yiqun; Crowe, John A; Gill, Cally; Clough, Geraldine F; Morgan, Stephen P

2013-09-18

The first fully integrated 2D CMOS imaging sensor with on-chip signal processing for applications in laser Doppler blood flow (LDBF) imaging has been designed and tested. To obtain a space efficient design over 64 × 64 pixels means that standard processing electronics used off-chip cannot be implemented. Therefore the analog signal processing at each pixel is a tailored design for LDBF signals with balanced optimization for signal-to-noise ratio and silicon area. This custom made sensor offers key advantages over conventional sensors, viz. the analog signal processing at the pixel level carries out signal normalization; the AC amplification in combination with an anti-aliasing filter allows analog-to-digital conversion with a low number of bits; low resource implementation of the digital processor enables on-chip processing and the data bottleneck that exists between the detector and processing electronics has been overcome. The sensor demonstrates good agreement with simulation at each design stage. The measured optical performance of the sensor is demonstrated using modulated light signals and in vivo blood flow experiments. Images showing blood flow changes with arterial occlusion and an inflammatory response to a histamine skin-prick demonstrate that the sensor array is capable of detecting blood flow signals from tissue.

Ultra low-power biomedical signal processing: An analog wavelet filter approach for pacemakers

OpenAIRE

Pavlík Haddad, S.A.

2006-01-01

The purpose of this thesis is to describe novel signal processing methodologies and analog integrated circuit techniques for low-power biomedical systems. Physiological signals, such as the electrocardiogram (ECG), the electroencephalogram (EEG) and the electromyogram (EMG) are mostly non-stationary. The main difficulty in dealing with biomedical signal processing is that the information of interest is often a combination of features that are well localized temporally (e.g., spikes) and other...

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.

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.

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.

Applied medical image processing a basic course

CERN Document Server

Birkfellner, Wolfgang

2014-01-01

A widely used, classroom-tested text, Applied Medical Image Processing: A Basic Course delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field. Avoiding excessive mathematical formalisms, the book presents key principles by implementing algorithms from scratch and using simple MATLAB®/Octave scripts with image data and illustrations on an accompanying CD-ROM or companion website. Organized as a complete textbook, it provides an overview of the physics of medical image processing and discusses image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform, three-dimensional spatial transforms, volume rendering, image registration, and tomographic reconstruction.

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.

OPTIMAL SIGNAL PROCESSING METHODS IN GPR

Directory of Open Access Journals (Sweden)

Saeid Karamzadeh

2014-01-01

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

Digital Signal Processing for In-Vehicle Systems and Safety

CERN Document Server

Boyraz, Pinar; Takeda, Kazuya; Abut, Hüseyin

2012-01-01

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

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.

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. The DISP-2003 lecture series is composed of two Terms, 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 questions and answers also in French. Spring 1 Term: DISP-2003: Introduction to Digital Signal Processing 20 February 2003 - 3 April 2003, 7 lectures, Thursdays (attendance cost: 70.- CHF, registration required) Lecturers: Maria Elena Angoletta, AB-BDI; Guy Baribaud, AB-BDI; Philippe Baudrenghien, AB-RF; Laurent Deniau, AT-MTM Programme: 'Classical' digital signal processing. Fourier analysis. The Laplace transform. The z-transform. Digital filters. Statistics for Signal Processing. Signal Estimation and Spectral Analysis. Spring 2 T...

The study of image processing of parallel digital signal processor

International Nuclear Information System (INIS)

Liu Jie

2000-01-01

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

The Mehler-Fock Transform in Signal Processing

Directory of Open Access Journals (Sweden)

Reiner Lenz

2017-06-01

Full Text Available Many signals can be described as functions on the unit disk (ball. In the framework of group representations it is well-known how to construct Hilbert-spaces containing these functions that have the groups SU(1,N as their symmetry groups. One illustration of this construction is three-dimensional color spaces in which chroma properties are described by points on the unit disk. A combination of principal component analysis and the Perron-Frobenius theorem can be used to show that perspective projections map positive signals (i.e., functions with positive values to a product of the positive half-axis and the unit ball. The representation theory (harmonic analysis of the group SU(1,1 leads to an integral transform, the Mehler-Fock-transform (MFT, that decomposes functions, depending on the radial coordinate only, into combinations of associated Legendre functions. This transformation is applied to kernel density estimators of probability distributions on the unit disk. It is shown that the transform separates the influence of the data and the measured data. The application of the transform is illustrated by studying the statistical distribution of RGB vectors obtained from a common set of object points under different illuminants.

Monitoring fetal heart rate during pregnancy: contributions from advanced signal processing and wearable technology.

Science.gov (United States)

Signorini, Maria G; Fanelli, Andrea; Magenes, Giovanni

2014-01-01

Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their conditions, thus providing necessary interventions in time. Both these two objectives can be achieved by integrating technological development with methodological tools, thus allowing accurate classification and extraction of useful diagnostic information. The paper is focused on monitoring procedures applied to fetal heart rate variability (FHRV) signals, collected during pregnancy, in order to assess fetal well-being. The use of linear time and frequency techniques as well as the computation of non linear indices can contribute to enhancing the diagnostic power and reliability of fetal monitoring. The paper shows how advanced signal processing approaches can contribute to developing new diagnostic and classification indices. Their usefulness is evaluated by comparing two selected populations: normal fetuses and intra uterine growth restricted (IUGR) fetuses. Results show that the computation of different indices on FHRV signals, either linear and nonlinear, gives helpful indications to describe pathophysiological mechanisms involved in the cardiovascular and neural system controlling the fetal heart. As a further contribution, the paper briefly describes how the introduction of wearable systems for fetal ECG recording could provide new technological solutions improving the quality and usability of prenatal monitoring.

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

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)

Digital phonocardiographic experiments and signal processing in multidisciplinary fields of university education

Science.gov (United States)

Nagy, Tamás; Vadai, Gergely; Gingl, Zoltán

2017-09-01

Modern measurement of physical signals is based on the use of sensors, electronic signal conditioning, analog-to-digital conversion and digital signal processing carried out by dedicated software. The same signal chain is used in many devices such as home appliances, automotive electronics, medical instruments, and smartphones. Teaching the theoretical, experimental, and signal processing background must be an essential part of improving the standard of higher education, and it fits well to the increasingly multidisciplinary nature of physics and engineering too. In this paper, we show how digital phonocardiography can be used in university education as a universal, highly scalable, exciting, and inspiring laboratory practice and as a demonstration at various levels and complexity. We have developed open-source software templates in modern programming languages to support immediate use and to serve as a basis of further modifications using personal computers, tablets, and smartphones.

Digital phonocardiographic experiments and signal processing in multidisciplinary fields of university education

International Nuclear Information System (INIS)

Nagy, Tamás; Vadai, Gergely; Gingl, Zoltán

2017-01-01

Modern measurement of physical signals is based on the use of sensors, electronic signal conditioning, analog-to-digital conversion and digital signal processing carried out by dedicated software. The same signal chain is used in many devices such as home appliances, automotive electronics, medical instruments, and smartphones. Teaching the theoretical, experimental, and signal processing background must be an essential part of improving the standard of higher education, and it fits well to the increasingly multidisciplinary nature of physics and engineering too. In this paper, we show how digital phonocardiography can be used in university education as a universal, highly scalable, exciting, and inspiring laboratory practice and as a demonstration at various levels and complexity. We have developed open-source software templates in modern programming languages to support immediate use and to serve as a basis of further modifications using personal computers, tablets, and smartphones. (paper)

Verification of FPGA-Signal using the test board which is applied to Safety-related controller

Energy Technology Data Exchange (ETDEWEB)

Chung, Youn-Hu; Yoo, Kwanwoo; Lee, Myeongkyun; Yun, Donghwa [SOOSAN ENS, Seoul (Korea, Republic of)

2016-10-15

This article aims to provide the verification method for BGA-type FPGA of Programmable Logic Controller (PLC) developed as Safety Class. The logic of FPGA in the control device with Safety Class is the circuit to control overall logic of PLC. Saftety-related PLC must meet the international standard specifications. With this reason, we use V and V according to an international standard in order to secure high reliability and safety. By using this, we are supposed to proceed to a variety of verification courses for extra reliability and safety analysis. In order to have efficient verification of test results, we propose the test using the newly changed BGA socket which can resolve the problems of the conventional socket on this paper. The Verification of processes is divided into verification of Hardware and firmware. That processes are carried out in the unit testing and integration testing. The proposed test method is simple, the effect of cost reductions by batch process. In addition, it is advantageous to measure the signal from the Hi-speed-IC due to its short length of the pins and it was plated with the copper around it. Further, it also to prevent abrasion on the IC ball because it has no direct contact with the PCB. Therefore, it can be actually applied is to the BGA package test and we can easily verify logic as well as easily checking the operation of the designed data.

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

Noise Suppression in ECG Signals through Efficient One-Step Wavelet Processing Techniques

Directory of Open Access Journals (Sweden)

E. Castillo

2013-01-01

Full Text Available This paper illustrates the application of the discrete wavelet transform (DWT for wandering and noise suppression in electrocardiographic (ECG signals. A novel one-step implementation is presented, which allows improving the overall denoising process. In addition an exhaustive study is carried out, defining threshold limits and thresholding rules for optimal wavelet denoising using this presented technique. The system has been tested using synthetic ECG signals, which allow accurately measuring the effect of the proposed processing. Moreover, results from real abdominal ECG signals acquired from pregnant women are presented in order to validate the presented approach.

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.

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.

Improved Empirical Mode Decomposition Algorithm of Processing Complex Signal for IoT Application

OpenAIRE

Yang, Xianzhao; Cheng, Gengguo; Liu, Huikang

2015-01-01

Hilbert-Huang transform is widely used in signal analysis. However, due to its inadequacy in estimating both the maximum and the minimum values of the signals at both ends of the border, traditional HHT is easy to produce boundary error in empirical mode decomposition (EMD) process. To overcome this deficiency, this paper proposes an enhanced empirical mode decomposition algorithm for processing complex signal. Our work mainly focuses on two aspects. On one hand, we develop a technique to obt...

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.

Genomic signal processing methods for computation of alignment-free distances from DNA sequences.

Science.gov (United States)

Borrayo, Ernesto; Mendizabal-Ruiz, E Gerardo; Vélez-Pérez, Hugo; Romo-Vázquez, Rebeca; Mendizabal, Adriana P; Morales, J Alejandro

2014-01-01

Genomic signal processing (GSP) refers to the use of digital signal processing (DSP) tools for analyzing genomic data such as DNA sequences. A possible application of GSP that has not been fully explored is the computation of the distance between a pair of sequences. In this work we present GAFD, a novel GSP alignment-free distance computation method. We introduce a DNA sequence-to-signal mapping function based on the employment of doublet values, which increases the number of possible amplitude values for the generated signal. Additionally, we explore the use of three DSP distance metrics as descriptors for categorizing DNA signal fragments. Our results indicate the feasibility of employing GAFD for computing sequence distances and the use of descriptors for characterizing DNA fragments.

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.)

An input feature selection method applied to fuzzy neural networks for signal esitmation

International Nuclear Information System (INIS)

Na, Man Gyun; Sim, Young Rok

2001-01-01

It is well known that the performance of a fuzzy neural networks strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output. As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural networks and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PAC), genetic algorithms (GA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods

8th International Conference on Robotic, Vision, Signal Processing & Power Applications

CERN Document Server

Mustaffa, Mohd

2014-01-01

The proceeding is a collection of research papers presented, at the 8th International Conference on Robotics, Vision, Signal Processing and Power Applications (ROVISP 2013), by researchers, scientists, engineers, academicians as well as industrial professionals from all around the globe. The topics of interest are as follows but are not limited to: • Robotics, Control, Mechatronics and Automation • Vision, Image, and Signal Processing • Artificial Intelligence and Computer Applications • Electronic Design and Applications • Telecommunication Systems and Applications • Power System and Industrial Applications  

Modulation, resolution and signal processing in radar, sonar and related systems

CERN Document Server

Benjamin, R; Costrell, L

1966-01-01

Electronics and Instrumentation, Volume 35: Modulation, Resolution and Signal Processing in Radar, Sonar and Related Systems presents the practical limitations and potentialities of advanced modulation systems. This book discusses the concepts and techniques in the radar context, but they are equally essential to sonar and to a wide range of signaling and data-processing applications, including seismology, radio astronomy, and band-spread communications.Organized into 15 chapters, this volume begins with an overview of the principal developments sought in pulse radar. This text then provides a

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.

A signal processing analysis of Purkinje cells in vitro

Directory of Open Access Journals (Sweden)

Ze'ev R Abrams

2010-05-01

Full Text Available Cerebellar Purkinje cells in vitro fire recurrent sequences of Sodium and Calcium spikes. Here, we analyze the Purkinje cell using harmonic analysis, and our experiments reveal that its output signal is comprised of three distinct frequency bands, which are combined using Amplitude and Frequency Modulation (AM/FM. We find that the three characteristic frequencies - Sodium, Calcium and Switching – occur in various combinations in all waveforms observed using whole-cell current clamp recordings. We found that the Calcium frequency can display a frequency doubling of its frequency mode, and the Switching frequency can act as a possible generator of pauses that are typically seen in Purkinje output recordings. Using a reversibly photo-switchable kainate receptor agonist, we demonstrate the external modulation of the Calcium and Switching frequencies. These experiments and Fourier analysis suggest that the Purkinje cell can be understood as a harmonic signal oscillator, enabling a higher level of interpretation of Purkinje signaling based on modern signal processing techniques.

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.

Multi-channel logical circuit module used for high-speed, low amplitude signals processing and QDC gate signals generation

International Nuclear Information System (INIS)

Su Hong; Li Xiaogang; Zhu Haidong; Ma Xiaoli; Yin Weiwei; Li Zhuyu; Jin Genming; Wu Heyu

2001-01-01

A new kind of logical circuit will be introduced in brief. There are 16 independent channels in the module. The module receives low amplitude signals(≥40 mV), and processes them to amplify, shape, delay, sum and etc. After the processing each channel produces 2 pairs of ECL logical signal to feed the gate of QDC as the gate signal of QDC. The module consists of high-speed preamplifier unit, high-speed discriminate unit, delaying and shaping unit, summing unit and trigger display unit. The module is developed for 64 CH. 12 BIT Multi-event QDC. The impedance of QDC is 110 Ω. Each gate signal of QDC requires a pair of differential ECL level, Min. Gate width 30 ns and Max. Gate width 1 μs. It has showed that the outputs of logical circuit module satisfy the QDC requirements in experiment. The module can be used on data acquisition system to acquire thousands of data at high-speed ,high-density and multi-parameter, in heavy particle nuclear physics experiment. It also can be used to discriminate multi-coincidence events

BioSig: the free and open source software library for biomedical signal processing.

Science.gov (United States)

Vidaurre, Carmen; Sander, Tilmann H; Schlögl, Alois

2011-01-01

BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems, and sleep research. Moreover, the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), or respiration signals is a very relevant element of the BioSig project. Specifically, BioSig provides solutions for data acquisition, artifact processing, quality control, feature extraction, classification, modeling, and data visualization, to name a few. In this paper, we highlight several methods to help students and researchers to work more efficiently with biomedical signals.

Digital signal processing using MATLAB

CERN Document Server

Schilling, Robert L

2016-01-01

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

Fundamentals of adaptive signal processing

CERN Document Server

Uncini, Aurelio

2015-01-01

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

Electron quantum optics as quantum signal processing

OpenAIRE

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

2016-01-01

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

Array signal processing in the NASA Deep Space Network

Science.gov (United States)

Pham, Timothy T.; Jongeling, Andre P.

2004-01-01

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

FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar

Science.gov (United States)

Azim, Noor ul; Jun, Wang

2016-11-01

Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.

Down sampled signal processing for a B Factory bunch-by-bunch feedback system

International Nuclear Information System (INIS)

Hindi, H.; Hosseini, W.; Briggs, D.; Fox, J.; Hutton, A.

1992-03-01

A bunch-by-bunch feedback scheme is studied for damping coupled bunch synchrotron oscillations in the proposed PEP II B Factory. The quasi-linear feedback systems design incorporates a phase detector to provide a quantized measure of bunch phase, digital signal processing to compute an error correction signal and a kicker system to correct the energy of the bunches. A farm of digital processors, operating in parallel, is proposed to compute correction signals for the 1658 bunches of the B Factory. This paper studies the use of down sampled processing to reduce the computational complexity of the feedback system. We present simulation results showing the effect of down sampling on beam dynamics. Results show that down sampled processing can reduce the scale of the processing task by a factor of 10

On the uncertainty inequality as applied to discrete signals

Directory of Open Access Journals (Sweden)

Y. V. Venkatesh

2006-01-01

Full Text Available Given a continuous-time bandlimited signal, the Shannon sampling theorem provides an interpolation scheme for exactly reconstructing it from its discrete samples. We analyze the relationship between concentration (or compactness in the temporal/spectral domains of the (i continuous-time and (ii discrete-time signals. The former is governed by the Heisenberg uncertainty inequality which prescribes a lower bound on the product of effective temporal and spectral spreads of the signal. On the other hand, the discrete-time counterpart seems to exhibit some strange properties, and this provides motivation for the present paper. We consider the following problem: for a bandlimited signal, can the uncertainty inequality be expressed in terms of the samples, using thestandard definitions of the temporal and spectral spreads of the signal? In contrast with the results of the literature, we present a new approach to solve this problem. We also present a comparison of the results obtained using the proposed definitions with those available in the literature.

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....

Nonnegative Tensor Factorization Approach Applied to Fission Chamber’s Output Signals Blind Source Separation

Science.gov (United States)

Laassiri, M.; Hamzaoui, E.-M.; Cherkaoui El Moursli, R.

2018-02-01

Inside nuclear reactors, gamma-rays emitted from nuclei together with the neutrons introduce unwanted backgrounds in neutron spectra. For this reason, powerful extraction methods are needed to extract useful neutron signal from recorded mixture and thus to obtain clearer neutron flux spectrum. Actually, several techniques have been developed to discriminate between neutrons and gamma-rays in a mixed radiation field. Most of these techniques, tackle using analogue discrimination methods. Others propose to use some organic scintillators to achieve the discrimination task. Recently, systems based on digital signal processors are commercially available to replace the analog systems. As alternative to these systems, we aim in this work to verify the feasibility of using a Nonnegative Tensor Factorization (NTF) to blind extract neutron component from mixture signals recorded at the output of fission chamber (WL-7657). This last have been simulated through the Geant4 linked to Garfield++ using a 252Cf neutron source. To achieve our objective of obtaining the best possible neutron-gamma discrimination, we have applied the two different NTF algorithms, which have been found to be the best methods that allow us to analyse this kind of nuclear data.

Measuring Dynamic Signals with Direct Sensor-to-Microcontroller Interfaces Applied to a Magnetoresistive Sensor.

Science.gov (United States)

Sifuentes, Ernesto; Gonzalez-Landaeta, Rafael; Cota-Ruiz, Juan; Reverter, Ferran

2017-05-18

This paper evaluates the performance of direct interface circuits (DIC), where the sensor is directly connected to a microcontroller, when a resistive sensor subjected to dynamic changes is measured. The theoretical analysis provides guidelines for the selection of the components taking into account both the desired resolution and the bandwidth of the input signal. Such an analysis reveals that there is a trade-off between the sampling frequency and the resolution of the measurement, and this depends on the selected value of the capacitor that forms the RC circuit together with the sensor resistance. This performance is then experimentally proved with a DIC measuring a magnetoresistive sensor exposed to a magnetic field of different frequencies, amplitudes, and waveforms. A sinusoidal magnetic field up to 1 kHz can be monitored with a resolution of eight bits and a sampling frequency of around 10 kSa/s. If a higher resolution is desired, the sampling frequency has to be lower, thus limiting the bandwidth of the dynamic signal under measurement. The DIC is also applied to measure an electrocardiogram-type signal and its QRS complex is well identified, which enables the estimation, for instance, of the heart rate.

Dual resonance approach to optical signal processing beyond the carrier relaxation rate

DEFF Research Database (Denmark)

Heuck, Mikkel; Kristensen, Philip Trøst; Mørk, Jesper

2014-01-01

We propose using two optical cavities in a differential control scheme to increase the bandwidth of cavity-based semiconductor optical signal processing devices beyond the limit given by the slowest carrier relaxation rate of the medium.......We propose using two optical cavities in a differential control scheme to increase the bandwidth of cavity-based semiconductor optical signal processing devices beyond the limit given by the slowest carrier relaxation rate of the medium....