WorldWideScience

Sample records for learning signal processing

  1. 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...

  2. 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...

  3. 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...

  4. Deep Learning in Visual Computing and Signal Processing

    OpenAIRE

    Xie, Danfeng; Zhang, Lei; Bai, Li

    2017-01-01

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

  5. 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...

  6. 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...

  7. Trends in Machine Learning for Signal Processing

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  8. 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...

  9. 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

  10. A Signal for the Need to Restructure the Learning Process.

    Science.gov (United States)

    Breivik, Patricia Senn

    1991-01-01

    Although the U.S. will not disintegrate tomorrow if information literacy and resource-based learning remain underfunded, today's disadvantaged groups will fall further behind, as a new "information elite" emerges. The American Library Association's 1989 information literacy report is one step toward creating a national agenda for…

  11. Method to predict process signals to learn for SVM

    International Nuclear Information System (INIS)

    Minowa, Hirotsugu; Gofuku, Akio

    2013-01-01

    Study of diagnostic system using machine learning to reduce the incidents of the plant is in advance because an accident causes large damage about human, economic and social loss. There is a problem that 2 performances between a classification performance and generalization performance on the machine diagnostic machine is exclusive. However, multi agent diagnostic system makes it possible to use a diagnostic machine specialized either performance by multi diagnostic machines can be used. We propose method to select optimized variables to improve classification performance. The method can also be used for other supervised learning machine but Support Vector Machine. This paper reports that our method and result of evaluation experiment applied our method to output 40% of Monju. (author)

  12. 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

  13. Auto-Encoder based Deep Learning for Surface Electromyography Signal Processing

    Directory of Open Access Journals (Sweden)

    Marwa Farouk Ibrahim Ibrahim

    2018-01-01

    Full Text Available Feature extraction is taking a very vital and essential part of bio-signal processing. We need to choose one of two paths to identify and select features in any system. The most popular track is engineering handcrafted, which mainly depends on the user experience and the field of application. While the other path is feature learning, which depends on training the system on recognising and picking the best features that match the application. The main concept of feature learning is to create a model that is expected to be able to learn the best features without any human intervention instead of recourse the traditional methods for feature extraction or reduction and avoid dealing with feature extraction that depends on researcher experience. In this paper, Auto-Encoder will be utilised as a feature learning algorithm to practice the recommended model to excerpt the useful features from the surface electromyography signal. Deep learning method will be suggested by using Auto-Encoder to learn features. Wavelet Packet, Spectrogram, and Wavelet will be employed to represent the surface electromyography signal in our recommended model. Then, the newly represented bio-signal will be fed to stacked autoencoder (2 stages to learn features and finally, the behaviour of the proposed algorithm will be estimated by hiring different classifiers such as Extreme Learning Machine, Support Vector Machine, and SoftMax Layer. The Rectified Linear Unit (ReLU will be created as an activation function for extreme learning machine classifier besides existing functions such as sigmoid and radial basis function. ReLU will show a better classification ability than sigmoid and Radial basis function (RBF for wavelet, Wavelet scale 5 and wavelet packet signal representations implemented techniques. ReLU will illustrate better classification ability, as an activation function, than sigmoid and poorer than RBF for spectrogram signal representation. Both confidence interval and

  14. Machine intelligence and signal processing

    CERN Document Server

    Vatsa, Mayank; Majumdar, Angshul; Kumar, Ajay

    2016-01-01

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

  15. Differential dependence of Pavlovian incentive motivation and instrumental incentive learning processes on dopamine signaling

    Science.gov (United States)

    Wassum, Kate M.; Ostlund, Sean B.; Balleine, Bernard W.; Maidment, Nigel T.

    2011-01-01

    Here we attempted to clarify the role of dopamine signaling in reward seeking. In Experiment 1, we assessed the effects of the dopamine D1/D2 receptor antagonist flupenthixol (0.5 mg/kg i.p.) on Pavlovian incentive motivation and found that flupenthixol blocked the ability of a conditioned stimulus to enhance both goal approach and instrumental performance (Pavlovian-to-instrumental transfer). In Experiment 2 we assessed the effects of flupenthixol on reward palatability during post-training noncontingent re-exposure to the sucrose reward in either a control 3-h or novel 23-h food-deprived state. Flupenthixol, although effective in blocking the Pavlovian goal approach, was without effect on palatability or the increase in reward palatability induced by the upshift in motivational state. This noncontingent re-exposure provided an opportunity for instrumental incentive learning, the process by which rats encode the value of a reward for use in updating reward-seeking actions. Flupenthixol administered prior to the instrumental incentive learning opportunity did not affect the increase in subsequent off-drug reward-seeking actions induced by that experience. These data suggest that although dopamine signaling is necessary for Pavlovian incentive motivation, it is not necessary for changes in reward experience, or for the instrumental incentive learning process that translates this experience into the incentive value used to drive reward-seeking actions, and provide further evidence that Pavlovian and instrumental incentive learning processes are dissociable. PMID:21693635

  16. Foundations of signal processing

    CERN Document Server

    Vetterli, Martin; Goyal, Vivek K

    2014-01-01

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

  17. 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...

  18. 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...

  19. 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...

  20. 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.

  1. 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)

  2. 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.)

  3. 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

  4. 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

  5. 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.

  6. 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....

  7. 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.

  8. 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

  9. 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

  10. 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...

  11. 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...

  12. 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)

  13. 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

  14. Proceedings of IEEE Workshop on Machine Learning for Signal Processing XIV

    DEFF Research Database (Denmark)

    Larsen, Jan

    of machine learning. We would like to express our appreciation and gratitude to UFMA, EMAP, ELETROBRÁS, ELETRONORTE, ALUMAR and BASA, who contributed to the workshop by providing technical and financial support in various forms. Our warmest, special thanks go to our plenary speakers: Prof. Petar M. Djuric...

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

    Science.gov (United States)

    1981-03-13

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

  16. 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.

  17. 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

  18. 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.

  19. 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

  20. Striatal and Hippocampal Entropy and Recognition Signals in Category Learning: Simultaneous Processes Revealed by Model-Based fMRI

    Science.gov (United States)

    Davis, Tyler; Love, Bradley C.; Preston, Alison R.

    2012-01-01

    Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and…

  1. 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

  2. Vicarious reinforcement learning signals when instructing others.

    Science.gov (United States)

    Apps, Matthew A J; Lesage, Elise; Ramnani, Narender

    2015-02-18

    Reinforcement learning (RL) theory posits that learning is driven by discrepancies between the predicted and actual outcomes of actions (prediction errors [PEs]). In social environments, learning is often guided by similar RL mechanisms. For example, teachers monitor the actions of students and provide feedback to them. This feedback evokes PEs in students that guide their learning. We report the first study that investigates the neural mechanisms that underpin RL signals in the brain of a teacher. Neurons in the anterior cingulate cortex (ACC) signal PEs when learning from the outcomes of one's own actions but also signal information when outcomes are received by others. Does a teacher's ACC signal PEs when monitoring a student's learning? Using fMRI, we studied brain activity in human subjects (teachers) as they taught a confederate (student) action-outcome associations by providing positive or negative feedback. We examined activity time-locked to the students' responses, when teachers infer student predictions and know actual outcomes. We fitted a RL-based computational model to the behavior of the student to characterize their learning, and examined whether a teacher's ACC signals when a student's predictions are wrong. In line with our hypothesis, activity in the teacher's ACC covaried with the PE values in the model. Additionally, activity in the teacher's insula and ventromedial prefrontal cortex covaried with the predicted value according to the student. Our findings highlight that the ACC signals PEs vicariously for others' erroneous predictions, when monitoring and instructing their learning. These results suggest that RL mechanisms, processed vicariously, may underpin and facilitate teaching behaviors. Copyright © 2015 Apps et al.

  3. Underwater Acoustic Signal Processing

    National Research Council Canada - National Science Library

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

    2007-01-01

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

  4. 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.

  5. 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.

  6. 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

  7. Stochastic Learning and the Intuitive Criterion in Simple Signaling Games

    DEFF Research Database (Denmark)

    Sloth, Birgitte; Whitta-Jacobsen, Hans Jørgen

    A stochastic learning process for signaling games with two types, two signals, and two responses gives rise to equilibrium selection which is in remarkable accordance with the selection obtained by the intuitive criterion......A stochastic learning process for signaling games with two types, two signals, and two responses gives rise to equilibrium selection which is in remarkable accordance with the selection obtained by the intuitive criterion...

  8. 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...

  9. 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.

  10. 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

  11. Digital Signal Processing applied to Physical Signals

    CERN Document Server

    Alberto, Diego; Musa, L

    2011-01-01

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

  12. Transnational Learning Processes

    DEFF Research Database (Denmark)

    Nedergaard, Peter

    This paper analyses and compares the transnational learning processes in the employment field in the European Union and among the Nordic countries. Based theoretically on a social constructivist model of learning and methodologically on a questionnaire distributed to the relevant participants......, a number of hypotheses concerning transnational learning processes are tested. The paper closes with a number of suggestions regarding an optimal institutional setting for facilitating transnational learning processes.Key words: Transnational learning, Open Method of Coordination, Learning, Employment......, European Employment Strategy, European Union, Nordic countries....

  13. 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...

  14. Sensor array signal processing

    CERN Document Server

    Naidu, Prabhakar S

    2009-01-01

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

  15. Handbook of signal processing systems

    CERN Document Server

    Deprettere, Ed; Leupers, Rainer; Takala, Jarmo

    2013-01-01

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

  16. 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

  17. 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.

  18. 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  

  19. Wavelets and multiscale signal processing

    CERN Document Server

    Cohen, Albert

    1995-01-01

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

  20. Learning dialog act processing

    OpenAIRE

    Wermter, Stefan; Löchel, Matthias

    1996-01-01

    In this paper we describe a new approach for learning dialog act processing. In this approach we integrate a symbolic semantic segmentation parser with a learning dialog act network. In order to support the unforeseeable errors and variations of spoken language we have concentrated on robust data-driven learning. This approach already compares favorably with the statistical average plausibility method, produces a segmentation and dialog act assignment for all utterances in a robust manner,...

  1. Learning sparse generative models of audiovisual signals

    OpenAIRE

    Monaci, Gianluca; Sommer, Friedrich T.; Vandergheynst, Pierre

    2008-01-01

    This paper presents a novel framework to learn sparse represen- tations for audiovisual signals. An audiovisual signal is modeled as a sparse sum of audiovisual kernels. The kernels are bimodal functions made of synchronous audio and video components that can be positioned independently and arbitrarily in space and time. We design an algorithm capable of learning sets of such audiovi- sual, synchronous, shift-invariant functions by alternatingly solving a coding and a learning pr...

  2. 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

  3. Computer-based and screencasts approach in the signal processing basics electrical engineering course : does blended-learning work to motivate students?

    NARCIS (Netherlands)

    Gomez Puente, S.M.; Sommen, P.C.W.

    2016-01-01

    This paper presents the first experience of the computer-based and screencast approach used in the Signal Processing Basics course to motivate first year electrical engineering students to assess own knowledge and skills. Signal Processing Basics is a freshman course with up to 240 students. With

  4. 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

  5. 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....

  6. 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.

  7. 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

  8. Experiment and practice on signal processing

    International Nuclear Information System (INIS)

    2002-11-01

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

  9. Experiment and practice on signal processing

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2002-11-15

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

  10. Signalling chains with probe and adjust learning

    Science.gov (United States)

    Gosti, Giorgio

    2018-04-01

    Many models explain the evolution of signalling in repeated stage games on social networks, differently in this study each signalling game evolves a communication strategy to transmit information across the network. Specifically, I formalise signalling chain games as a generalisation of Lewis' signalling games, where a number of players are placed on a chain network and play a signalling game in which they have to propagate information across the network. I show that probe and adjust learning allows the system to develop communication conventions, but it may temporarily perturb the system out of conventions. Through simulations, I evaluate how long the system takes to evolve a signalling convention and the amount of time it stays in it. This discussion presents a mechanism in which simple players can evolve signalling across a social network without necessarily understanding the entire system.

  11. Neural Correlates of Success and Failure Signals During Neurofeedback Learning.

    Science.gov (United States)

    Radua, Joaquim; Stoica, Teodora; Scheinost, Dustin; Pittenger, Christopher; Hampson, Michelle

    2018-05-15

    Feedback-driven learning, observed across phylogeny and of clear adaptive value, is frequently operationalized in simple operant conditioning paradigms, but it can be much more complex, driven by abstract representations of success and failure. This study investigates the neural processes involved in processing success and failure during feedback learning, which are not well understood. Data analyzed were acquired during a multisession neurofeedback experiment in which ten participants were presented with, and instructed to modulate, the activity of their orbitofrontal cortex with the aim of decreasing their anxiety. We assessed the regional blood-oxygenation-level-dependent response to the individualized neurofeedback signals of success and failure across twelve functional runs acquired in two different magnetic resonance sessions in each of ten individuals. Neurofeedback signals of failure correlated early during learning with deactivation in the precuneus/posterior cingulate and neurofeedback signals of success correlated later during learning with deactivation in the medial prefrontal/anterior cingulate cortex. The intensity of the latter deactivations predicted the efficacy of the neurofeedback intervention in the reduction of anxiety. These findings indicate a role for regulation of the default mode network during feedback learning, and suggest a higher sensitivity to signals of failure during the early feedback learning and to signals of success subsequently. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

  12. Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

    DEFF Research Database (Denmark)

    Thrane, Jakob; Wass, Jesper; Piels, Molly

    2017-01-01

    Linear signal processing algorithms are effective in dealing with linear transmission channel and linear signal detection, while the nonlinear signal processing algorithms, from the machine learning community, are effective in dealing with nonlinear transmission channel and nonlinear signal...... detection. In this paper, a brief overview of the various machine learning methods and their application in optical communication is presented and discussed. Moreover, supervised machine learning methods, such as neural networks and support vector machine, are experimentally demonstrated for in-band optical...

  13. Brain signal complexity rises with repetition suppression in visual learning.

    Science.gov (United States)

    Lafontaine, Marc Philippe; Lacourse, Karine; Lina, Jean-Marc; McIntosh, Anthony R; Gosselin, Frédéric; Théoret, Hugo; Lippé, Sarah

    2016-06-21

    Neuronal activity associated with visual processing of an unfamiliar face gradually diminishes when it is viewed repeatedly. This process, known as repetition suppression (RS), is involved in the acquisition of familiarity. Current models suggest that RS results from interactions between visual information processing areas located in the occipito-temporal cortex and higher order areas, such as the dorsolateral prefrontal cortex (DLPFC). Brain signal complexity, which reflects information dynamics of cortical networks, has been shown to increase as unfamiliar faces become familiar. However, the complementarity of RS and increases in brain signal complexity have yet to be demonstrated within the same measurements. We hypothesized that RS and brain signal complexity increase occur simultaneously during learning of unfamiliar faces. Further, we expected alteration of DLPFC function by transcranial direct current stimulation (tDCS) to modulate RS and brain signal complexity over the occipito-temporal cortex. Participants underwent three tDCS conditions in random order: right anodal/left cathodal, right cathodal/left anodal and sham. Following tDCS, participants learned unfamiliar faces, while an electroencephalogram (EEG) was recorded. Results revealed RS over occipito-temporal electrode sites during learning, reflected by a decrease in signal energy, a measure of amplitude. Simultaneously, as signal energy decreased, brain signal complexity, as estimated with multiscale entropy (MSE), increased. In addition, prefrontal tDCS modulated brain signal complexity over the right occipito-temporal cortex during the first presentation of faces. These results suggest that although RS may reflect a brain mechanism essential to learning, complementary processes reflected by increases in brain signal complexity, may be instrumental in the acquisition of novel visual information. Such processes likely involve long-range coordinated activity between prefrontal and lower order visual

  14. 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.

  15. 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

  16. 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.

  17. Process Dissociation and Mixture Signal Detection Theory

    Science.gov (United States)

    DeCarlo, Lawrence T.

    2008-01-01

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

  18. 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...

  19. 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....

  20. [Automated processing of electrophysiologic signals].

    Science.gov (United States)

    Korenevskiĭ, N A; Gubanov, V V

    1995-01-01

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

  1. Advanced Methods of Biomedical Signal Processing

    CERN Document Server

    Cerutti, Sergio

    2011-01-01

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

  2. 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.

  3. 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

  4. 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

  5. Fast digitizing and digital signal processing of detector signals

    International Nuclear Information System (INIS)

    Hannaske, Roland

    2008-01-01

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

  6. Cognitive Algorithms for Signal Processing

    Science.gov (United States)

    2011-03-18

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

  7. 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.

  8. Knee joint vibroarthrographic signal processing and analysis

    CERN Document Server

    Wu, Yunfeng

    2015-01-01

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

  9. Advances in heuristic signal processing and applications

    CERN Document Server

    Chatterjee, Amitava; Siarry, Patrick

    2013-01-01

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

  10. 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....

  11. Pedagogical reforms of digital signal processing education

    Science.gov (United States)

    Christensen, Michael

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

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. Electronic devices for analog signal processing

    CERN Document Server

    Rybin, Yu K

    2012-01-01

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

  17. Denoising of gravitational wave signals via dictionary learning algorithms

    Science.gov (United States)

    Torres-Forné, Alejandro; Marquina, Antonio; Font, José A.; Ibáñez, José M.

    2016-12-01

    Gravitational wave astronomy has become a reality after the historical detections accomplished during the first observing run of the two advanced LIGO detectors. In the following years, the number of detections is expected to increase significantly with the full commissioning of the advanced LIGO, advanced Virgo and KAGRA detectors. The development of sophisticated data analysis techniques to improve the opportunities of detection for low signal-to-noise-ratio events is, hence, a most crucial effort. In this paper, we present one such technique, dictionary-learning algorithms, which have been extensively developed in the last few years and successfully applied mostly in the context of image processing. However, to the best of our knowledge, such algorithms have not yet been employed to denoise gravitational wave signals. By building dictionaries from numerical relativity templates of both binary black holes mergers and bursts of rotational core collapse, we show how machine-learning algorithms based on dictionaries can also be successfully applied for gravitational wave denoising. We use a subset of signals from both catalogs, embedded in nonwhite Gaussian noise, to assess our techniques with a large sample of tests and to find the best model parameters. The application of our method to the actual signal GW150914 shows promising results. Dictionary-learning algorithms could be a complementary addition to the gravitational wave data analysis toolkit. They may be used to extract signals from noise and to infer physical parameters if the data are in good enough agreement with the morphology of the dictionary atoms.

  18. 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...

  19. 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...

  20. 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

  1. 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)

  2. 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

  3. 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.

  4. Signal processing: opportunities for superconductive circuits

    International Nuclear Information System (INIS)

    Ralston, R.W.

    1985-01-01

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

  5. 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

  6. Dissociable Learning Processes Underlie Human Pain Conditioning.

    Science.gov (United States)

    Zhang, Suyi; Mano, Hiroaki; Ganesh, Gowrishankar; Robbins, Trevor; Seymour, Ben

    2016-01-11

    Pavlovian conditioning underlies many aspects of pain behavior, including fear and threat detection [1], escape and avoidance learning [2], and endogenous analgesia [3]. Although a central role for the amygdala is well established [4], both human and animal studies implicate other brain regions in learning, notably ventral striatum and cerebellum [5]. It remains unclear whether these regions make different contributions to a single aversive learning process or represent independent learning mechanisms that interact to generate the expression of pain-related behavior. We designed a human parallel aversive conditioning paradigm in which different Pavlovian visual cues probabilistically predicted thermal pain primarily to either the left or right arm and studied the acquisition of conditioned Pavlovian responses using combined physiological recordings and fMRI. Using computational modeling based on reinforcement learning theory, we found that conditioning involves two distinct types of learning process. First, a non-specific "preparatory" system learns aversive facial expressions and autonomic responses such as skin conductance. The associated learning signals-the learned associability and prediction error-were correlated with fMRI brain responses in amygdala-striatal regions, corresponding to the classic aversive (fear) learning circuit. Second, a specific lateralized system learns "consummatory" limb-withdrawal responses, detectable with electromyography of the arm to which pain is predicted. Its related learned associability was correlated with responses in ipsilateral cerebellar cortex, suggesting a novel computational role for the cerebellum in pain. In conclusion, our results show that the overall phenotype of conditioned pain behavior depends on two dissociable reinforcement learning circuits. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  7. 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

  8. 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

  9. Learning processes across knowledge domains

    DEFF Research Database (Denmark)

    Hall-Andersen, Lene Bjerg; Broberg, Ole

    2014-01-01

    Purpose - The purpose of this paper is to shed light on the problematics of learning across knowledge boundaries in organizational settings. The paper specifically explores learning processes that emerge, when a new knowledge domain is introduced into an existing organizational practice with the ...

  10. 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

  11. Nonlinear filtering for LIDAR signal processing

    Directory of Open Access Journals (Sweden)

    D. G. Lainiotis

    1996-01-01

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

  12. Digital signal processing theory and practice

    CERN Document Server

    Rao, K Deergha

    2018-01-01

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

  13. 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.

  14. 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.

  15. 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.

  16. 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.)

  17. 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

  18. 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).

  19. 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

  20. 'Steps in the learning Process'

    International Nuclear Information System (INIS)

    Cheung, Kyung Mo; Cheung, Hwan

    1984-01-01

    The process by which a student learns is extremely complicated. Whether he is simply learning facts, laws or formulae, changing his values or mastering a skill the way in which his brain functions is impossible to describe. The idea of learning domains is put forward not to explain in biological terms what happens in the brain but simply to attempt to break the system down into simpler units so that the learning process can be organized in an easier, more systematic way. In the most commonly used description of this process, the one described by BLOOM, this is BLOOM's Taxonomy. In addition to, I'd like to compare with the work of Lewis (Levels of Knowledge and Understanding). As a result, let us discuss about the most effective method in teaching in order to supply high-quality education

  1. 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...

  2. 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

  3. 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).

  4. 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…

  5. 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.

  6. Neural signals of vicarious extinction learning.

    Science.gov (United States)

    Golkar, Armita; Haaker, Jan; Selbing, Ida; Olsson, Andreas

    2016-10-01

    Social transmission of both threat and safety is ubiquitous, but little is known about the neural circuitry underlying vicarious safety learning. This is surprising given that these processes are critical to flexibly adapt to a changeable environment. To address how the expression of previously learned fears can be modified by the transmission of social information, two conditioned stimuli (CS + s) were paired with shock and the third was not. During extinction, we held constant the amount of direct, non-reinforced, exposure to the CSs (i.e. direct extinction), and critically varied whether another individual-acting as a demonstrator-experienced safety (CS + vic safety) or aversive reinforcement (CS + vic reinf). During extinction, ventromedial prefrontal cortex (vmPFC) responses to the CS + vic reinf increased but decreased to the CS + vic safety This pattern of vmPFC activity was reversed during a subsequent fear reinstatement test, suggesting a temporal shift in the involvement of the vmPFC. Moreover, only the CS + vic reinf association recovered. Our data suggest that vicarious extinction prevents the return of conditioned fear responses, and that this efficacy is reflected by diminished vmPFC involvement during extinction learning. The present findings may have important implications for understanding how social information influences the persistence of fear memories in individuals suffering from emotional disorders. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  7. 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

  8. 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

  9. E-learning educational process

    Directory of Open Access Journals (Sweden)

    Leszek Rudak

    2012-06-01

    Full Text Available The e-learning educational process differs fundamentally from the teaching-learning process in the face-to-face teaching. A reason of differences is the nature of the distance education: the teacher cannot observe the student at work. Thus, the natural process of teaching, based on performing particular actions by teacher and students in relays, is disturbed. So, one has to consider the e-learning educational process as two separate sets of actions. The first, strongly regular, consists of teachers operations. The second, unorganized, contains the student activities. In the article some relations between the both structures are investigated. Moreover, some methods of arranging the set of students’ activities to better fit in with the educational goals are provided.

  10. 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.

  11. Living and learning food processing

    Science.gov (United States)

    This year’s annual event promises to be both exciting and educational for those who wish to learn more about food processing. This column will provide a brief overview of the multitude of scientific sessions that reveal new research related to food processing. In addition to the symposia previewed h...

  12. 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.

  13. Continuous residual reinforcement learning for traffic signal control optimization

    NARCIS (Netherlands)

    Aslani, Mohammad; Seipel, Stefan; Wiering, Marco

    2018-01-01

    Traffic signal control can be naturally regarded as a reinforcement learning problem. Unfortunately, it is one of the most difficult classes of reinforcement learning problems owing to its large state space. A straightforward approach to address this challenge is to control traffic signals based on

  14. 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.

  15. Machinery vibration signal denoising based on learned dictionary and sparse representation

    International Nuclear Information System (INIS)

    Guo, Liang; Gao, Hongli; Li, Jun; Huang, Haifeng; Zhang, Xiaochen

    2015-01-01

    Mechanical vibration signal denoising has been an import problem for machine damage assessment and health monitoring. Wavelet transfer and sparse reconstruction are the powerful and practical methods. However, those methods are based on the fixed basis functions or atoms. In this paper, a novel method is presented. The atoms used to represent signals are learned from the raw signal. And in order to satisfy the requirements of real-time signal processing, an online dictionary learning algorithm is adopted. Orthogonal matching pursuit is applied to extract the most pursuit column in the dictionary. At last, denoised signal is calculated with the sparse vector and learned dictionary. A simulation signal and real bearing fault signal are utilized to evaluate the improved performance of the proposed method through the comparison with kinds of denoising algorithms. Then Its computing efficiency is demonstrated by an illustrative runtime example. The results show that the proposed method outperforms current algorithms with efficiency calculation. (paper)

  16. Haptic teleoperation systems signal processing perspective

    CERN Document Server

    Lee, Jae-young

    2015-01-01

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

  17. Genomic signal processing for DNA sequence clustering.

    Science.gov (United States)

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

    2018-01-01

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

  18. Signal processing method for Johnson noise thermometry

    International Nuclear Information System (INIS)

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

    2003-01-01

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

  19. 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.

  20. 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...

  1. Homework in the Learning Process

    Directory of Open Access Journals (Sweden)

    Gómez Sandra M.

    2000-08-01

    Full Text Available A problem has been observed that creates difficulties in the normal and productive development of the English courses. Without any doubt, doing homework is very important in the learning process of a new language. Doubtless it affects the student’s active participation in the classroom and his relationship to partners and teachers. Because of this, a research project was done with the aim to finding out strategies to ensure students do homework and make it part of the learning process, erasing the image of homework as a punishment.

  2. 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...

  3. The windmill of learning processes

    DEFF Research Database (Denmark)

    Kragelund, Linda

    2011-01-01

    that part of the nursing education has been reduced in some countries as e.g. Denmark.  The approach is presented through a model termed the 'Windmill of Learning Processes', which draws on empirical data from a qualitative investigation with an explorative and descriptive design, and on the theoretical......This article presents a new approach to student nurses' learning from their interaction with psychiatric patients. Using the approach can enable students and mentors to exploit students' learning opportunities, and help students to get the most out of their clinical placement in a time, where...... concepts of 'disjuncture', and 'everyday life activities'. 'Disjuncture' is defined as a situation in which there is disharmony between a person's experiences and the current situation. In such a situation there is potential for learning. My analysis of the empirical data led to the identification of a new...

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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...

  9. Gaussian processes for machine learning.

    Science.gov (United States)

    Seeger, Matthias

    2004-04-01

    Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided.

  10. 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

  11. 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.

  12. 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

  13. Ultrafast Optical Signal Processing with Bragg Structures

    Directory of Open Access Journals (Sweden)

    Yikun Liu

    2017-05-01

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

  14. Fourier transforms in radar and signal processing

    CERN Document Server

    Brandwood, David

    2011-01-01

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

  15. 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.

  16. 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)

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

    Science.gov (United States)

    Bergeron, Bryan; Cline, Andrew

    2011-01-01

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

  18. 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)

  19. 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

  20. 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

  1. Multiresolution, Geometric, and Learning Methods in Statistical Image Processing, Object Recognition, and Sensor Fusion

    National Research Council Canada - National Science Library

    Willsky, Alan

    2004-01-01

    .... Our research blends methods from several fields-statistics and probability, signal and image processing, mathematical physics, scientific computing, statistical learning theory, and differential...

  2. BURAR: Detection and signal processing capabilities

    International Nuclear Information System (INIS)

    Ghica, Daniela; Radulian, Mircea; Popa, Mihaela

    2004-01-01

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

  3. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Lapedes, A.; Farber, R.

    1987-06-01

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

  5. Signal Processing for Improved Wireless Receiver Performance

    DEFF Research Database (Denmark)

    Christensen, Lars P.B.

    2007-01-01

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

  6. Mathematical SETI Statistics, Signal Processing, Space Missions

    CERN Document Server

    Maccone, Claudio

    2012-01-01

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

  7. A simple approach to digital signal processing

    CERN Document Server

    Marven, Craig

    1996-01-01

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

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

    CERN Document Server

    Corinthios, Michael

    2009-01-01

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

  9. Learning Process Questionnaire Manual. Student Approaches to Learning and Studying.

    Science.gov (United States)

    Biggs, John B.

    This manual describes the theory behind the Learning Process Questionnaire (LPQ) used in Australia and defines what the subscale and scale scores mean. The LPQ is a 36-item self-report questionnaire that yields scores on three basic motives for learning and three learning strategies, and on the approaches to learning that are formed by these…

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

    International Nuclear Information System (INIS)

    Li, Q; Clifford, G D

    2012-01-01

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

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

    Science.gov (United States)

    Li, Q; Clifford, G D

    2012-09-01

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

  12. Learning for Nonstationary Dirichlet Processes

    Czech Academy of Sciences Publication Activity Database

    Quinn, A.; Kárný, Miroslav

    2007-01-01

    Roč. 21, č. 10 (2007), s. 827-855 ISSN 0890-6327 R&D Projects: GA AV ČR 1ET100750401 Grant - others:MŠk ČR(CZ) 2C06001 Program:2C Institutional research plan: CEZ:AV0Z10750506 Keywords : Nestacionární procesy * učení * Dirichletovy procesy * zapomínání Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.776, year: 2007 http://library.utia.cas.cz/separaty/2007/as/karny- learning for nonstationary dirichlet processes.pdf

  13. Seismic Signal Compression Using Nonparametric Bayesian Dictionary Learning via Clustering

    Directory of Open Access Journals (Sweden)

    Xin Tian

    2017-06-01

    Full Text Available We introduce a seismic signal compression method based on nonparametric Bayesian dictionary learning method via clustering. The seismic data is compressed patch by patch, and the dictionary is learned online. Clustering is introduced for dictionary learning. A set of dictionaries could be generated, and each dictionary is used for one cluster’s sparse coding. In this way, the signals in one cluster could be well represented by their corresponding dictionaries. A nonparametric Bayesian dictionary learning method is used to learn the dictionaries, which naturally infers an appropriate dictionary size for each cluster. A uniform quantizer and an adaptive arithmetic coding algorithm are adopted to code the sparse coefficients. With comparisons to other state-of-the art approaches, the effectiveness of the proposed method could be validated in the experiments.

  14. Learning the lipid language of plant signalling.

    NARCIS (Netherlands)

    van Leeuwen, W.; Okresz, L.; Bogre, L.; Munnik, T.

    2004-01-01

    Plant cells respond to different biotic and abiotic stresses by producing various uncommon phospholipids that are believed to play key roles in cell signalling. We can predict how they work because animal and yeast proteins have been shown to have specific lipid-binding domains, which act as docking

  15. 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...

  16. THE LET ME LEARN PROFESSIONAL LEARNING PROCESS FOR TEACHER TRANSFORMATION

    OpenAIRE

    Calleja, Colin

    2013-01-01

    This research set out to explore how a group of nine educators from a Catholic Church school in Malta, who have attended the Let Me Learn professional Learning process (LMLpLp), experienced personal and professional transformation. This study investigates those factors influencing participants in their transformative learning journey. It also explores the dynamics of transformative learning and whether individual transformation affects the school’s transformative learning experience. More spe...

  17. Neutron coincidence counting with digital signal processing

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  18. Signal Processing Model for Radiation Transport

    Energy Technology Data Exchange (ETDEWEB)

    Chambers, D H

    2008-07-28

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

  19. Closed orbit feedback with digital signal processing

    International Nuclear Information System (INIS)

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

    1994-01-01

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

  20. 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. .

  1. 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/...

  2. Local learning processes in Malaysian industry

    DEFF Research Database (Denmark)

    Wangel, Arne

    1999-01-01

    Local learning processes are a vital part of any dynamic assimilation of transferred technology. The paper raises the question about the interaction between the training paradigms, which transnational corporations introduce in their subsidiaries in Malaysia and the specific basis for learning...... of Malaysian labour. Experiences from Malaysian industry indicate that local learning processes are shaped, among other things, by the concept of knowledge in a particular training programme, labour market structures, and learning cultures....

  3. Microwave signal processing with photorefractive dynamic holography

    Science.gov (United States)

    Fotheringham, Edeline B.

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

  4. Signal processing for liquid ionization calorimeters

    International Nuclear Information System (INIS)

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

    1992-01-01

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

  5. Electrical measurement, signal processing, and displays

    CERN Document Server

    Webster, John G

    2003-01-01

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

  6. Classifying BCI signals from novice users with extreme learning machine

    Directory of Open Access Journals (Sweden)

    Rodríguez-Bermúdez Germán

    2017-07-01

    Full Text Available Brain computer interface (BCI allows to control external devices only with the electrical activity of the brain. In order to improve the system, several approaches have been proposed. However it is usual to test algorithms with standard BCI signals from experts users or from repositories available on Internet. In this work, extreme learning machine (ELM has been tested with signals from 5 novel users to compare with standard classification algorithms. Experimental results show that ELM is a suitable method to classify electroencephalogram signals from novice users.

  7. Interference in Ballistic Motor Learning: Specificity and Role of Sensory Error Signals

    Science.gov (United States)

    Lundbye-Jensen, Jesper; Petersen, Tue Hvass; Rothwell, John C.; Nielsen, Jens Bo

    2011-01-01

    Humans are capable of learning numerous motor skills, but newly acquired skills may be abolished by subsequent learning. Here we ask what factors determine whether interference occurs in motor learning. We speculated that interference requires competing processes of synaptic plasticity in overlapping circuits and predicted specificity. To test this, subjects learned a ballistic motor task. Interference was observed following subsequent learning of an accuracy-tracking task, but only if the competing task involved the same muscles and movement direction. Interference was not observed from a non-learning task suggesting that interference requires competing learning. Subsequent learning of the competing task 4 h after initial learning did not cause interference suggesting disruption of early motor memory consolidation as one possible mechanism underlying interference. Repeated transcranial magnetic stimulation (rTMS) of corticospinal motor output at intensities below movement threshold did not cause interference, whereas suprathreshold rTMS evoking motor responses and (re)afferent activation did. Finally, the experiments revealed that suprathreshold repetitive electrical stimulation of the agonist (but not antagonist) peripheral nerve caused interference. The present study is, to our knowledge, the first to demonstrate that peripheral nerve stimulation may cause interference. The finding underscores the importance of sensory feedback as error signals in motor learning. We conclude that interference requires competing plasticity in overlapping circuits. Interference is remarkably specific for circuits involved in a specific movement and it may relate to sensory error signals. PMID:21408054

  8. Predicting Process Behaviour using Deep Learning

    OpenAIRE

    Evermann, Joerg; Rehse, Jana-Rebecca; Fettke, Peter

    2016-01-01

    Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel method in process prediction, which has largely relied on explicit process models, and also a novel application of deep learning methods. The approach is evaluated on two real da...

  9. Mixed signal learning by spike correlation propagation in feedback inhibitory circuits.

    Directory of Open Access Journals (Sweden)

    Naoki Hiratani

    2015-04-01

    Full Text Available The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory.

  10. Quantum Dot Devices for Optical Signal Processing

    DEFF Research Database (Denmark)

    Chen, Yaohui

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

  11. Statistical mechanics of learning orthogonal signals for general covariance models

    International Nuclear Information System (INIS)

    Hoyle, David C

    2010-01-01

    Statistical mechanics techniques have proved to be useful tools in quantifying the accuracy with which signal vectors are extracted from experimental data. However, analysis has previously been limited to specific model forms for the population covariance C, which may be inappropriate for real world data sets. In this paper we obtain new statistical mechanical results for a general population covariance matrix C. For data sets consisting of p sample points in R N we use the replica method to study the accuracy of orthogonal signal vectors estimated from the sample data. In the asymptotic limit of N,p→∞ at fixed α = p/N, we derive analytical results for the signal direction learning curves. In the asymptotic limit the learning curves follow a single universal form, each displaying a retarded learning transition. An explicit formula for the location of the retarded learning transition is obtained and we find marked variation in the location of the retarded learning transition dependent on the distribution of population covariance eigenvalues. The results of the replica analysis are confirmed against simulation

  12. 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.

  13. 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...

  14. Conceptualizing impact assessment as a learning process

    International Nuclear Information System (INIS)

    Sánchez, Luis E.; Mitchell, Ross

    2017-01-01

    This paper explores how project developers and their consultants, government regulators and stakeholders can learn from the impact assessment (IA) process, thus potentially improving its effectiveness and enhancing project sustainability. Despite the benefits that learning can bring to an organization, failure to learn appears commonplace both within the IA process and, once approved, subsequent industrial development. To nurture organizational learning through IA, enabling structures that foster information sharing and interpretation and enhance organizational memory are needed. In this paper learning outcomes are grouped into three categories: acquisition of knowledge and skills, developing new behaviors and developing sustainability-oriented norms and values. Means to achieve such outcomes include education and training, experiential learning, learning through public participation (social learning) and a ‘learning organization approach’. Societal expectations increasingly demand not only projects that ‘pass’ the review criteria of regulators, financiers and the community, but IA processes capable of delivering sustainable outcomes that include learning and sharing of knowledge. It is proposed that learning be treated as a purposeful – not as an accidental – outcome of IA, and facilitated by adopting a ‘learning organization approach’ coupled with best practice such as early stakeholder engagement. - Highlights: • Proponents are challenged to develop projects that deliver sustainable outcomes. • Passing the test of government approval may be insufficient to obtain a social license. • Learning by all stakeholders is vital to meet these challenges. • Learning outcomes have to go beyond instrumental learning to reach new behaviors, norms and values. • A “learning organization approach” can promote mutual learning and improve project design.

  15. Conceptualizing impact assessment as a learning process

    Energy Technology Data Exchange (ETDEWEB)

    Sánchez, Luis E., E-mail: lsanchez@usp.br [Escola Politécnica, University of São Paulo, Av. Prof. Mello Moraes, 2373, 05508-900 São Paulo (Brazil); Mitchell, Ross, E-mail: ross.mitchell@ualberta.net [Shell International Exploration & Production BV (Netherlands)

    2017-01-15

    This paper explores how project developers and their consultants, government regulators and stakeholders can learn from the impact assessment (IA) process, thus potentially improving its effectiveness and enhancing project sustainability. Despite the benefits that learning can bring to an organization, failure to learn appears commonplace both within the IA process and, once approved, subsequent industrial development. To nurture organizational learning through IA, enabling structures that foster information sharing and interpretation and enhance organizational memory are needed. In this paper learning outcomes are grouped into three categories: acquisition of knowledge and skills, developing new behaviors and developing sustainability-oriented norms and values. Means to achieve such outcomes include education and training, experiential learning, learning through public participation (social learning) and a ‘learning organization approach’. Societal expectations increasingly demand not only projects that ‘pass’ the review criteria of regulators, financiers and the community, but IA processes capable of delivering sustainable outcomes that include learning and sharing of knowledge. It is proposed that learning be treated as a purposeful – not as an accidental – outcome of IA, and facilitated by adopting a ‘learning organization approach’ coupled with best practice such as early stakeholder engagement. - Highlights: • Proponents are challenged to develop projects that deliver sustainable outcomes. • Passing the test of government approval may be insufficient to obtain a social license. • Learning by all stakeholders is vital to meet these challenges. • Learning outcomes have to go beyond instrumental learning to reach new behaviors, norms and values. • A “learning organization approach” can promote mutual learning and improve project design.

  16. Machine learning approaches for the prediction of signal peptides and otherprotein sorting signals

    DEFF Research Database (Denmark)

    Nielsen, Henrik; Brunak, Søren; von Heijne, Gunnar

    1999-01-01

    Prediction of protein sorting signals from the sequence of amino acids has great importance in the field of proteomics today. Recently,the growth of protein databases, combined with machine learning approaches, such as neural networks and hidden Markov models, havemade it possible to achieve...

  17. 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

  18. Robust digital processing of speech signals

    CERN Document Server

    Kovacevic, Branko; Veinović, Mladen; Marković, Milan

    2017-01-01

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

  19. SIGNAL PROCESSING UTILIZING RADIO FREQUENCY PHOTONICS

    Science.gov (United States)

    2017-09-07

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

  20. Signal processing for distributed readout using TESs

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  1. How initial representations shape coupled learning processes

    DEFF Research Database (Denmark)

    Puranam, Phanish; Swamy, M.

    2016-01-01

    Coupled learning processes, in which specialists from different domains learn how to make interdependent choices among alternatives, are common in organizations. We explore the role played by initial representations held by the learners in coupled learning processes using a formal agent-based model....... We find that initial representations have important consequences for the success of the coupled learning process, particularly when communication is constrained and individual rates of learning are high. Under these conditions, initial representations that generate incorrect beliefs can outperform...... one that does not discriminate among alternatives, or even a mix of correct and incorrect representations among the learners. We draw implications for the design of coupled learning processes in organizations. © 2016 INFORMS....

  2. On the organizational learning work process

    International Nuclear Information System (INIS)

    Weil, Richard; Apostolakis, George

    2000-01-01

    This paper presents an organizational learning work process for use at nuclear power plants or other high-risk industries. Relying on insights gained from surveying organizational learning activities at nuclear power plants, the proposed work process synthesizes distributed learning activities and improves upon existing organizational learning processes. A root-cause analysis that targets organizational factors is presented. Additionally, a more accurate and objective methodology for prioritizing operating experience is presented. This methodology was applied to a case study during a workshop with utility personnel held at MIT. (author)

  3. 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

  4. 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.

  5. 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.

  6. Effect of signal noise on the learning capability of an artificial neural network

    International Nuclear Information System (INIS)

    Vega, J.J.; Reynoso, R.; Calvet, H. Carrillo

    2009-01-01

    Digital Pulse Shape Analysis (DPSA) by artificial neural networks (ANN) is becoming an important tool to extract relevant information from digitized signals in different areas. In this paper, we present a systematic evidence of how the concomitant noise that distorts the signals or patterns to be identified by an ANN set limits to its learning capability. Also, we present evidence that explains overtraining as a competition between the relevant pattern features, on the one side, against the signal noise, on the other side, as the main cause defining the shape of the error surface in weight space and, consequently, determining the steepest descent path that controls the ANN adaptation process.

  7. Innovative signal processing for Johnson Noise thermometry

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-07-01

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

  8. Signal processing for underclad crack sizing

    International Nuclear Information System (INIS)

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

    1985-01-01

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

  9. Subspace Signal Processing in Structured Noise

    Science.gov (United States)

    1990-12-01

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

  10. 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.

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

    NARCIS (Netherlands)

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

    2005-01-01

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

  12. School Colors Enhance Learning Process

    Science.gov (United States)

    Modern Schools, 1976

    1976-01-01

    The dramatic use of bold colors in the interior design of the Greenhill Middle School in Dallas, Texas, is an example of how a learning environment can stimulate student interest and enthusiasm. (Author/MLF)

  13. Motion-compensated processing of image signals

    NARCIS (Netherlands)

    2010-01-01

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

  14. 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)

  15. 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....

  16. Functions of the learning portfolio in student teachers' learning process

    NARCIS (Netherlands)

    Mansvelder-Longayroux, D.D.; Beijaard, D.; Verloop, N.; Vermunt, J.D.

    2007-01-01

    In this study, we aimed to develop a framework that could be used to describe the value of the learning portfolio for the learning process of individual student teachers. Retrospective interviews with 21 student teachers were used, as were their portfolio-evaluation reports on their experiences of

  17. Functions of the learning portfolio in student teachers' learning process

    NARCIS (Netherlands)

    Mansvelder-Longayroux, Desiree D.; Beijaard, Douwe; Verloop, Nico; Vermunt, Jan D.

    In this study, we aimed to develop a framework that could be used to describe the value of the learning portfolio for the learning process of individual student teachers. Retrospective interviews with 21 student teachers were used, as were their portfolio-evaluation reports on their experiences Of

  18. Larger error signals in major depression are associated with better avoidance learning

    Directory of Open Access Journals (Sweden)

    James F eCavanagh

    2011-11-01

    Full Text Available The medial prefrontal cortex (mPFC is particularly reactive to signals of error, punishment, and conflict in the service of behavioral adaptation and it is consistently implicated in the etiology of Major Depressive Disorder (MDD. This association makes conceptual sense, given that MDD has been associated with hyper-reactivity in neural systems associated with punishment processing. Yet in practice, depression-related variance in measures of mPFC functioning often fails to relate to performance. For example, neuroelectric reflections of mediofrontal error signals are often found to be larger in MDD, but a deficit in post-error performance suggests that these error signals are not being used to rapidly adapt behavior. Thus, it remains unknown if depression-related variance in error signals reflects a meaningful alteration in the use of error or punishment information. However, larger mediofrontal error signals have also been related to another behavioral tendency: increased accuracy in avoidance learning. The integrity of this error-avoidance system remains untested in MDD. In this study, EEG was recorded as 21 symptomatic, drug-free participants with current or past MDD and 24 control participants performed a probabilistic reinforcement learning task. Depressed participants had larger mPFC EEG responses to error feedback than controls. The direct relationship between error signal amplitudes and avoidance learning accuracy was replicated. Crucially, this relationship was stronger in depressed participants for high conflict lose-lose situations, demonstrating a selective alteration of avoidance learning. This investigation provided evidence that larger error signal amplitudes in depression are associated with increased avoidance learning, identifying a candidate mechanistic model for hypersensitivity to negative outcomes in depression.

  19. 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....

  20. Creative Problem Solving as a Learning Process

    Directory of Open Access Journals (Sweden)

    Andreas Ninck

    2013-12-01

    Full Text Available The Business School at the Bern University of Applied Sciences is offering a new MScBA degree program in business development. The paper presents a practical report about the action learning approach in the course 'Business Analysis and Design'. Our problem-based approach is more than simply 'learning by doing'. In a world of increasing complexity, taking action alone will not result in a learning effect per se. What is imperative is to structure and facilitate the learning process on different levels: individual construction of mental models; understanding needs and developing adequate solutions; critical reflection of methods and processes. Reflective practice, where individuals are learning from their own professional experiences rather than from formal teaching or knowledge transfer, may be the most important source for lifelong learning.

  1. All-optical signal processing and regeneration

    DEFF Research Database (Denmark)

    Wolfson, David

    2001-01-01

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

  2. 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.

  3. Holistic processing from learned attention to parts.

    Science.gov (United States)

    Chua, Kao-Wei; Richler, Jennifer J; Gauthier, Isabel

    2015-08-01

    Attention helps us focus on what is most relevant to our goals, and prior work has shown that aspects of attention can be learned. Learned inattention to parts can abolish holistic processing of faces, but it is unknown whether learned attention to parts is sufficient to cause a change from part-based to holistic processing with objects. We trained subjects to individuate nonface objects (Greebles) from 2 categories: Ploks and Glips. Diagnostic information was in complementary halves for the 2 categories. Holistic processing was then tested with Plok-Glip composites that combined the kind of part that was diagnostic or nondiagnostic during training. Exposure to Greeble parts resulted in general failures of selective attention for nondiagnostic composites, but face-like holistic processing was only observed for diagnostic composites. These results demonstrated a novel link between learned attentional control and the acquisition of holistic processing. (c) 2015 APA, all rights reserved).

  4. Signal Processing of Underwater Acoustic Waves

    Science.gov (United States)

    1969-11-01

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

  5. Signal processing for mobile communications handbook

    CERN Document Server

    Ibnkahla, Mohamed

    2004-01-01

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

  6. 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.

  7. 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

  8. 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

  9. 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

  10. Process Systems Engineering Education: Learning by Research

    Science.gov (United States)

    Abbas, A.; Alhammadi, H. Y.; Romagnoli, J. A.

    2009-01-01

    In this paper, we discuss our approach in teaching the final-year course Process Systems Engineering. Students are given ownership of the course by transferring to them the responsibility of learning. A project-based group environment stimulates learning while solving a real engineering problem. We discuss postgraduate student involvement and how…

  11. Flexible Processes in Project-Centred Learning

    NARCIS (Netherlands)

    Ceri, Stefano; Matera, Maristella; Raffio, Alessandro; Spoelstra, Howard

    2007-01-01

    Ceri, S., Matera, M., Raffio, A. & Spoelstra, H. (2007). Flexible Processes in Project-Centred Learning. In E. Duval, R. Klamma, and M. Wolpers (Eds.), European Conference on Technology Enhanced Learning, Lecture Notes in Computer Science, Vol. 4753, pp. 463-468. Berlin Heidelberg: Springer-Verlag

  12. 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.

  13. Signals structural analysis and processing: application to acoustic signals recorded during sodium boiling in a nuclear reactor

    International Nuclear Information System (INIS)

    Rodriguez, J.

    1986-02-01

    An acoustic system that uses examples to learn the structure of specific signals linked to a corresponding class of physical phenomena, and classify an unknown signal (possibly with noise present) into one of the learned classes is presented. The first stage consists of smoothing the data. The signal is represented as a trace according to background and event. To learn the structures in each class, smoothed, segmented signals are used. For classification, three operations to modify the signal so that it perfectly verifies the model description are available [fr

  14. 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....

  15. 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

  16. Utilization of Smartphone Literacy In Learning Process

    Directory of Open Access Journals (Sweden)

    Yenni Yuniati

    2017-01-01

    Full Text Available The utilization of smartphones is increasingly developing among the students. It causes various modifications of attitude and behavior, that media literacy nowadays becomes highly important. Therefore, media literacy shall become the priority for related parties specifically parents and teachers. In addition to helping to find information and to conduct fast communication, smartphone is also functions in formal learning process among the students.The aim of this research is to acknowledge the utilization of smartphones in formal learning process. This study uses qualitative descriptive method which makes serious efforts in describing and depicting utilization of smartphones in learning process among Junior High School students in Bandung. The research result shows that smartphones may function as a device to channel messages and to stimulate the mind, feeling and desire of the students which may encourage learning process in them and to give positive values and to bridge media literacy among the students.

  17. Learning Markov Decision Processes for Model Checking

    DEFF Research Database (Denmark)

    Mao, Hua; Chen, Yingke; Jaeger, Manfred

    2012-01-01

    . The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation......Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm...... on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system...

  18. 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)

  19. Forgetting in Reinforcement Learning Links Sustained Dopamine Signals to Motivation.

    Science.gov (United States)

    Kato, Ayaka; Morita, Kenji

    2016-10-01

    It has been suggested that dopamine (DA) represents reward-prediction-error (RPE) defined in reinforcement learning and therefore DA responds to unpredicted but not predicted reward. However, recent studies have found DA response sustained towards predictable reward in tasks involving self-paced behavior, and suggested that this response represents a motivational signal. We have previously shown that RPE can sustain if there is decay/forgetting of learned-values, which can be implemented as decay of synaptic strengths storing learned-values. This account, however, did not explain the suggested link between tonic/sustained DA and motivation. In the present work, we explored the motivational effects of the value-decay in self-paced approach behavior, modeled as a series of 'Go' or 'No-Go' selections towards a goal. Through simulations, we found that the value-decay can enhance motivation, specifically, facilitate fast goal-reaching, albeit counterintuitively. Mathematical analyses revealed that underlying potential mechanisms are twofold: (1) decay-induced sustained RPE creates a gradient of 'Go' values towards a goal, and (2) value-contrasts between 'Go' and 'No-Go' are generated because while chosen values are continually updated, unchosen values simply decay. Our model provides potential explanations for the key experimental findings that suggest DA's roles in motivation: (i) slowdown of behavior by post-training blockade of DA signaling, (ii) observations that DA blockade severely impairs effortful actions to obtain rewards while largely sparing seeking of easily obtainable rewards, and (iii) relationships between the reward amount, the level of motivation reflected in the speed of behavior, and the average level of DA. These results indicate that reinforcement learning with value-decay, or forgetting, provides a parsimonious mechanistic account for the DA's roles in value-learning and motivation. Our results also suggest that when biological systems for value-learning

  20. Forgetting in Reinforcement Learning Links Sustained Dopamine Signals to Motivation.

    Directory of Open Access Journals (Sweden)

    Ayaka Kato

    2016-10-01

    Full Text Available It has been suggested that dopamine (DA represents reward-prediction-error (RPE defined in reinforcement learning and therefore DA responds to unpredicted but not predicted reward. However, recent studies have found DA response sustained towards predictable reward in tasks involving self-paced behavior, and suggested that this response represents a motivational signal. We have previously shown that RPE can sustain if there is decay/forgetting of learned-values, which can be implemented as decay of synaptic strengths storing learned-values. This account, however, did not explain the suggested link between tonic/sustained DA and motivation. In the present work, we explored the motivational effects of the value-decay in self-paced approach behavior, modeled as a series of 'Go' or 'No-Go' selections towards a goal. Through simulations, we found that the value-decay can enhance motivation, specifically, facilitate fast goal-reaching, albeit counterintuitively. Mathematical analyses revealed that underlying potential mechanisms are twofold: (1 decay-induced sustained RPE creates a gradient of 'Go' values towards a goal, and (2 value-contrasts between 'Go' and 'No-Go' are generated because while chosen values are continually updated, unchosen values simply decay. Our model provides potential explanations for the key experimental findings that suggest DA's roles in motivation: (i slowdown of behavior by post-training blockade of DA signaling, (ii observations that DA blockade severely impairs effortful actions to obtain rewards while largely sparing seeking of easily obtainable rewards, and (iii relationships between the reward amount, the level of motivation reflected in the speed of behavior, and the average level of DA. These results indicate that reinforcement learning with value-decay, or forgetting, provides a parsimonious mechanistic account for the DA's roles in value-learning and motivation. Our results also suggest that when biological systems

  1. 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.

  2. 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)

  3. 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.

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

    International Nuclear Information System (INIS)

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

    1991-01-01

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

  5. 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).

  6. 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....

  7. 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....

  8. 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

  9. 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....

  10. 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....

  11. 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....

  12. 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....

  13. 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

  14. 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

  15. 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.

  16. 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.

  17. 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.

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

    International Nuclear Information System (INIS)

    Mahmoud, H.K.A.E.

    2012-01-01

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

  19. Impaired implicit learning and feedback processing after stroke.

    Science.gov (United States)

    Lam, J M; Globas, C; Hosp, J A; Karnath, H-O; Wächter, T; Luft, A R

    2016-02-09

    The ability to learn is assumed to support successful recovery and rehabilitation therapy after stroke. Hence, learning impairments may reduce the recovery potential. Here, the hypothesis is tested that stroke survivors have deficits in feedback-driven implicit learning. Stroke survivors (n=30) and healthy age-matched control subjects (n=21) learned a probabilistic classification task with brain activation measured using functional magnetic resonance imaging in a subset of these individuals (17 stroke and 10 controls). Stroke subjects learned slower than controls to classify cues. After being rewarded with a smiley face, they were less likely to give the same response when the cue was repeated. Stroke subjects showed reduced brain activation in putamen, pallidum, thalamus, frontal and prefrontal cortices and cerebellum when compared with controls. Lesion analysis identified those stroke survivors as learning-impaired who had lesions in frontal areas, putamen, thalamus, caudate and insula. Lesion laterality had no effect on learning efficacy or brain activation. These findings suggest that stroke survivors have deficits in reinforcement learning that may be related to dysfunctional processing of feedback-based decision-making, reward signals and working memory. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

  20. 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.

  1. Students' learning processes during school-based learning and workplace learning in vocational education : a review

    NARCIS (Netherlands)

    Dr. Harmen Schaap; Dr. Liesbeth Baartman; Prof.Dr. Elly de Bruijn

    2012-01-01

    This article reviews 24 articles in order to get a structured view on student's learning processes when dealing with a combination of school-based learning and workplace learning in vocational education. It focuses on six main themes: students' expertise development, students' learning styles,

  2. Investigation of the Relationship between Learning Process and Learning Outcomes in E-Learning Environments

    Science.gov (United States)

    Yurdugül, Halil; Menzi Çetin, Nihal

    2015-01-01

    Problem Statement: Learners can access and participate in online learning environments regardless of time and geographical barriers. This brings up the umbrella concept of learner autonomy that contains self-directed learning, self-regulated learning and the studying process. Motivation and learning strategies are also part of this umbrella…

  3. 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

  4. Framework for Conducting Empirical Observations of Learning Processes.

    Science.gov (United States)

    Fischer, Hans Ernst; von Aufschnaiter, Stephan

    1993-01-01

    Reviews four hypotheses about learning: Comenius's transmission-reception theory, information processing theory, Gestalt theory, and Piagetian theory. Uses the categories preunderstanding, conceptual change, and learning processes to classify and assess investigations on learning processes. (PR)

  5. 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

  6. Reward processing in the value-driven attention network: reward signals tracking cue identity and location.

    Science.gov (United States)

    Anderson, Brian A

    2017-03-01

    Through associative reward learning, arbitrary cues acquire the ability to automatically capture visual attention. Previous studies have examined the neural correlates of value-driven attentional orienting, revealing elevated activity within a network of brain regions encompassing the visual corticostriatal loop [caudate tail, lateral occipital complex (LOC) and early visual cortex] and intraparietal sulcus (IPS). Such attentional priority signals raise a broader question concerning how visual signals are combined with reward signals during learning to create a representation that is sensitive to the confluence of the two. This study examines reward signals during the cued reward training phase commonly used to generate value-driven attentional biases. High, compared with low, reward feedback preferentially activated the value-driven attention network, in addition to regions typically implicated in reward processing. Further examination of these reward signals within the visual system revealed information about the identity of the preceding cue in the caudate tail and LOC, and information about the location of the preceding cue in IPS, while early visual cortex represented both location and identity. The results reveal teaching signals within the value-driven attention network during associative reward learning, and further suggest functional specialization within different regions of this network during the acquisition of an integrated representation of stimulus value. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  7. 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.

  8. 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.

  9. Biomedical signal acquisition, processing and transmission using smartphone

    International Nuclear Information System (INIS)

    Roncagliolo, Pablo; Arredondo, Luis; Gonzalez, AgustIn

    2007-01-01

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

  10. Biomedical signal acquisition, processing and transmission using smartphone

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-11-15

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

  11. 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...

  12. 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

  13. 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.

  14. Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

    Science.gov (United States)

    Jiang, Yizhang; Wu, Dongrui; Deng, Zhaohong; Qian, Pengjiang; Wang, Jun; Wang, Guanjin; Chung, Fu-Lai; Choi, Kup-Sze; Wang, Shitong

    2017-12-01

    Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the classification accuracy is usually not satisfactory for two main reasons: the distributions of the data used for training and testing may be different, and the amount of training data may not be enough. In addition, most machine learning approaches generate black-box models that are difficult to interpret. In this paper, we integrate transductive transfer learning, semi-supervised learning and TSK fuzzy system to tackle these three problems. More specifically, we use transfer learning to reduce the discrepancy in data distribution between the training and testing data, employ semi-supervised learning to use the unlabeled testing data to remedy the shortage of training data, and adopt TSK fuzzy system to increase model interpretability. Two learning algorithms are proposed to train the system. Our experimental results show that the proposed approaches can achieve better performance than many state-of-the-art seizure classification algorithms.

  15. 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).

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

    CERN Document Server

    Devasahayam, Suresh R

    2013-01-01

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

  17. 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.

  18. 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.

  19. Learning algorithms and automatic processing of languages

    International Nuclear Information System (INIS)

    Fluhr, Christian Yves Andre

    1977-01-01

    This research thesis concerns the field of artificial intelligence. It addresses learning algorithms applied to automatic processing of languages. The author first briefly describes some mechanisms of human intelligence in order to describe how these mechanisms are simulated on a computer. He outlines the specific role of learning in various manifestations of intelligence. Then, based on the Markov's algorithm theory, the author discusses the notion of learning algorithm. Two main types of learning algorithms are then addressed: firstly, an 'algorithm-teacher dialogue' type sanction-based algorithm which aims at learning how to solve grammatical ambiguities in submitted texts; secondly, an algorithm related to a document system which structures semantic data automatically obtained from a set of texts in order to be able to understand by references to any question on the content of these texts

  20. Explaining neural signals in human visual cortex with an associative learning model.

    Science.gov (United States)

    Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

    2012-08-01

    "Predictive coding" models posit a key role for associative learning in visual cognition, viewing perceptual inference as a process of matching (learned) top-down predictions (or expectations) against bottom-up sensory evidence. At the neural level, these models propose that each region along the visual processing hierarchy entails one set of processing units encoding predictions of bottom-up input, and another set computing mismatches (prediction error or surprise) between predictions and evidence. This contrasts with traditional views of visual neurons operating purely as bottom-up feature detectors. In support of the predictive coding hypothesis, a recent human neuroimaging study (Egner, Monti, & Summerfield, 2010) showed that neural population responses to expected and unexpected face and house stimuli in the "fusiform face area" (FFA) could be well-described as a summation of hypothetical face-expectation and -surprise signals, but not by feature detector responses. Here, we used computer simulations to test whether these imaging data could be formally explained within the broader framework of a mathematical neural network model of associative learning (Schmajuk, Gray, & Lam, 1996). Results show that FFA responses could be fit very closely by model variables coding for conditional predictions (and their violations) of stimuli that unconditionally activate the FFA. These data document that neural population signals in the ventral visual stream that deviate from classic feature detection responses can formally be explained by associative prediction and surprise signals.

  1. 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

  2. Optimality of Poisson Processes Intensity Learning with Gaussian Processes

    NARCIS (Netherlands)

    Kirichenko, A.; van Zanten, H.

    2015-01-01

    In this paper we provide theoretical support for the so-called "Sigmoidal Gaussian Cox Process" approach to learning the intensity of an inhomogeneous Poisson process on a d-dimensional domain. This method was proposed by Adams, Murray and MacKay (ICML, 2009), who developed a tractable computational

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. 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

  8. All-Optical Signal Processing using Silicon Devices

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  9. 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.

  10. 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.

  11. Spared internal but impaired external reward prediction error signals in major depressive disorder during reinforcement learning.

    Science.gov (United States)

    Bakic, Jasmina; Pourtois, Gilles; Jepma, Marieke; Duprat, Romain; De Raedt, Rudi; Baeken, Chris

    2017-01-01

    Major depressive disorder (MDD) creates debilitating effects on a wide range of cognitive functions, including reinforcement learning (RL). In this study, we sought to assess whether reward processing as such, or alternatively the complex interplay between motivation and reward might potentially account for the abnormal reward-based learning in MDD. A total of 35 treatment resistant MDD patients and 44 age matched healthy controls (HCs) performed a standard probabilistic learning task. RL was titrated using behavioral, computational modeling and event-related brain potentials (ERPs) data. MDD patients showed comparable learning rate compared to HCs. However, they showed decreased lose-shift responses as well as blunted subjective evaluations of the reinforcers used during the task, relative to HCs. Moreover, MDD patients showed normal internal (at the level of error-related negativity, ERN) but abnormal external (at the level of feedback-related negativity, FRN) reward prediction error (RPE) signals during RL, selectively when additional efforts had to be made to establish learning. Collectively, these results lend support to the assumption that MDD does not impair reward processing per se during RL. Instead, it seems to alter the processing of the emotional value of (external) reinforcers during RL, when additional intrinsic motivational processes have to be engaged. © 2016 Wiley Periodicals, Inc.

  12. 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...

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

    Directory of Open Access Journals (Sweden)

    Jack B. Dennis

    1996-01-01

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

  14. 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.

  15. 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.

  16. 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...

  17. Role of Symbolic Coding and Rehearsal Processes in Observational Learning

    Science.gov (United States)

    Bandura, Albert; Jeffery, Robert W.

    1973-01-01

    Results were interpreted supporting a social learning view of observational learning that emphasizes contral processing of response information in the acquisition phase and motor reproduction and incentive processes in the overt enactment of what has been learned. (Author)

  18. Body Learning: Examining the Processes of Skill Learning in Dance

    Science.gov (United States)

    Bailey, Richard; Pickard, Angela

    2010-01-01

    This paper was stimulated by the authors' attempt to understand the process of skill learning in dance. Its stimulus was a period of fieldwork based at the Royal Ballet School in London, and subsequent discussions with the school's teachers and with academic colleagues about how it was that the young dancers developed their characteristic set of…

  19. Understanding the Advising Learning Process Using Learning Taxonomies

    Science.gov (United States)

    Muehleck, Jeanette K.; Smith, Cathleen L.; Allen, Janine M.

    2014-01-01

    To better understand the learning that transpires in advising, we used Anderson et al.'s (2001) revision of Bloom's (1956) taxonomy and Krathwohl, Bloom, and Masia's (1964) affective taxonomy to analyze eight student-reported advising outcomes from Smith and Allen (2014). Using the cognitive processes and knowledge domains of Anderson et al.'s…

  20. 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

  1. 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.

  2. 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...

  3. 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

  4. 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

  5. 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.

  6. 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

  7. Awake, Offline Processing during Associative Learning.

    Science.gov (United States)

    Bursley, James K; Nestor, Adrian; Tarr, Michael J; Creswell, J David

    2016-01-01

    Offline processing has been shown to strengthen memory traces and enhance learning in the absence of conscious rehearsal or awareness. Here we evaluate whether a brief, two-minute offline processing period can boost associative learning and test a memory reactivation account for these offline processing effects. After encoding paired associates, subjects either completed a distractor task for two minutes or were immediately tested for memory of the pairs in a counterbalanced, within-subjects functional magnetic resonance imaging study. Results showed that brief, awake, offline processing improves memory for associate pairs. Moreover, multi-voxel pattern analysis of the neuroimaging data suggested reactivation of encoded memory representations in dorsolateral prefrontal cortex during offline processing. These results signify the first demonstration of awake, active, offline enhancement of associative memory and suggest that such enhancement is accompanied by the offline reactivation of encoded memory representations.

  8. Awake, Offline Processing during Associative Learning.

    Directory of Open Access Journals (Sweden)

    James K Bursley

    Full Text Available Offline processing has been shown to strengthen memory traces and enhance learning in the absence of conscious rehearsal or awareness. Here we evaluate whether a brief, two-minute offline processing period can boost associative learning and test a memory reactivation account for these offline processing effects. After encoding paired associates, subjects either completed a distractor task for two minutes or were immediately tested for memory of the pairs in a counterbalanced, within-subjects functional magnetic resonance imaging study. Results showed that brief, awake, offline processing improves memory for associate pairs. Moreover, multi-voxel pattern analysis of the neuroimaging data suggested reactivation of encoded memory representations in dorsolateral prefrontal cortex during offline processing. These results signify the first demonstration of awake, active, offline enhancement of associative memory and suggest that such enhancement is accompanied by the offline reactivation of encoded memory representations.

  9. 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

  10. 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.

  11. 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

  12. 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)

  13. 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)

  14. Dissociation of binding and learning processes.

    Science.gov (United States)

    Moeller, Birte; Frings, Christian

    2017-11-01

    A single encounter of a stimulus together with a response can result in a short-lived association between the stimulus and the response [sometimes called an event file, see Hommel, Müsseler, Aschersleben, & Prinz, (2001) Behavioral and Brain Sciences, 24, 910-926]. The repetition of stimulus-response pairings typically results in longer lasting learning effects indicating stimulus-response associations (e.g., Logan & Etherton, (1994) Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 1022-1050]. An important question is whether or not what has been described as stimulus-response binding in action control research is actually identical with an early stage of incidental learning (e.g., binding might be seen as single-trial learning). Here, we present evidence that short-lived binding effects can be distinguished from learning of longer lasting stimulus-response associations. In two experiments, participants always responded to centrally presented target letters that were flanked by response irrelevant distractor letters. Experiment 1 varied whether distractors flanked targets on the horizontal or vertical axis. Binding effects were larger for a horizontal than for a vertical distractor-target configuration, while stimulus configuration did not influence incidental learning of longer lasting stimulus-response associations. In Experiment 2, the duration of the interval between response n - 1 and presentation of display n (500 ms vs. 2000 ms) had opposing influences on binding and learning effects. Both experiments indicate that modulating factors influence stimulus-response binding and incidental learning effects in different ways. We conclude that distinct underlying processes should be assumed for binding and incidental learning effects.

  15. 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

  16. 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

  17. 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)

  18. Smart signal processing for an evolving electric grid

    Science.gov (United States)

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

    2015-12-01

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

  19. 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.

  20. 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.

  1. Testing Methodology in the Student Learning Process

    Science.gov (United States)

    Gorbunova, Tatiana N.

    2017-01-01

    The subject of the research is to build methodologies to evaluate the student knowledge by testing. The author points to the importance of feedback about the mastering level in the learning process. Testing is considered as a tool. The object of the study is to create the test system models for defence practice problems. Special attention is paid…

  2. When a regulation becomes a learning process

    DEFF Research Database (Denmark)

    Nunez, Heilyn Camacho; Cespedes, Paula

    systems. It influences the business processes, and therefore a business practice should be redeveloped and redefined, furthermore the control over the ICT practice has become very important in the recent years. Some frameworks, methodologies and bodies of knowledge have been developed to support......, a small consulting company from Costa Rica, is using action learning to implement COBIT in the financial sector in Costa Rica....

  3. 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.

  4. Dual learning processes in interactive skill acquisition.

    Science.gov (United States)

    Fu, Wai-Tat; Anderson, John R

    2008-06-01

    Acquisition of interactive skills involves the use of internal and external cues. Experiment 1 showed that when actions were interdependent, learning was effective with and without external cues in the single-task condition but was effective only with the presence of external cues in the dual-task condition. In the dual-task condition, actions closer to the feedback were learned faster than actions farther away but this difference was reversed in the single-task condition. Experiment 2 tested how knowledge acquired in single and dual-task conditions would transfer to a new reward structure. Results confirmed the two forms of learning mediated by the secondary task: A declarative memory encoding process that simultaneously assigned credits to actions and a reinforcement-learning process that slowly propagated credits backward from the feedback. The results showed that both forms of learning were engaged during training, but only at the response selection stage, one form of knowledge may dominate over the other depending on the availability of attentional resources. (c) 2008 APA, all rights reserved

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

    NARCIS (Netherlands)

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

    2009-01-01

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

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

    DEFF Research Database (Denmark)

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

    1998-01-01

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

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

    CERN Document Server

    Gaydecki, Patrick

    2005-01-01

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

  8. A practicable signal processing algorithm for industrial nuclear instrument

    International Nuclear Information System (INIS)

    Tang Yaogeng; Gao Song; Yang Wujiao

    2006-01-01

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

  9. 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

  10. Programming signal processing applications on heterogeneous wireless sensor platforms

    NARCIS (Netherlands)

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

    2009-01-01

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

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

    Indian Academy of Sciences (India)

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

  12. Multiplexing and data processing of in-core signals

    International Nuclear Information System (INIS)

    Meyer, M.

    1983-01-01

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

  13. Nonlinear signal processing for ultrasonic imaging of material complexity

    Czech Academy of Sciences Publication Activity Database

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

    2010-01-01

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

  14. 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.

  15. Motor-related signals in the auditory system for listening and learning.

    Science.gov (United States)

    Schneider, David M; Mooney, Richard

    2015-08-01

    In the auditory system, corollary discharge signals are theorized to facilitate normal hearing and the learning of acoustic behaviors, including speech and music. Despite clear evidence of corollary discharge signals in the auditory cortex and their presumed importance for hearing and auditory-guided motor learning, the circuitry and function of corollary discharge signals in the auditory cortex are not well described. In this review, we focus on recent developments in the mouse and songbird that provide insights into the circuitry that transmits corollary discharge signals to the auditory system and the function of these signals in the context of hearing and vocal learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. IRB Process Improvements: A Machine Learning Analysis.

    Science.gov (United States)

    Shoenbill, Kimberly; Song, Yiqiang; Cobb, Nichelle L; Drezner, Marc K; Mendonca, Eneida A

    2017-06-01

    Clinical research involving humans is critically important, but it is a lengthy and expensive process. Most studies require institutional review board (IRB) approval. Our objective is to identify predictors of delays or accelerations in the IRB review process and apply this knowledge to inform process change in an effort to improve IRB efficiency, transparency, consistency and communication. We analyzed timelines of protocol submissions to determine protocol or IRB characteristics associated with different processing times. Our evaluation included single variable analysis to identify significant predictors of IRB processing time and machine learning methods to predict processing times through the IRB review system. Based on initial identified predictors, changes to IRB workflow and staffing procedures were instituted and we repeated our analysis. Our analysis identified several predictors of delays in the IRB review process including type of IRB review to be conducted, whether a protocol falls under Veteran's Administration purview and specific staff in charge of a protocol's review. We have identified several predictors of delays in IRB protocol review processing times using statistical and machine learning methods. Application of this knowledge to process improvement efforts in two IRBs has led to increased efficiency in protocol review. The workflow and system enhancements that are being made support our four-part goal of improving IRB efficiency, consistency, transparency, and communication.

  17. 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.

  18. Beyond the Learning Process and toward the Knowledge Creation Process: Linking Learning and Knowledge in the Supportive Learning Culture

    Science.gov (United States)

    Yoon, Seung Won; Song, Ji Hoon; Lim, Doo Hun

    2009-01-01

    This integrative literature review synthesizes the concepts and process of organizational knowledge creation with theories of individual learning. The knowledge conversion concept (Nonaka & Takeuchi, 1995; Nonaka, Toyama, & Byosiere, 2001) is used as the basis of the organizational knowledge creation process, while major learning theories relevant…

  19. Two Undergraduate Process Modeling Courses Taught Using Inductive Learning Methods

    Science.gov (United States)

    Soroush, Masoud; Weinberger, Charles B.

    2010-01-01

    This manuscript presents a successful application of inductive learning in process modeling. It describes two process modeling courses that use inductive learning methods such as inquiry learning and problem-based learning, among others. The courses include a novel collection of multi-disciplinary complementary process modeling examples. They were…

  20. 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

  1. Modulation of learning and memory by cytokines: signaling mechanisms and long term consequences.

    Science.gov (United States)

    Donzis, Elissa J; Tronson, Natalie C

    2014-11-01

    This review describes the role of cytokines and their downstream signaling cascades on the modulation of learning and memory. Immune proteins are required for many key neural processes and dysregulation of these functions by systemic inflammation can result in impairments of memory that persist long after the resolution of inflammation. Recent research has demonstrated that manipulations of individual cytokines can modulate learning, memory, and synaptic plasticity. The many conflicting findings, however, have prevented a clear understanding of the precise role of cytokines in memory. Given the complexity of inflammatory signaling, understanding its modulatory role requires a shift in focus from single cytokines to a network of cytokine interactions and elucidation of the cytokine-dependent intracellular signaling cascades. Finally, we propose that whereas signal transduction and transcription may mediate short-term modulation of memory, long-lasting cellular and molecular mechanisms such as epigenetic modifications and altered neurogenesis may be required for the long lasting impact of inflammation on memory and cognition. Copyright © 2014 Elsevier Inc. All rights reserved.

  2. 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...

  3. 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.

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

    Science.gov (United States)

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

    2014-09-01

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

  5. 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 ...

  6. 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

  7. 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

  8. 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.

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

    DEFF Research Database (Denmark)

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

    2008-01-01

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

  10. 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.

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

    Science.gov (United States)

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

    2018-05-01

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

  12. 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.

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

    International Nuclear Information System (INIS)

    Wintzer, K.

    1977-01-01

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

  14. 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

  15. 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.

  16. 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

  17. Smart Educational Process Based on Personal Learning Capabilities

    OpenAIRE

    Gavriushenko, Mariia; Lindberg, Renny S. N.; Khriyenko, Oleksiy

    2017-01-01

    Personalized learning is increasingly gaining popularity, especially with the development of information technology and modern educational resources for learning. Each person is individual and has different knowledge background, different kind of memory, different learning speed. Teacher can adapt learning course, learning instructions or learning material according to the majority of learners in class, but that means that learning process is not adapted to the personality of each...

  18. 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

  19. Extinction of avoidance behavior by safety learning depends on endocannabinoid signaling in the hippocampus.

    Science.gov (United States)

    Micale, Vincenzo; Stepan, Jens; Jurik, Angela; Pamplona, Fabricio A; Marsch, Rudolph; Drago, Filippo; Eder, Matthias; Wotjak, Carsten T

    2017-07-01

    The development of exaggerated avoidance behavior is largely responsible for the decreased quality of life in patients suffering from anxiety disorders. Studies using animal models have contributed to the understanding of the neural mechanisms underlying the acquisition of avoidance responses. However, much less is known about its extinction. Here we provide evidence in mice that learning about the safety of an environment (i.e., safety learning) rather than repeated execution of the avoided response in absence of negative consequences (i.e., response extinction) allowed the animals to overcome their avoidance behavior in a step-down avoidance task. This process was context-dependent and could be blocked by pharmacological (3 mg/kg, s.c.; SR141716) or genetic (lack of cannabinoid CB1 receptors in neurons expressing dopamine D1 receptors) inactivation of CB1 receptors. In turn, the endocannabinoid reuptake inhibitor AM404 (3 mg/kg, i.p.) facilitated safety learning in a CB1-dependent manner and attenuated the relapse of avoidance behavior 28 days after conditioning. Safety learning crucially depended on endocannabinoid signaling at level of the hippocampus, since intrahippocampal SR141716 treatment impaired, whereas AM404 facilitated safety learning. Other than AM404, treatment with diazepam (1 mg/kg, i.p.) impaired safety learning. Drug effects on behavior were directly mirrored by drug effects on evoked activity propagation through the hippocampal trisynaptic circuit in brain slices: As revealed by voltage-sensitive dye imaging, diazepam impaired whereas AM404 facilitated activity propagation to CA1 in a CB1-dependent manner. In line with this, systemic AM404 enhanced safety learning-induced expression of Egr1 at level of CA1. Together, our data render it likely that AM404 promotes safety learning by enhancing information flow through the trisynaptic circuit to CA1. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Serial Learning Process: Test of Chaining, Position, and Dual-Process Hypotheses

    Science.gov (United States)

    Giurintano, S. L.

    1973-01-01

    The chaining, position, and dual-process hypotheses of serial learning (SL) as well as serial recall, reordering, and relearning of paired-associate learning were examined to establish learning patterns. Results provide evidence for dual-process hypothesis. (DS)

  1. Prediction of preterm deliveries from EHG signals using machine learning.

    Directory of Open Access Journals (Sweden)

    Paul Fergus

    Full Text Available There has been some improvement in the treatment of preterm infants, which has helped to increase their chance of survival. However, the rate of premature births is still globally increasing. As a result, this group of infants are most at risk of developing severe medical conditions that can affect the respiratory, gastrointestinal, immune, central nervous, auditory and visual systems. In extreme cases, this can also lead to long-term conditions, such as cerebral palsy, mental retardation, learning difficulties, including poor health and growth. In the US alone, the societal and economic cost of preterm births, in 2005, was estimated to be $26.2 billion, per annum. In the UK, this value was close to £2.95 billion, in 2009. Many believe that a better understanding of why preterm births occur, and a strategic focus on prevention, will help to improve the health of children and reduce healthcare costs. At present, most methods of preterm birth prediction are subjective. However, a strong body of evidence suggests the analysis of uterine electrical signals (Electrohysterography, could provide a viable way of diagnosing true labour and predict preterm deliveries. Most Electrohysterography studies focus on true labour detection during the final seven days, before labour. The challenge is to utilise Electrohysterography techniques to predict preterm delivery earlier in the pregnancy. This paper explores this idea further and presents a supervised machine learning approach that classifies term and preterm records, using an open source dataset containing 300 records (38 preterm and 262 term. The synthetic minority oversampling technique is used to oversample the minority preterm class, and cross validation techniques, are used to evaluate the dataset against other similar studies. Our approach shows an improvement on existing studies with 96% sensitivity, 90% specificity, and a 95% area under the curve value with 8% global error using the polynomial

  2. Deep learning evaluation using deep linguistic processing

    OpenAIRE

    Kuhnle, Alexander; Copestake, Ann

    2017-01-01

    We discuss problems with the standard approaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a complement to current practice. We demonstrate that with the help of existing 'deep' linguistic processing technology we are able to create challenging abstract datasets, which enable us to investigate the language understanding abilities of multimodal deep learning models in detail, as compared to a single performance value ...

  3. Learning during Processing: Word Learning Doesn't Wait for Word Recognition to Finish

    Science.gov (United States)

    Apfelbaum, Keith S.; McMurray, Bob

    2017-01-01

    Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed…

  4. 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...

  5. 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.

  6. 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.

  7. Signal Processing for Time-Series Functions on a Graph

    Science.gov (United States)

    2018-02-01

    Figures Fig. 1 Time -series function on a fixed graph.............................................2 iv Approved for public release; distribution is...φi〉`2(V)φi (39) 6= f̄ (40) Instead, we simply recover the average of f over time . 13 Approved for public release; distribution is unlimited. This...ARL-TR-8276• FEB 2018 US Army Research Laboratory Signal Processing for Time -Series Functions on a Graph by Humberto Muñoz-Barona, Jean Vettel, and

  8. 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

  9. Synthesis of computational structures for analog signal processing

    CERN Document Server

    Popa, Cosmin Radu

    2011-01-01

    Presents the most important classes of computational structures for analog signal processing, including differential or multiplier structures, squaring or square-rooting circuits, exponential or Euclidean distance structures and active resistor circuitsIntroduces the original concept of the multifunctional circuit, an active structure that is able to implement, starting from the same circuit core, a multitude of continuous mathematical functionsCovers mathematical analysis, design and implementation of a multitude of function generator structures

  10. 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

  11. Digital signal processing of data from borehole creep closure

    International Nuclear Information System (INIS)

    Chakrabarti, S.; Patrick, W.C.; Duplancic, N.

    1987-01-01

    Digital signal processing, a technique commonly used in the fields of electrical engineering and communication technology, has been successfully used to analyze creep closure data obtained from a 0.91 m diameter by 5.13 deep borehole in bedded salt. By filtering the ''noise'' component of the closure data from a test borehole, important data trends were made more evident and average creep closure rates were able to be calculated. This process provided accurate estimates of closure rates that are used in the design of lined boreholes in which heat-generating transuranic nuclear wastes are emplaced at the Waste Isolation Pilot Plant

  12. Low power signal processing electronics for wearable medical devices.

    Science.gov (United States)

    Casson, Alexander J; Rodriguez-Villegas, Esther

    2010-01-01

    Custom designed microchips, known as Application Specific Integrated Circuits (ASICs), offer the lowest possible power consumption electronics. However, this comes at the cost of a longer, more complex and more costly design process compared to one using generic, off-the-shelf components. Nevertheless, their use is essential in future truly wearable medical devices that must operate for long periods of time from physically small, energy limited batteries. This presentation will demonstrate the state-of-the-art in ASIC technology for providing online signal processing for use in these wearable medical devices.

  13. Mannotriose regulates learning and memory signal transduction in the hippocampus

    Institute of Scientific and Technical Information of China (English)

    Lina Zhang; Weiwei Dai; Xueli Zhang; Zhangbin Gong; Guoqin Jin

    2013-01-01

    Rehmannia is a commonly used Chinese herb, which improves learning and memory. However, the crucial components of the signal transduction pathway associated with this effect remain elusive. Pri-mary hippocampal neurons were cultured in vitro, insulted with high-concentration (1 × 10-4 mol/L) cor-ticosterone, and treated with 1 × 10-4 mol/L mannotriose. Thiazolyl blue tetrazolium bromide assay and western blot analysis showed that hippocampal neuron survival rates and protein levels of glucocorti-coid receptor, serum and glucocorticoid-regulated protein kinase, and brain-derived neurotrophic factor were al dramatical y decreased after high-concentration corticosterone-induced injury. This effect was reversed by mannotriose, to a similar level as RU38486 and donepezil. Our findings indicate that mannotriose could protect hippocampal neurons from high-concentration corticosterone-induced injury. The mechanism by which this occurred was associated with levels of glucocorticoid receptor protein, serum and glucocorticoid-regulated protein kinase, and brain-derived neurotrophic factor.

  14. 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.

  15. Wireless receiver architectures and design antennas, RF, synthesizers, mixed signal, and digital signal processing

    CERN Document Server

    Rouphael, Tony J

    2014-01-01

    Wireless Receiver Architectures and Design presents the various designs and architectures of wireless receivers in the context of modern multi-mode and multi-standard devices. This one-stop reference and guide to designing low-cost low-power multi-mode, multi-standard receivers treats analog and digital signal processing simultaneously, with equal detail given to the chosen architecture and modulating waveform. It provides a complete understanding of the receiver's analog front end and the digital backend, and how each affects the other. The book explains the design process in great detail, s

  16. 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

  17. 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.

  18. 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.

  19. 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

  20. Entrepreneurship Learning Process by using SWOT Analysis

    Directory of Open Access Journals (Sweden)

    Jajat Sudrajat

    2016-03-01

    Full Text Available The research objective was to produce a model of learning entrepreneurship by using SWOT analysis, which was currently being run with the concept of large classes and small classes. The benefits of this study was expected to be useful for the Binus Entrepreneurship Center (BEC unit to create a map development learning entrepreneurship. Influences that would be generated by using SWOT Analysis were very wide as the benefits of the implementation of large classes and small classes for students and faculty. Participants of this study were Binus student of various majors who were taking courses EN001 and EN002. This study used research and development that examining the theoretical learning components of entrepreneurship education (teaching and learning dimension, where there were six dimensions of the survey which was a fundamental element in determining the framework of entrepreneurship education. Research finds that a strategy based on a matrix of factors is at least eight strategies for improving the learning process of entrepreneurship. From eight strategies are one of them strategies to increase collaboration BEC with family support. This strategy is supported by the survey results to the three majors who are following the EN001 and EN002, where more than 85% of the students are willing to do an aptitude test to determine the advantages and disadvantages of self-development and more of 54% of the students are not willing to accept the wishes of their parents because they do not correspond to his ideals. Based on the above results, it is suggested for further research, namely developing entrepreneurship research by analyzing other dimensions.

  1. Loss of Signal, Aeromedical Lessons Learned from the STS-107 Columbia Space Shuttle Mishap

    Science.gov (United States)

    Stepaniak, Phillip C.; Patlach, Robert

    2014-01-01

    Loss of Signal, a NASA publication to be available in May 2014 presents the aeromedical lessons learned from the Columbia accident that will enhance crew safety and survival on human space flight missions. These lessons were presented to limited audiences at three separate Aerospace Medical Association (AsMA) conferences: in 2004 in Anchorage, Alaska, on the causes of the accident; in 2005 in Kansas City, Missouri, on the response, recovery, and identification aspects of the investigation; and in 2011, again in Anchorage, Alaska, on future implications for human space flight. As we embark on the development of new spacefaring vehicles through both government and commercial efforts, the NASA Johnson Space Center Human Health and Performance Directorate is continuing to make this information available to a wider audience engaged in the design and development of future space vehicles. Loss of Signal summarizes and consolidates the aeromedical impacts of the Columbia mishap process-the response, recovery, identification, investigative studies, medical and legal forensic analysis, and future preparation that are needed to respond to spacecraft mishaps. The goal of this book is to provide an account of the aeromedical aspects of the Columbia accident and the investigation that followed, and to encourage aerospace medical specialists to continue to capture information, learn from it, and improve procedures and spacecraft designs for the safety of future crews. This poster presents an outline of Loss of Signal contents and highlights from each of five sections - the mission and mishap, the response, the investigation, the analysis and the future.

  2. 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)

  3. Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning

    KAUST Repository

    Teng, Haotian; Cao, Minh Duc; Hall, Michael B; Duarte, Tania; Wang, Sheng; Coin, Lachlan J M

    2018-01-01

    Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

  4. Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning

    KAUST Repository

    Teng, Haotian

    2018-04-10

    Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1996-02-01

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

  6. Perspectives of using spin waves for computing and signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Csaba, György, E-mail: gcsaba@gmail.com [Center for Nano Science and Technology, University of Notre Dame (United States); Faculty for Information Technology and Bionics, Pázmány Péter Catholic University (Hungary); Papp, Ádám [Center for Nano Science and Technology, University of Notre Dame (United States); Faculty for Information Technology and Bionics, Pázmány Péter Catholic University (Hungary); Porod, Wolfgang [Center for Nano Science and Technology, University of Notre Dame (United States)

    2017-05-03

    Highlights: • We give an overview of spin wave-based computing with emphasis on non-Boolean signal processors. • Spin waves can combine the best of electronics and photonics and do it in an on-chip and integrable way. • Copying successful approaches from microelectronics may not be the best way toward spin-wave based computing. • Practical devices can be constructed by minimizing the number of required magneto-electric interconnections. - Abstract: Almost all the world's information is processed and transmitted by either electric currents or photons. Now they may get a serious contender: spin-wave-based devices may just perform some information-processing tasks in a lot more efficient and practical way. In this article, we give an engineering perspective of the potential of spin-wave-based devices. After reviewing various flavors for spin-wave-based processing devices, we argue that the niche for spin-wave-based devices is low-power, compact and high-speed signal-processing devices, where most traditional electronics show poor performance.

  7. Wigner Ville Distribution in Signal Processing, using Scilab Environment

    Directory of Open Access Journals (Sweden)

    Petru Chioncel

    2011-01-01

    Full Text Available The Wigner Ville distribution offers a visual display of quantitative information about the way a signal’s energy is distributed in both, time and frequency. Through that, this distribution embodies the fundamentally concepts of the Fourier and time-domain analysis. The energy of the signal is distributed so that specific frequencies are localized in time by the group delay time and at specifics instants in time the frequency is given by the instantaneous frequency. The net positive volum of the Wigner distribution is numerically equal to the signal’s total energy. The paper shows the application of the Wigner Ville distribution, in the field of signal processing, using Scilab environment.

  8. CAS - CERN Accelerator School: Course on Digital Signal Processing

    CERN Document Server

    Digital Signal Processing; CAS 2007

    2008-01-01

    These proceedings present the lectures given at the twenty-first specialized course organized by the CERN Accelerator School (CAS), the topic being Digital Signal Processing. The course was held in Sigtuna, Sweden, from 31 May–9 June 2007. This is the first time this topic has been selected for a specialized course. Taking into account the number of related applications currently in use in accelerators around the world, it was recognized that such a topic should definitively be incorporated into the CAS series of specialized courses. The specific aim of the course was to introduce the participants to the use and programming of Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs) evaluation boards. The course consisted of lectures in the mornings covering fundamental background knowledge in mathematics, controls theory, design tools, programming hardware platforms, and implementation details. In the afternoons the students split into two groups with people working in pairs. One group w...

  9. Ultra-high-speed Optical Signal Processing using Silicon Photonics

    DEFF Research Database (Denmark)

    Oxenløwe, Leif Katsuo; Ji, Hua; Jensen, Asger Sellerup

    with a photonic layer on top to interconnect them. For such systems, silicon is an attractive candidate enabling both electronic and photonic control. For some network scenarios, it may be beneficial to use optical on-chip packet switching, and for high data-density environments one may take advantage...... of the ultra-fast nonlinear response of silicon photonic waveguides. These chips offer ultra-broadband wavelength operation, ultra-high timing resolution and ultra-fast response, and when used appropriately offer energy-efficient switching. In this presentation we review some all-optical functionalities based...... on silicon photonics. In particular we use nano-engineered silicon waveguides (nanowires) [1] enabling efficient phasematched four-wave mixing (FWM), cross-phase modulation (XPM) or self-phase modulation (SPM) for ultra-high-speed optical signal processing of ultra-high bit rate serial data signals. We show...

  10. Autonomous data acquisition system for Paks NPP process noise signals

    International Nuclear Information System (INIS)

    Lipcsei, S.; Kiss, S.; Czibok, T.; Dezso, Z.; Horvath, Cs.

    2005-01-01

    A prototype of a new concept noise diagnostics data acquisition system has been developed recently to renew the aged present system. This new system is capable of collecting the whole available noise signal set simultaneously. Signal plugging and data acquisition are performed by autonomous systems (installed at each reactor unit) that are controlled through the standard plant network from a central computer installed at a suitable location. Experts can use this central unit to process and archive data series downloaded from the reactor units. This central unit also provides selected noise diagnostics information for other departments. The paper describes the hardware and software architecture of the new system in detail, emphasising the potential benefits of the new approach. (author)

  11. Digital Signal Processing for Optical Coherent Communication Systems

    DEFF Research Database (Denmark)

    Zhang, Xu

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

  12. Role of Nonneuronal TRPV4 Signaling in Inflammatory Processes.

    Science.gov (United States)

    Rajasekhar, Pradeep; Poole, Daniel P; Veldhuis, Nicholas A

    2017-01-01

    Transient receptor potential (TRP) ion channels are important signaling components in nociceptive and inflammatory pathways. This is attributed to their ability to function as polymodal sensors of environmental stimuli (chemical and mechanical) and as effector molecules in receptor signaling pathways. TRP vanilloid 4 (TRPV4) is a nonselective cation channel that is activated by multiple endogenous stimuli including shear stress, membrane stretch, and arachidonic acid metabolites. TRPV4 contributes to many important physiological processes and dysregulation of its activity is associated with chronic conditions of metabolism, inflammation, peripheral neuropathies, musculoskeletal development, and cardiovascular regulation. Mechanosensory and receptor- or lipid-mediated signaling functions of TRPV4 have historically been attributed to central and peripheral neurons. However, with the development of potent and selective pharmacological tools, transgenic mice and improved molecular and imaging techniques, many new roles for TRPV4 have been revealed in nonneuronal cells. In this chapter, we discuss these recent findings and highlight the need for greater characterization of TRPV4-mediated signaling in nonneuronal cell types that are either directly associated with neurons or indirectly control their excitability through release of sensitizing cellular factors. We address the integral role of these cells in sensory and inflammatory processes as well as their importance when considering undesirable on-target effects that may be caused by systemic delivery of TRPV4-selective pharmaceutical agents for treatment of chronic diseases. In future, this will drive a need for targeted drug delivery strategies to regulate such a diverse and promiscuous protein. © 2017 Elsevier Inc. All rights reserved.

  13. Extracting meaning from audio signals - a machine learning approach

    DEFF Research Database (Denmark)

    Larsen, Jan

    2007-01-01

    * Machine learning framework for sound search * Genre classification * Music and audio separation * Wind noise suppression......* Machine learning framework for sound search * Genre classification * Music and audio separation * Wind noise suppression...

  14. Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning

    Directory of Open Access Journals (Sweden)

    Shandilya Sharad

    2012-10-01

    Full Text Available Abstract Background Ventricular Fibrillation (VF is a common presenting dysrhythmia in the setting of cardiac arrest whose main treatment is defibrillation through direct current countershock to achieve return of spontaneous circulation. However, often defibrillation is unsuccessful and may even lead to the transition of VF to more nefarious rhythms such as asystole or pulseless electrical activity. Multiple methods have been proposed for predicting defibrillation success based on examination of the VF waveform. To date, however, no analytical technique has been widely accepted. We developed a unique approach of computational VF waveform analysis, with and without addition of the signal of end-tidal carbon dioxide (PetCO2, using advanced machine learning algorithms. We compare these results with those obtained using the Amplitude Spectral Area (AMSA technique. Methods A total of 90 pre-countershock ECG signals were analyzed form an accessible preshosptial cardiac arrest database. A unified predictive model, based on signal processing and machine learning, was developed with time-series and dual-tree complex wavelet transform features. Upon selection of correlated variables, a parametrically optimized support vector machine (SVM model was trained for predicting outcomes on the test sets. Training and testing was performed with nested 10-fold cross validation and 6–10 features for each test fold. Results The integrative model performs real-time, short-term (7.8 second analysis of the Electrocardiogram (ECG. For a total of 90 signals, 34 successful and 56 unsuccessful defibrillations were classified with an average Accuracy and Receiver Operator Characteristic (ROC Area Under the Curve (AUC of 82.2% and 85%, respectively. Incorporation of the end-tidal carbon dioxide signal boosted Accuracy and ROC AUC to 83.3% and 93.8%, respectively, for a smaller dataset containing 48 signals. VF analysis using AMSA resulted in accuracy and ROC AUC of 64

  15. The role of learning-related dopamine signals in addiction vulnerability.

    Science.gov (United States)

    Huys, Quentin J M; Tobler, Philippe N; Hasler, Gregor; Flagel, Shelly B

    2014-01-01

    Dopaminergic signals play a mathematically precise role in reward-related learning, and variations in dopaminergic signaling have been implicated in vulnerability to addiction. Here, we provide a detailed overview of the relationship between theoretical, mathematical, and experimental accounts of phasic dopamine signaling, with implications for the role of learning-related dopamine signaling in addiction and related disorders. We describe the theoretical and behavioral characteristics of model-free learning based on errors in the prediction of reward, including step-by-step explanations of the underlying equations. We then use recent insights from an animal model that highlights individual variation in learning during a Pavlovian conditioning paradigm to describe overlapping aspects of incentive salience attribution and model-free learning. We argue that this provides a computationally coherent account of some features of addiction. © 2014 Elsevier B.V. All rights reserved.

  16. Students’ development in the learning process

    Directory of Open Access Journals (Sweden)

    Vladimir D. Shadrikov

    2012-01-01

    Full Text Available A system genetics approach has been employed to study students’ mental development.Ability development is considered in terms of mastering of intellectualoperations. The study endeavors to identify the components of certain abilitiesconsciously acquired by a student in the process of learning. The study was arrangedin two directions: the teaching of students to master intellectual operationsand use them in their work with training materials, and psychological testingof control and experimental student groups before and after training tests todiagnose the level of intellectual development. The study involved teachers andstudents of primary and secondary school.

  17. Performance assessment in algebra learning process

    Science.gov (United States)

    Lestariani, Ida; Sujadi, Imam; Pramudya, Ikrar

    2017-12-01

    The purpose of research to describe the implementation of performance assessment on algebra learning process. The subject in this research is math educator of SMAN 1 Ngawi class X. This research includes descriptive qualitative research type. Techniques of data collecting are done by observation method, interview, and documentation. Data analysis technique is done by data reduction, data presentation, and conclusion. The results showed any indication that the steps taken by the educator in applying the performance assessment are 1) preparing individual worksheets and group worksheets, 2) preparing rubric assessments for independent worksheets and groups and 3) making performance assessments rubric to learners’ performance results with individual or groups task.

  18. Bacterial Biofilm Control by Perturbation of Bacterial Signaling Processes

    Directory of Open Access Journals (Sweden)

    Tim Holm Jakobsen

    2017-09-01

    Full Text Available The development of effective strategies to combat biofilm infections by means of either mechanical or chemical approaches could dramatically change today’s treatment procedures for the benefit of thousands of patients. Remarkably, considering the increased focus on biofilms in general, there has still not been invented and/or developed any simple, efficient and reliable methods with which to “chemically” eradicate biofilm infections. This underlines the resilience of infective agents present as biofilms and it further emphasizes the insufficiency of today’s approaches used to combat chronic infections. A potential method for biofilm dismantling is chemical interception of regulatory processes that are specifically involved in the biofilm mode of life. In particular, bacterial cell to cell signaling called “Quorum Sensing” together with intracellular signaling by bis-(3′-5′-cyclic-dimeric guanosine monophosphate (cyclic-di-GMP have gained a lot of attention over the last two decades. More recently, regulatory processes governed by two component regulatory systems and small non-coding RNAs have been increasingly investigated. Here, we review novel findings and potentials of using small molecules to target and modulate these regulatory processes in the bacterium Pseudomonas aeruginosa to decrease its pathogenic potential.

  19. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

    Science.gov (United States)

    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  20. Use of fuzzy logic in signal processing and validation

    International Nuclear Information System (INIS)

    Heger, A.S.; Alang-Rashid, N.K.; Holbert, K.E.

    1993-01-01

    The advent of fuzzy logic technology has afforded another opportunity to reexamine the signal processing and validation process (SPV). The features offered by fuzzy logic can lend themselves to a more reliable and perhaps fault-tolerant approach to SPV. This is particularly attractive to complex system operations, where optimal control for safe operation depends on reliable input data. The reason for the use of fuzzy logic as the tool for SPV is its ability to transform information from the linguistic domain to a mathematical domain for processing and then transformation of its result back into the linguistic domain for presentation. To ensure the safe and optimal operation of a nuclear plant, for example, reliable and valid data must be available to the human and computer operators. Based on these input data, the operators determine the current state of the power plant and project corrective actions for future states. This determination is based on available data and the conceptual and mathematical models for the plant. A fault-tolerant SPV based on fuzzy logic can help the operators meet the objective of effective, efficient, and safe operation of the nuclear power plant. The ultimate product of this project will be a code that will assist plant operators in making informed decisions under uncertain conditions when conflicting signals may be present

  1. 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...

  2. Digital signal processing in power electronics control circuits

    CERN Document Server

    Sozanski, Krzysztof

    2013-01-01

    Many digital control circuits in current literature are described using analog transmittance. This may not always be acceptable, especially if the sampling frequency and power transistor switching frequencies are close to the band of interest. Therefore, a digital circuit is considered as a digital controller rather than an analog circuit. This helps to avoid errors and instability in high frequency components. Digital Signal Processing in Power Electronics Control Circuits covers problems concerning the design and realization of digital control algorithms for power electronics circuits using

  3. Modeling, estimation and optimal filtration in signal processing

    CERN Document Server

    Najim, Mohamed

    2010-01-01

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

  4. Diffraction and signal processing experiments with a liquid crystal microdisplay

    International Nuclear Information System (INIS)

    MartInez, Jose Luis; Moreno, Ignacio; Ahouzi, Esmail

    2006-01-01

    In this work, we show some diffraction experiments performed with a liquid crystal display (LCD) that shows how useful this device can be to teach and experience diffraction optics and signal processing experiments. The LCD acts as a programmable pixelated diffractive mask. The Fourier spectrum of the image displayed in the LCD is visualized through a simple free propagation diffraction experiment. This optical system allows easy testing of different diffractive elements. As a demonstration we include experimental results with well-known diffractive elements like diffraction gratings or Fresnel lenses, and with more complicated elements like computer-generated holograms

  5. Diffraction and signal processing experiments with a liquid crystal microdisplay

    Energy Technology Data Exchange (ETDEWEB)

    MartInez, Jose Luis [Departamento de Ciencia y TecnologIa de Materiales, Universidad Miguel Hernandez de Elche, Alicante (Spain); Moreno, Ignacio [Departamento de Ciencia y TecnologIa de Materiales, Universidad Miguel Hernandez de Elche, Alicante (Spain); Ahouzi, Esmail [Institut National des Postes et Telecomunications (INTP), Madinat Al Irfane, Rabat (Morocco)

    2006-09-01

    In this work, we show some diffraction experiments performed with a liquid crystal display (LCD) that shows how useful this device can be to teach and experience diffraction optics and signal processing experiments. The LCD acts as a programmable pixelated diffractive mask. The Fourier spectrum of the image displayed in the LCD is visualized through a simple free propagation diffraction experiment. This optical system allows easy testing of different diffractive elements. As a demonstration we include experimental results with well-known diffractive elements like diffraction gratings or Fresnel lenses, and with more complicated elements like computer-generated holograms.

  6. 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.

  7. Music Signal Processing Using Vector Product Neural Networks

    Science.gov (United States)

    Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

    2017-05-01

    We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

  8. Oversampling of digitized images. [effects on interpolation in signal processing

    Science.gov (United States)

    Fischel, D.

    1976-01-01

    Oversampling is defined as sampling with a device whose characteristic width is greater than the interval between samples. This paper shows why oversampling should be avoided and discusses the limitations in data processing if circumstances dictate that oversampling cannot be circumvented. Principally, oversampling should not be used to provide interpolating data points. Rather, the time spent oversampling should be used to obtain more signal with less relative error, and the Sampling Theorem should be employed to provide any desired interpolated values. The concepts are applicable to single-element and multielement detectors.

  9. With you or against you: social orientation dependent learning signals guide actions made for others.

    Science.gov (United States)

    Christopoulos, George I; King-Casas, Brooks

    2015-01-01

    In social environments, it is crucial that decision-makers take account of the impact of their actions not only for oneself, but also on other social agents. Previous work has identified neural signals in the striatum encoding value-based prediction errors for outcomes to oneself; also, recent work suggests that neural activity in prefrontal cortex may similarly encode value-based prediction errors related to outcomes to others. However, prior work also indicates that social valuations are not isomorphic, with social value orientations of decision-makers ranging on a cooperative to competitive continuum; this variation has not been examined within social learning environments. Here, we combine a computational model of learning with functional neuroimaging to examine how individual differences in orientation impact neural mechanisms underlying 'other-value' learning. Across four experimental conditions, reinforcement learning signals for other-value were identified in medial prefrontal cortex, and were distinct from self-value learning signals identified in striatum. Critically, the magnitude and direction of the other-value learning signal depended strongly on an individual's cooperative or competitive orientation toward others. These data indicate that social decisions are guided by a social orientation-dependent learning system that is computationally similar but anatomically distinct from self-value learning. The sensitivity of the medial prefrontal learning signal to social preferences suggests a mechanism linking such preferences to biases in social actions and highlights the importance of incorporating heterogeneous social predispositions in neurocomputational models of social behavior. Published by Elsevier Inc.

  10. Social signal processing for studying parent-infant interaction

    Directory of Open Access Journals (Sweden)

    Marie eAvril

    2014-12-01

    Full Text Available Studying early interactions is a core issue of infant development and psychopathology. Automatic social signal processing theoretically offers the possibility to extract and analyse communication by taking an integrative perspective, considering the multimodal nature and dynamics of behaviours (including synchrony. This paper proposes an explorative method to acquire and extract relevant social signals from a naturalistic early parent-infant interaction. An experimental setup is proposed based on both clinical and technical requirements. We extracted various cues from body postures and speech productions of partners using the IMI2S (Interaction, Multimodal Integration, and Social Signal Framework. Preliminary clinical and computational results are reported for two dyads (one pathological in a situation of severe emotional neglect and one normal control as an illustration of our cross-disciplinary protocol. The results from both clinical and computational analyses highlight similar differences: the pathological dyad shows dyssynchronic interaction led by the infant whereas the control dyad shows synchronic interaction and a smooth interactive dialog. The results suggest that the current method might be promising for future studies.

  11. E-learning process maturity level: a conceptual framework

    Science.gov (United States)

    Rahmah, A.; Santoso, H. B.; Hasibuan, Z. A.

    2018-03-01

    ICT advancement is a sure thing with the impact influencing many domains, including learning in both formal and informal situations. It leads to a new mindset that we should not only utilize the given ICT to support the learning process, but also improve it gradually involving a lot of factors. These phenomenon is called e-learning process evolution. Accordingly, this study attempts to explore maturity level concept to provide the improvement direction gradually and progression monitoring for the individual e-learning process. Extensive literature review, observation, and forming constructs are conducted to develop a conceptual framework for e-learning process maturity level. The conceptual framework consists of learner, e-learning process, continuous improvement, evolution of e-learning process, technology, and learning objectives. Whilst, evolution of e-learning process depicted as current versus expected conditions of e-learning process maturity level. The study concludes that from the e-learning process maturity level conceptual framework, it may guide the evolution roadmap for e-learning process, accelerate the evolution, and decrease the negative impact of ICT. The conceptual framework will be verified and tested in the future study.

  12. 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

  13. Real-time Color Codes for Assessing Learning Process

    OpenAIRE

    Dzelzkalēja, L; Kapenieks, J

    2016-01-01

    Effective assessment is an important way for improving the learning process. There are existing guidelines for assessing the learning process, but they lack holistic digital knowledge society considerations. In this paper the authors propose a method for real-time evaluation of students’ learning process and, consequently, for quality evaluation of teaching materials both in the classroom and in the distance learning environment. The main idea of the proposed Color code method (CCM) is to use...

  14. Supporting the processes of teaching and learning

    DEFF Research Database (Denmark)

    Bundsgaard, Jeppe

    2010-01-01

    an equally widespread process at the meso-level is a workflow called Lecture-Recitation-Seatwork-Plenary session (abbreviated as LeReSeP). These two structures are discussed and analysed, and they are criticised on a theoretical basis for being too teacher-centred, and leaving insufficient room....... A course consists of several modules integrating several workflows, each of which comprises several interaction sequences. Two common processes are identified. At the micro-level, the most common interaction sequence is (the teacher's) Initiation- (student's) Response- (teacher's) Feedback (IRF) while...... for developing more complex competences in students. A number of alternative interaction sequences and workflows are described and discussed. These alternatives all have their advantages, but they are evaluated as more complex, troublesome, and inconvenient to work with. Teaching and learning materials support...

  15. Channel modeling, signal processing and coding for perpendicular magnetic recording

    Science.gov (United States)

    Wu, Zheng

    With the increasing areal density in magnetic recording systems, perpendicular recording has replaced longitudinal recording to overcome the superparamagnetic limit. Studies on perpendicular recording channels including aspects of channel modeling, signal processing and coding techniques are presented in this dissertation. To optimize a high density perpendicular magnetic recording system, one needs to know the tradeoffs between various components of the system including the read/write transducers, the magnetic medium, and the read channel. We extend the work by Chaichanavong on the parameter optimization for systems via design curves. Different signal processing and coding techniques are studied. Information-theoretic tools are utilized to determine the acceptable region for the channel parameters when optimal detection and linear coding techniques are used. Our results show that a considerable gain can be achieved by the optimal detection and coding techniques. The read-write process in perpendicular magnetic recording channels includes a number of nonlinear effects. Nonlinear transition shift (NLTS) is one of them. The signal distortion induced by NLTS can be reduced by write precompensation during data recording. We numerically evaluate the effect of NLTS on the read-back signal and examine the effectiveness of several write precompensation schemes in combating NLTS in a channel characterized by both transition jitter noise and additive white Gaussian electronics noise. We also present an analytical method to estimate the bit-error-rate and use it to help determine the optimal write precompensation values in multi-level precompensation schemes. We propose a mean-adjusted pattern-dependent noise predictive (PDNP) detection algorithm for use on the channel with NLTS. We show that this detector can offer significant improvements in bit-error-rate (BER) compared to conventional Viterbi and PDNP detectors. Moreover, the system performance can be further improved by

  16. Photonic Crystal Nanocavity Devices for Nonlinear Signal Processing

    DEFF Research Database (Denmark)

    Yu, Yi

    , membranization of InP/InGaAs structure and wet etching. Experimental investigation of the switching dynamics of InP photonic crystal nanocavity structures are carried out using short-pulse homodyne pump-probe techniques, both in the linear and nonlinear region where the cavity is perturbed by a relatively small......This thesis deals with the investigation of InP material based photonic crystal cavity membrane structures, both experimentally and theoretically. The work emphasizes on the understanding of the physics underlying the structures’ nonlinear properties and their applications for all-optical signal...... processing. Based on the previous fabrication recipe developed in our III-V platform, several processing techniques are developed and optimized for the fabrication of InP photonic crystal membrane structures. Several key issues are identified to ensure a good device quality such as air hole size control...

  17. Mathematical model with autoregressive process for electrocardiogram signals

    Science.gov (United States)

    Evaristo, Ronaldo M.; Batista, Antonio M.; Viana, Ricardo L.; Iarosz, Kelly C.; Szezech, José D., Jr.; Godoy, Moacir F. de

    2018-04-01

    The cardiovascular system is composed of the heart, blood and blood vessels. Regarding the heart, cardiac conditions are determined by the electrocardiogram, that is a noninvasive medical procedure. In this work, we propose autoregressive process in a mathematical model based on coupled differential equations in order to obtain the tachograms and the electrocardiogram signals of young adults with normal heartbeats. Our results are compared with experimental tachogram by means of Poincaré plot and dentrended fluctuation analysis. We verify that the results from the model with autoregressive process show good agreement with experimental measures from tachogram generated by electrical activity of the heartbeat. With the tachogram we build the electrocardiogram by means of coupled differential equations.

  18. Influence of signal processing strategy in auditory abilities.

    Science.gov (United States)

    Melo, Tatiana Mendes de; Bevilacqua, Maria Cecília; Costa, Orozimbo Alves; Moret, Adriane Lima Mortari

    2013-01-01

    The signal processing strategy is a parameter that may influence the auditory performance of cochlear implant and is important to optimize this parameter to provide better speech perception, especially in difficult listening situations. To evaluate the individual's auditory performance using two different signal processing strategy. Prospective study with 11 prelingually deafened children with open-set speech recognition. A within-subjects design was used to compare performance with standard HiRes and HiRes 120 in three different moments. During test sessions, subject's performance was evaluated by warble-tone sound-field thresholds, speech perception evaluation, in quiet and in noise. In the silence, children S1, S4, S5, S7 showed better performance with the HiRes 120 strategy and children S2, S9, S11 showed better performance with the HiRes strategy. In the noise was also observed that some children performed better using the HiRes 120 strategy and other with HiRes. Not all children presented the same pattern of response to the different strategies used in this study, which reinforces the need to look at optimizing cochlear implant clinical programming.

  19. Acoustic monitoring of rotating machine by advanced signal processing technology

    International Nuclear Information System (INIS)

    Kanemoto, Shigeru

    2010-01-01

    The acoustic data remotely measured by hand held type microphones are investigated for monitoring and diagnosing the rotational machine integrity in nuclear power plants. The plant operator's patrol monitoring is one of the important activities for condition monitoring. However, remotely measured sound has some difficulties to be considered for precise diagnosis or quantitative judgment of rotating machine anomaly, since the measurement sensitivity is different in each measurement, and also, the sensitivity deteriorates in comparison with an attached type sensor. Hence, in the present study, several advanced signal processing methods are examined and compared in order to find optimum anomaly monitoring technology from the viewpoints of both sensitivity and robustness of performance. The dimension of pre-processed signal feature patterns are reduced into two-dimensional space for the visualization by using the standard principal component analysis (PCA) or the kernel based PCA. Then, the normal state is classified by using probabilistic neural network (PNN) or support vector data description (SVDD). By using the mockup test facility of rotating machine, it is shown that the appropriate combination of the above algorithms gives sensitive and robust anomaly monitoring performance. (author)

  20. Understanding the Learning Process in SMEs

    Science.gov (United States)

    Carr, James; Gannon-Leary, Pat

    2007-01-01

    A major obstacle to the diffusion of management development learning technologies from Higher Education Institutions to Small and Medium-sized Enterprises (SMEs) is a lack of understanding about how SME learners learn. This article examines the nature of learning in SMEs and considers the incidence of informal support for informal learning.…

  1. Real-time numerical processing for HPGE detectors signals

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  2. Signal validation with control-room information-processing computers

    International Nuclear Information System (INIS)

    Belblidia, L.A.; Carlson, R.W.; Russell, J.L. Jr.

    1985-01-01

    One of the 'lessons learned' from the Three Mile Island accident focuses upon the need for a validated source of plant-status information in the control room. The utilization of computer-generated graphics to display the readings of the major plant instrumentation has introduced the capability of validating signals prior to their presentation to the reactor operations staff. The current operations philosophies allow the operator a quick look at the gauges to form an impression of the fraction of full scale as the basis for knowledge of the current plant conditions. After the introduction of a computer-based information-display system such as the Safety Parameter Display System (SPDS), operational decisions can be based upon precise knowledge of the parameters that define the operation of the reactor and auxiliary systems. The principal impact of this system on the operator will be to remove the continuing concern for the validity of the instruments which provide the information that governs the operator's decisions. (author)

  3. 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....

  4. 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.

  5. Machine Learning for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

    DEFF Research Database (Denmark)

    Wass, J.; Thrane, Jakob; Piels, Molly

    2016-01-01

    Supervised machine learning methods are applied and demonstrated experimentally for inband OSNR estimation and modulation format classification in optical communication systems. The proposed methods accurately evaluate coherent signals up to 64QAM using only intensity information....

  6. Opponent appetitive-aversive neural processes underlie predictive learning of pain relief.

    Science.gov (United States)

    Seymour, Ben; O'Doherty, John P; Koltzenburg, Martin; Wiech, Katja; Frackowiak, Richard; Friston, Karl; Dolan, Raymond

    2005-09-01

    Termination of a painful or unpleasant event can be rewarding. However, whether the brain treats relief in a similar way as it treats natural reward is unclear, and the neural processes that underlie its representation as a motivational goal remain poorly understood. We used fMRI (functional magnetic resonance imaging) to investigate how humans learn to generate expectations of pain relief. Using a pavlovian conditioning procedure, we show that subjects experiencing prolonged experimentally induced pain can be conditioned to predict pain relief. This proceeds in a manner consistent with contemporary reward-learning theory (average reward/loss reinforcement learning), reflected by neural activity in the amygdala and midbrain. Furthermore, these reward-like learning signals are mirrored by opposite aversion-like signals in lateral orbitofrontal cortex and anterior cingulate cortex. This dual coding has parallels to 'opponent process' theories in psychology and promotes a formal account of prediction and expectation during pain.

  7. E-Learning and Further Education: How do Individual Learning Paths support Personal Learning Processes

    Directory of Open Access Journals (Sweden)

    Bertil Haack

    2010-02-01

    Full Text Available The MOPEM project includes two fixed scenarios that have been defined to convey the idea of "learning paths". Our aim in this paper is to demonstrate the contexts and conditions for flexible learning paths that can be tailored to meet individual needs. The concept of this kind of specialised path is to enable learners to individualise the learning process and to adjust it to their personal needs. We will outline the background and pro- vide examples to explain the concept of learning stations which we use in our four courses: Online Marketing, CRM Systems, Business Communications and Event Marketing. This idea of "freely" combining subject matter naturally leads to the ques- tion of multi-applicability for the learning blocks in various educational contexts. The answers to this question are interest- ing not only in terms of the feasibility of learning paths from a content and didactic point of view, but also with regard to the economic viability of E-Learning or Blended Learning Systems, which ultimately require technical implementation. In addition we will present some first thoughts on the design of a prototype "Content Pool". It would, however, only make sense to develop and implement this within the scope of a follow-up project.

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

    Directory of Open Access Journals (Sweden)

    Ali Ibrahim

    2017-03-01

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

  9. Loss of Signal, Aeromedical Lessons Learned for the STS-I07 Columbia Space Shuttle Mishap

    Science.gov (United States)

    Patlach, Robert; Stepaniak, Philip C.; Lane, Helen W.

    2014-01-01

    Loss of Signal, a NASA publication to be available in May 2014, presents the aeromedical lessons learned from the Columbia accident that will enhance crew safety and survival on human space flight missions. These lessons were presented to limited audiences at three separate Aerospace Medical Association (AsMA) conferences: in 2004 in Anchorage, Alaska, on the causes of the accident; in 2005 in Kansas City, Missouri, on the response, recovery, and identification aspects of the investigation; and in 2011, again in Anchorage, Alaska, on future implications for human space flight. As we embark on the development of new spacefaring vehicles through both government and commercial efforts, the NASA Johnson Space Center Human Health and Performance Directorate is continuing to make this information available to a wider audience engaged in the design and development of future space vehicles. Loss of Signal summarizes and consolidates the aeromedical impacts of the Columbia mishap process-the response, recovery, identification, investigative studies, medical and legal forensic analysis, and future preparation that are needed to respond to spacecraft mishaps. The goals of this book are to provide an account of the aeromedical aspects of the Columbia accident and the investigation that followed, and to encourage aerospace medical specialists to continue to capture information, learn from it, and improve procedures and spacecraft designs for the safety of future crews.

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

    Directory of Open Access Journals (Sweden)

    Adirelle C. Santana

    2012-03-01

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

  11. Validity and Reliability of Revised Inventory of Learning Processes.

    Science.gov (United States)

    Gadzella, B. M.; And Others

    The Inventory of Learning Processes (ILP) was developed by Schmeck, Ribich, and Ramanaiah in 1977 as a self-report inventory to assess learning style through a behavioral-oriented approach. The ILP was revised by Schmeck in 1983. The Revised ILP contains six scales: (1) Deep Processing; (2) Elaborative Processing; (3) Shallow Processing; (4)…

  12. The Promise of Process. Learning through Enterprise in Higher Education

    DEFF Research Database (Denmark)

    Frederiksen, Signe Hedeboe

    Entrepreneurial process increasingly attracts attention as an opportunity to learn in higher education. Students learn “through” enterprise, when they actively engage in an entrepreneurial process while reflecting on their actions and experiences. In this qualitative field study, I investigate how...... postgraduate students pursued opportunities to learn in a process-driven entrepreneurship module. Drawing on situated learning theory, I find that students tried to access learning opportunities through a constant dynamic of participation which involved contradictory participatory stances. The learning through...... paradigm in enterprise education imposes conditions on the learning environment and involves images of a particular learner, who is able to take advantage of this learning opportunity. The findings indicate a contradictory process of becoming a legitimate entrepreneurial learner which is more uncertain...

  13. Evaluation of signal processing for boiling noise detection

    International Nuclear Information System (INIS)

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

    1989-01-01

    As part of the co-ordinated research programme on the detection of sodium boiling some further analysis has been performed on the data from the test loop in Karlsruhe and some preliminary analysis of the data from the BOR 60 experiment. The work on the Karlsruhe data is concerned with the search for a reliable method by which the quality of signal processing strategies may be compared. The results show that the three novel methods previously reported are all markedly superior to the mean square method which is used as a benchmark. The three novel methods are nth order differentiation in the frequency domain, the mean square prediction based on nth order conditional expectation and the nth order probability density function. A preliminary analysis on the data from the BOR 60 reactor shows that 4th order differentiation is adequate for the detection of signals derived from a pressure transducer and that the map of spurious trip probability (S) and the probability of missing an event (M) is consistent with the theoretical model proposed herein, and the suggested procedures for evaluating the quality of detection strategies. (author). 15 figs, 1 tab

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

    Science.gov (United States)

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

    1986-01-01

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

  15. Optimization of signal processing algorithm for digital beam position monitor

    International Nuclear Information System (INIS)

    Lai Longwei; Yi Xing; Leng Yongbin; Yan Yingbing; Chen Zhichu

    2013-01-01

    Based on turn-by-turn (TBT) signal processing, the paper emphasizes on the optimization of system timing and implementation of digital automatic gain control, slow application (SA) modules. Beam position including TBT, fast application (FA) and SA data can be acquired. On-line evaluation on Shanghai Synchrotron Radiation Facility (SSRF) shows that the processor is able to get the multi-rate position data which contain true beam movements. When the storage ring is 174 mA and 500 bunches filled, the resolutions of TBT data, FA data and SA data achieve 0.84, 0.44 and 0.23 μm respectively. The above results prove that the design could meet the performance requirements. (authors)

  16. Signal processing and control challenges for smart vehicles

    Science.gov (United States)

    Zhang, Hui; Braun, Simon G.

    2017-03-01

    Smart phones have changed not only the mobile phone market but also our society during the past few years. Could the next potential intelligent device may be the vehicle? Judging by the visibility, in all media, of the numerous attempts to develop autonomous vehicles, this is certainly one of the logical outcomes. Smart vehicles would be equipped with an advanced operating system such that the vehicles could communicate with others, optimize the operation to reduce fuel consumption and emissions, enhance safety, or even become self-driving. These combined new features of vehicles require instrumentation and hardware developments, fast signal processing/fusion, decision making and online optimization. Meanwhile, the inevitable increasing system complexity would certainly challenges the control unit design.

  17. Mathematical modeling and signal processing in speech and hearing sciences

    CERN Document Server

    Xin, Jack

    2014-01-01

    The aim of the book is to give an accessible introduction of mathematical models and signal processing methods in speech and hearing sciences for senior undergraduate and beginning graduate students with basic knowledge of linear algebra, differential equations, numerical analysis, and probability. Speech and hearing sciences are fundamental to numerous technological advances of the digital world in the past decade, from music compression in MP3 to digital hearing aids, from network based voice enabled services to speech interaction with mobile phones. Mathematics and computation are intimately related to these leaps and bounds. On the other hand, speech and hearing are strongly interdisciplinary areas where dissimilar scientific and engineering publications and approaches often coexist and make it difficult for newcomers to enter.

  18. A Signal Processing Method to Explore Similarity in Protein Flexibility

    Directory of Open Access Journals (Sweden)

    Simina Vasilache

    2010-01-01

    Full Text Available Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods.

  19. High-resolution imaging methods in array signal processing

    DEFF Research Database (Denmark)

    Xenaki, Angeliki

    in active sonar signal processing for detection and imaging of submerged oil contamination in sea water from a deep-water oil leak. The submerged oil _eld is modeled as a uid medium exhibiting spatial perturbations in the acoustic parameters from their mean ambient values which cause weak scattering...... of the incident acoustic energy. A highfrequency active sonar is selected to insonify the medium and receive the backscattered waves. High-frequency acoustic methods can both overcome the optical opacity of water (unlike methods based on electromagnetic waves) and resolve the small-scale structure...... of the submerged oil field (unlike low-frequency acoustic methods). The study shows that high-frequency acoustic methods are suitable not only for large-scale localization of the oil contamination in the water column but also for statistical characterization of the submerged oil field through inference...

  20. Modeling and processing of laser Doppler reactive hyperaemia signals

    Science.gov (United States)

    Humeau, Anne; Saumet, Jean-Louis; L'Huiller, Jean-Pierre

    2003-07-01

    Laser Doppler flowmetry is a non-invasive method used in the medical domain to monitor the microvascular blood cell perfusion through tissue. Most commercial laser Doppler flowmeters use an algorithm calculating the first moment of the power spectral density to give the perfusion value. Many clinical applications measure the perfusion after a vascular provocation such as a vascular occlusion. The response obtained is then called reactive hyperaemia. Target pathologies include diabetes, hypertension and peripheral arterial occlusive diseases. In order to have a deeper knowledge on reactive hyperaemia acquired by the laser Doppler technique, the present work first proposes two models (one analytical and one numerical) of the observed phenomenon. Then, a study on the multiple scattering between photons and red blood cells occurring during reactive hyperaemia is carried out. Finally, a signal processing that improves the diagnosis of peripheral arterial occlusive diseases is presented.

  1. 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.

  2. Receivers for processing electron beam pick-up electrode signals

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    There are several methods of determining the transverse position of the electron beam, based upon sensing either the electric field, the magnetic field, or both. At the NSLS the transverse beam position monitors each consist of a set of four circular electrodes. There are 48 sets of pick-up electrodes in the X-ray ring and 24 in the VUV storage ring for determining the electron orbit, and a few extra sets installed for specialized purposes. When the beam passes between the four electrodes, charge is induced on each electrode, the amount depending upon the distance of the beam from that electrode. If V a , V b , V c and V d given by a difference between pairs of electrodes normalized for variations in beam current by dividing by the sum of electrode voltages. The method of processing these signals depends upon their time structure. The electrons circulating around the vacuum chamber are concentrated in short bunches within stability buckets produced by the accelerating voltage in the RF cavities. The charges induced on the pickup electrodes then are narrow pulses, a fraction of a nanosecond long, and would result in a monopolar voltage pulses if it were not for the impedance of the cable connecting the electrode to the processing apparatus. The capacitance between each electrode and the chamber wall is only a few picofarads and is effectively in parallel with the cable impedance (50 ohms). Thus an appreciable amount of the charge flows off the electrode while the bunch is between the electrodes, resulting in potential of opposite sign as the bunch is leaving the vicinity of the electrode. The resulting signal consists of a series of bipolar pulses, each of less than one nanosecond duration

  3. Learning during processing Word learning doesn’t wait for word recognition to finish

    Science.gov (United States)

    Apfelbaum, Keith S.; McMurray, Bob

    2017-01-01

    Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning may incorporate spurious, partial information. For example, during word recognition, words take time to be identified, and competing words are often active in parallel. If learning proceeds before this competition resolves, representations may be influenced by the preliminary activations present at the time of learning. In three experiments using word learning as a model domain, we provide evidence that learning reflects the ongoing dynamics of auditory and visual processing during a learning event. These results show that learning can occur before stimulus recognition processes are complete; learning does not wait for ongoing perceptual processing to complete. PMID:27471082

  4. Cardiac Concomitants of Feedback and Prediction Error Processing in Reinforcement Learning

    Science.gov (United States)

    Kastner, Lucas; Kube, Jana; Villringer, Arno; Neumann, Jane

    2017-01-01

    Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a differential impact of reward and punishment on successful feedback-based learning. On the autonomic level, learning and feedback processing were closely mirrored by phasic cardiac responses on a trial-by-trial basis: (1) Negative feedback was accompanied by faster and prolonged heart rate deceleration compared to positive feedback. (2) Cardiac responses shifted from feedback presentation at the beginning of learning to stimulus presentation later on. (3) Most importantly, the strength of phasic cardiac responses to the presentation of feedback correlated with the strength of prediction error signals that alert the learner to the necessity for behavioral adaptation. Considering participants' weight status and gender revealed obesity-related deficits in learning to avoid negative consequences and less consistent behavioral adaptation in women compared to men. In sum, our results provide strong new evidence for the notion that during learning phasic cardiac responses reflect an internal value and feedback monitoring system that is sensitive to the violation of performance-based expectations. Moreover, inter-individual differences in weight status and gender may affect both behavioral and autonomic responses in reinforcement-based learning. PMID:29163004

  5. Cardiac Concomitants of Feedback and Prediction Error Processing in Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Lucas Kastner

    2017-10-01

    Full Text Available Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a differential impact of reward and punishment on successful feedback-based learning. On the autonomic level, learning and feedback processing were closely mirrored by phasic cardiac responses on a trial-by-trial basis: (1 Negative feedback was accompanied by faster and prolonged heart rate deceleration compared to positive feedback. (2 Cardiac responses shifted from feedback presentation at the beginning of learning to stimulus presentation later on. (3 Most importantly, the strength of phasic cardiac responses to the presentation of feedback correlated with the strength of prediction error signals that alert the learner to the necessity for behavioral adaptation. Considering participants' weight status and gender revealed obesity-related deficits in learning to avoid negative consequences and less consistent behavioral adaptation in women compared to men. In sum, our results provide strong new evidence for the notion that during learning phasic cardiac responses reflect an internal value and feedback monitoring system that is sensitive to the violation of performance-based expectations. Moreover, inter-individual differences in weight status and gender may affect both behavioral and autonomic responses in reinforcement-based learning.

  6. Chronically Increased G[subscript s][alpha] Signaling Disrupts Associative and Spatial Learning

    Science.gov (United States)

    Bourtchouladze, Rusiko; Patterson, Susan L.; Kelly, Michele P.; Kreibich, Arati; Kandel, Eric R.; Abel, Ted

    2006-01-01

    The cAMP/PKA pathway plays a critical role in learning and memory systems in animals ranging from mice to "Drosophila" to "Aplysia." Studies of olfactory learning in "Drosophila" suggest that altered expression of either positive or negative regulators of the cAMP/PKA signaling pathway beyond a certain optimum range may be deleterious. Here we…

  7. Supporting Multimedia Learning with Visual Signalling and Animated Pedagogical Agent: Moderating Effects of Prior Knowledge

    Science.gov (United States)

    Johnson, A. M.; Ozogul, G.; Reisslein, M.

    2015-01-01

    An experiment examined the effects of visual signalling to relevant information in multiple external representations and the visual presence of an animated pedagogical agent (APA). Students learned electric circuit analysis using a computer-based learning environment that included Cartesian graphs, equations and electric circuit diagrams. The…

  8. Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

    Science.gov (United States)

    Barua, Shaibal; Begum, Shahina; Ahmed, Mobyen Uddin

    2015-01-01

    Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Diagnosis and treatment of patients based on manual analysis of these sensor data are difficult and time consuming. Therefore, development of Knowledge-based systems to support clinicians in decision-making is important. However, it is necessary to perform experimental work to compare performances of different machine learning methods to help to select appropriate method for a specific characteristic of data sets. This paper compares classification performance of three popular machine learning methods i.e., case-based reasoning, neutral networks and support vector machine to diagnose stress of vehicle drivers using finger temperature and heart rate variability. The experimental results show that case-based reasoning outperforms other two methods in terms of classification accuracy. Case-based reasoning has achieved 80% and 86% accuracy to classify stress using finger temperature and heart rate variability. On contrary, both neural network and support vector machine have achieved less than 80% accuracy by using both physiological signals.

  9. 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.

  10. 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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1998-02-01

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

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

    International Nuclear Information System (INIS)

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

    1998-02-01

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

  13. Thickness measurement by using cepstrum ultrasonic signal processing

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  14. Linear circuits, systems and signal processing: theory and application

    International Nuclear Information System (INIS)

    Byrnes, C.I.; Saeks, R.E.; Martin, C.F.

    1988-01-01

    In part because of its universal role as a first approximation of more complicated behaviour and in part because of the depth and breadth of its principle paradigms, the study of linear systems continues to play a central role in control theory and its applications. Enhancing more traditional applications to aerospace and electronics, application areas such as econometrics, finance, and speech and signal processing have contributed to a renaissance in areas such as realization theory and classical automatic feedback control. Thus, the last few years have witnessed a remarkable research effort expended in understanding both new algorithms and new paradigms for modeling and realization of linear processes and in the analysis and design of robust control strategies. The papers in this volume reflect these trends in both the theory and applications of linear systems and were selected from the invited and contributed papers presented at the 8th International Symposium on the Mathematical Theory of Networks and Systems held in Phoenix on June 15-19, 1987

  15. 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.

  16. Science Integrating Learning Objectives: A Cooperative Learning Group Process

    Science.gov (United States)

    Spindler, Matt

    2015-01-01

    The integration of agricultural and science curricular content that capitalizes on natural and inherent connections represents a challenge for secondary agricultural educators. The purpose of this case study was to create information about the employment of Cooperative Learning Groups (CLG) to enhance the science integrating learning objectives…

  17. Altered neural reward and loss processing and prediction error signalling in depression

    Science.gov (United States)

    Ubl, Bettina; Kuehner, Christine; Kirsch, Peter; Ruttorf, Michaela

    2015-01-01

    Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. When compared with healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression. PMID:25567763

  18. An integrated domain specific language for post-processing and visualizing electrophysiological signals in Java.

    Science.gov (United States)

    Strasser, T; Peters, T; Jagle, H; Zrenner, E; Wilke, R

    2010-01-01

    Electrophysiology of vision - especially the electroretinogram (ERG) - is used as a non-invasive way for functional testing of the visual system. The ERG is a combined electrical response generated by neural and non-neuronal cells in the retina in response to light stimulation. This response can be recorded and used for diagnosis of numerous disorders. For both clinical practice and clinical trials it is important to process those signals in an accurate and fast way and to provide the results as structured, consistent reports. Therefore, we developed a freely available and open-source framework in Java (http://www.eye.uni-tuebingen.de/project/idsI4sigproc). The framework is focused on an easy integration with existing applications. By leveraging well-established software patterns like pipes-and-filters and fluent interfaces as well as by designing the application programming interfaces (API) as an integrated domain specific language (DSL) the overall framework provides a smooth learning curve. Additionally, it already contains several processing methods and visualization features and can be extended easily by implementing the provided interfaces. In this way, not only can new processing methods be added but the framework can also be adopted for other areas of signal processing. This article describes in detail the structure and implementation of the framework and demonstrate its application through the software package used in clinical practice and clinical trials at the University Eye Hospital Tuebingen one of the largest departments in the field of visual electrophysiology in Europe.

  19. Implementation of Process Oriented Guided Inquiry Learning (POGIL) in Engineering

    Science.gov (United States)

    Douglas, Elliot P.; Chiu, Chu-Chuan

    2013-01-01

    This paper describes implementation and testing of an active learning, team-based pedagogical approach to instruction in engineering. This pedagogy has been termed Process Oriented Guided Inquiry Learning (POGIL), and is based upon the learning cycle model. Rather than sitting in traditional lectures, students work in teams to complete worksheets…

  20. Neural Signaling of Food Healthiness Associated with Emotion Processing.

    Science.gov (United States)

    Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B; Siegrist, Michael

    2016-01-01

    The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake.

  1. 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...

  2. Experiential Learning: A Process for Teaching Youth Entrepreneurship

    Directory of Open Access Journals (Sweden)

    Karen Biers

    2006-09-01

    Full Text Available Youth of all ages are indicating an interest in starting a business. However, few classes on business start-up and management are available. Young people who are actively engaged in learning business management concepts also develop life skills such as decision making, communicating, and learning to learn. Studies have shown that youth who are in participatory, entrepreneurship classes develop a positive attitude toward starting a business. This article addresses how the experiential learning model provides an opportunity for youth to develop entrepreneurial skills. The entrepreneurial learning model is a learning process of doing, reflecting, and then applying.

  3. Learning and Motivational Processes When Students Design Curriculum‐Based Digital Learning Games

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2016-01-01

    This design‐based research (DBR) project has developed an overall gamified learning design (big Game) to facilitate the learning process for adult students by inviting them to be their own learning designers through designing digital learning games (small games) in cross‐disciplinary subject...... matters. The DBR project has investigated and experimented with which elements, methods, and processes are important when aiming at creating a cognitive complex (Anderson and Krathwohl, 2001) and motivating learning process within a reusable game‐based learning design. This project took place in a co......, or programming provide a rich context for learning, since the construction of artefacts, in this case learning games, enables reflection and new ways of thinking. The students learned from reflection and interaction with the tools alone as well as in collaboration with peers. After analysing the students...

  4. Learning and Motivational Processes When Students Design Curriculum-Based Digital Learning Games

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2015-01-01

    This design-based research (DBR) project has developed an overall gamified learning design (big Game) to facilitate the learning process for adult students by inviting them to be their own learning designers through designing digital learning games (small games) in cross-disciplinary subject...... matters. The DBR project has investigated and experimented with which elements, methods, and processes are important when aiming at creating a cognitive complex (Anderson and Krathwohl, 2001) and motivating learning process within a reusable game-based learning design. This project took place in a co......, or programming provide a rich context for learning, since the construction of artefacts, in this case learning games, enables reflection and new ways of thinking. The students learned from reflection and interaction with the tools alone as well as in collaboration with peers. After analysing the students...

  5. Bose-Einstein condensates form in heuristics learned by ciliates deciding to signal 'social' commitments.

    Science.gov (United States)

    Clark, Kevin B

    2010-03-01

    Fringe quantum biology theories often adopt the concept of Bose-Einstein condensation when explaining how consciousness, emotion, perception, learning, and reasoning emerge from operations of intact animal nervous systems and other computational media. However, controversial empirical evidence and mathematical formalism concerning decoherence rates of bioprocesses keep these frameworks from satisfactorily accounting for the physical nature of cognitive-like events. This study, inspired by the discovery that preferential attachment rules computed by complex technological networks obey Bose-Einstein statistics, is the first rigorous attempt to examine whether analogues of Bose-Einstein condensation precipitate learned decision making in live biological systems as bioenergetics optimization predicts. By exploiting the ciliate Spirostomum ambiguum's capacity to learn and store behavioral strategies advertising mating availability into heuristics of topologically invariant computational networks, three distinct phases of strategy use were found to map onto statistical distributions described by Bose-Einstein, Fermi-Dirac, and classical Maxwell-Boltzmann behavior. Ciliates that sensitized or habituated signaling patterns to emit brief periods of either deceptive 'harder-to-get' or altruistic 'easier-to-get' serial escape reactions began testing condensed on initially perceived fittest 'courting' solutions. When these ciliates switched from their first strategy choices, Bose-Einstein condensation of strategy use abruptly dissipated into a Maxwell-Boltzmann computational phase no longer dominated by a single fittest strategy. Recursive trial-and-error strategy searches annealed strategy use back into a condensed phase consistent with performance optimization. 'Social' decisions performed by ciliates showing no nonassociative learning were largely governed by Fermi-Dirac statistics, resulting in degenerate distributions of strategy choices. These findings corroborate

  6. Learning design and feedback processes at scale

    DEFF Research Database (Denmark)

    Ringtved, Ulla L.; Miligan, Sandra; Corrin, Linda

    2016-01-01

    Design for teaching in scaled courses is shifting away from replication of the traditional on-campus or online teaching-learning relationship towards exploiting the distinctive characteristic and potentials of that environment to transform both teaching and learning. This involves consideration...... design and would benefit from learning analytics support? What is the character of analytics that can be deployed to help deliver good design of online learning platforms? What are the theoretical and pedagogical bases inherent in different analytics designs? These and other questions will be examined...

  7. Open Integrated Personal Learning Environment: Towards a New Conception of the ICT-Based Learning Processes

    Science.gov (United States)

    Conde, Miguel Ángel; García-Peñalvo, Francisco José; Casany, Marià José; Alier Forment, Marc

    Learning processes are changing related to technological and sociological evolution, taking this in to account, a new learning strategy must be considered. Specifically what is needed is to give an effective step towards the eLearning 2.0 environments consolidation. This must imply the fusion of the advantages of the traditional LMS (Learning Management System) - more formative program control and planning oriented - with the social learning and the flexibility of the web 2.0 educative applications.

  8. Design of learner-centred constructivism based learning process

    OpenAIRE

    Schreurs, Jeanne; Al-Huneidi, Ahmad

    2012-01-01

    A Learner-centered learning is constructivism based and Competence directed. We define general competencies, domain competencies and specific course competencies. Constructivism based learning activities are based on constructivism theory. For each course module the intended learning level will be defined. A model is built for the design of a learner centered constructivism based and competency directed learning process. The application of it in two courses are presented. Constructivism ba...

  9. Improving EEG signal peak detection using feature weight learning ...

    Indian Academy of Sciences (India)

    Therefore, we aimed to develop a general procedure for eye event-related applications based on feature weight learning (FWL), through the use of a neural network with random weights (NNRW) as the classifier. The FWL is performed using a particle swarm optimization algorithm, applied to the well-studied Dumpala, Acir, ...

  10. Sign(al)s: Living and Learning as Semiotic Engagement

    Science.gov (United States)

    Stables, Andrew

    2006-01-01

    Cartesian mind-body dualism, while often explicitly denied, has left a legacy of conceptions that remain highly influential in education. I argue that trends in both analytic and continental philosophy of language point towards a post-Cartesian settlement in which the distinction between "signs" and "signals" is collapsed, and which thus construes…

  11. Detection and Processing Techniques of FECG Signal for Fetal Monitoring

    Directory of Open Access Journals (Sweden)

    Hasan MA

    2009-03-01

    Full Text Available Abstract Fetal electrocardiogram (FECG signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies are becoming very important requirements in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and developed algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature for fetal monitoring. A comparative study has been carried out to show the performance and accuracy of various methods of FECG signal analysis for fetal monitoring. Finally, this paper further focused some of the hardware implementations using electrical signals for monitoring the fetal heart rate. This paper opens up a passage for researchers, physicians, and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system.

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

    Science.gov (United States)

    Tosi, Daniele; Olivero, Massimo; Perrone, Guido

    2008-06-01

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

  13. Cryogenic loss monitors with FPGA TDC signal processing

    Energy Technology Data Exchange (ETDEWEB)

    Warner, A.; Wu, J.; /Fermilab

    2011-09-01

    Radiation hard helium gas ionization chambers capable of operating in vacuum at temperatures ranging from 5K to 350K have been designed, fabricated and tested and will be used inside the cryostats at Fermilab's Superconducting Radiofrequency beam test facility. The chamber vessels are made of stainless steel and all materials used including seals are known to be radiation hard and suitable for operation at 5K. The chambers are designed to measure radiation up to 30 kRad/hr with sensitivity of approximately 1.9 pA/(Rad/hr). The signal current is measured with a recycling integrator current-to-frequency converter to achieve a required measurement capability for low current and a wide dynamic range. A novel scheme of using an FPGA-based time-to-digital converter (TDC) to measure time intervals between pulses output from the recycling integrator is employed to ensure a fast beam loss response along with a current measurement resolution better than 10-bit. This paper will describe the results obtained and highlight the processing techniques used.

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

    Science.gov (United States)

    Rao, K. R.

    1987-06-01

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

  15. Signal Processing for a Lunar Array: Minimizing Power Consumption

    Science.gov (United States)

    D'Addario, Larry; Simmons, Samuel

    2011-01-01

    Motivation for the study is: (1) Lunar Radio Array for low frequency, high redshift Dark Ages/Epoch of Reionization observations (z =6-50, f=30-200 MHz) (2) High precision cosmological measurements of 21 cm H I line fluctuations (3) Probe universe before first star formation and provide information about the Intergalactic Medium and evolution of large scale structures (5) Does the current cosmological model accurately describe the Universe before reionization? Lunar Radio Array is for (1) Radio interferometer based on the far side of the moon (1a) Necessary for precision measurements, (1b) Shielding from earth-based and solar RFI (12) No permanent ionosphere, (2) Minimum collecting area of approximately 1 square km and brightness sensitivity 10 mK (3)Several technologies must be developed before deployment The power needed to process signals from a large array of nonsteerable elements is not prohibitive, even for the Moon, and even in current technology. Two different concepts have been proposed: (1) Dark Ages Radio Interferometer (DALI) (2)( Lunar Array for Radio Cosmology (LARC)

  16. 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...

  17. 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.

  18. Dynamic Characteristics of Buildings from Signal Processing of Ambient Vibration

    Science.gov (United States)

    Dobre, Daniela; Sorin Dragomir, Claudiu

    2017-10-01

    The experimental technique used to determine the dynamic characteristics of buildings is based on records of low intensity oscillations of the building produced by various natural factors, such as permanent agitation type microseismic motions, city traffic, wind etc. The possibility of recording these oscillations is provided by the latest seismic stations (Geosig and Kinemetrics digital accelerographs). The permanent microseismic agitation of the soil is a complex form of stationary random oscillations. The building filters the soil excitation, selects and increases the components of disruptive vibrations corresponding to its natural vibration periods. For some selected buildings, with different instrumentation schemes for the location of sensors (in free-field, at basement, ground floor, roof level), a correlation between the dynamic characteristics resulted from signal processing of ambient vibration and from a theoretical analysis will be presented. The interpretation of recording results could highlight the behavior of the whole structure. On the other hand, these results are compared with those from strong motions, or obtained from a complex dynamic analysis, and they are quite different, but they are explicable.

  19. Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

    Science.gov (United States)

    Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

    2017-02-01

    Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

  20. A New Digital Signal Processing Method for Spectrum Interference Monitoring

    Science.gov (United States)

    Angrisani, L.; Capriglione, D.; Ferrigno, L.; Miele, G.

    2011-01-01

    Frequency spectrum is a limited shared resource, nowadays interested by an ever growing number of different applications. Generally, the companies providing such services pay to the governments the right of using a limited portion of the spectrum, consequently they would be assured that the licensed radio spectrum resource is not interested by significant external interferences. At the same time, they have to guarantee that their devices make an efficient use of the spectrum and meet the electromagnetic compatibility regulations. Therefore the competent authorities are called to control the access to the spectrum adopting suitable management and monitoring policies, as well as the manufacturers have to periodically verify the correct working of their apparatuses. Several measurement solutions are present on the market. They generally refer to real-time spectrum analyzers and measurement receivers. Both of them are characterized by good metrological accuracies but show costs, dimensions and weights that make no possible a use "on the field". The paper presents a first step in realizing a digital signal processing based measurement instrument able to suitably accomplish for the above mentioned needs. In particular the attention has been given to the DSP based measurement section of the instrument. To these aims an innovative measurement method for spectrum monitoring and management is proposed in this paper. It performs an efficient sequential analysis based on a sample by sample digital processing. Three main issues are in particular pursued: (i) measurement performance comparable to that exhibited by other methods proposed in literature; (ii) fast measurement time, (iii) easy implementation on cost-effective measurement hardware.

  1. BIBLIOGRAPHY ON LEARNING PROCESS. SUPPLEMENT II.

    Science.gov (United States)

    Harvard Univ., Cambridge, MA. Graduate School of Education.

    THIS SUPPLEMENTARY BIBLIOGRAPHY LISTS MATERIALS ON VARIOUS FACETS OF HUMAN LEARNING. APPROXIMATELY 60 UNANNOTATED REFERENCES ARE PROVIDED FOR DOCUMENTS DATING FROM 1954 TO 1966. JOURNAL ARTICLES, BOOKS, RESEARCH REPORTS, AND CONFERENCE PAPERS ARE LISTED. SOME SUBJECT AREAS INCLUDED ARE (1) LEARNING PARAMETERS AND ABILITY, (2) RETENTION AND…

  2. Learning Process and Vocational Experience Attainments.

    Science.gov (United States)

    Colardyn, Danielle; White, Kathleen M.

    From a search of (mostly French) literature, a hypothesis was formulated that students with both academic training and work experience would solve a practical learning problem more easily than students with academic learning only. A study was conducted at the Conservatoire National des Arts et Metiers in Paris to test this hypothesis. Two groups,…

  3. Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning.

    Science.gov (United States)

    McDougle, Samuel D; Bond, Krista M; Taylor, Jordan A

    2015-07-01

    A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. Copyright © 2015 the authors 0270-6474/15/359568-12$15.00/0.

  4. An Analysis of Learning Activities in a Technology Education Textbook for Teachers : Learning Process Based on Contents Framework and Learning Scene to Develop Technological Literacy

    OpenAIRE

    Yata, Chikahiko; Hamamoto, Kengo; Oguri, Takenori

    2014-01-01

    This study analyzed the learning activities in a textbook on technology education for teachers, in order to examine the learning processes and learning scenes detailed therein. Results of analyzing learning process, primary learning activity found each contents framework. Other learning activities designated to be related to complementary in learning process. Results of analyzing learning scene, 14 learning scenes, among them "Scene to recognize the impact on social life and progress of techn...

  5. Social signals and aversive learning in honey bee drones and workers

    Science.gov (United States)

    Pérez, Eddie; Vallejo, Lianna; Pérez, María E.; Abramson, Charles I.; Giray, Tugrul

    2017-01-01

    ABSTRACT The dissemination of information is a basic element of group cohesion. In honey bees (Apis mellifera Linnaeus 1758), like in other social insects, the principal method for colony-wide information exchange is communication via pheromones. This medium of communication allows multiple individuals to conduct tasks critical to colony survival. Social signaling also establishes conflict at the level of the individual who must trade-off between attending to the immediate environment or the social demand. In this study we examined this conflict by challenging highly social worker honey bees, and less social male drone honey bees undergoing aversive training by presenting them with a social stress signal (isopentyl acetate, IPA). We utilized IPA exposure methods that caused lower learning performance in appetitive learning in workers. Exposure to isopentyl acetate (IPA) did not affect performance of drones and had a dose-specific effect on worker response, with positive effects diminishing at higher IPA doses. The IPA effects are specific because non-social cues, such as the odor cineole, improve learning performance in drones, and social homing signals (geraniol) did not have a discernible effect on drone or worker performance. We conclude that social signals do generate conflict and that response to them is dependent on signal relevance to the individual as well as the context. We discuss the effect of social signal on learning both related to its social role and potential evolutionary history. PMID:27895050

  6. Social signals and aversive learning in honey bee drones and workers

    Directory of Open Access Journals (Sweden)

    Arian Avalos

    2017-01-01

    Full Text Available The dissemination of information is a basic element of group cohesion. In honey bees (Apis mellifera Linnaeus 1758, like in other social insects, the principal method for colony-wide information exchange is communication via pheromones. This medium of communication allows multiple individuals to conduct tasks critical to colony survival. Social signaling also establishes conflict at the level of the individual who must trade-off between attending to the immediate environment or the social demand. In this study we examined this conflict by challenging highly social worker honey bees, and less social male drone honey bees undergoing aversive training by presenting them with a social stress signal (isopentyl acetate, IPA. We utilized IPA exposure methods that caused lower learning performance in appetitive learning in workers. Exposure to isopentyl acetate (IPA did not affect performance of drones and had a dose-specific effect on worker response, with positive effects diminishing at higher IPA doses. The IPA effects are specific because non-social cues, such as the odor cineole, improve learning performance in drones, and social homing signals (geraniol did not have a discernible effect on drone or worker performance. We conclude that social signals do generate conflict and that response to them is dependent on signal relevance to the individual as well as the context. We discuss the effect of social signal on learning both related to its social role and potential evolutionary history.

  7. Social signals and aversive learning in honey bee drones and workers.

    Science.gov (United States)

    Avalos, Arian; Pérez, Eddie; Vallejo, Lianna; Pérez, María E; Abramson, Charles I; Giray, Tugrul

    2017-01-15

    The dissemination of information is a basic element of group cohesion. In honey bees (Apis mellifera Linnaeus 1758), like in other social insects, the principal method for colony-wide information exchange is communication via pheromones. This medium of communication allows multiple individuals to conduct tasks critical to colony survival. Social signaling also establishes conflict at the level of the individual who must trade-off between attending to the immediate environment or the social demand. In this study we examined this conflict by challenging highly social worker honey bees, and less social male drone honey bees undergoing aversive training by presenting them with a social stress signal (isopentyl acetate, IPA). We utilized IPA exposure methods that caused lower learning performance in appetitive learning in workers. Exposure to isopentyl acetate (IPA) did not affect performance of drones and had a dose-specific effect on worker response, with positive effects diminishing at higher IPA doses. The IPA effects are specific because non-social cues, such as the odor cineole, improve learning performance in drones, and social homing signals (geraniol) did not have a discernible effect on drone or worker performance. We conclude that social signals do generate conflict and that response to them is dependent on signal relevance to the individual as well as the context. We discuss the effect of social signal on learning both related to its social role and potential evolutionary history. © 2017. Published by The Company of Biologists Ltd.

  8. Statistical Signal Processing in Humanitarian Mine Clerance Systems

    DEFF Research Database (Denmark)

    Karlsen, Brian; Sørensen, Helge Bjarup Dissing; Larsen, Jan

    2002-01-01

    Denne artikel beskriver kortfattet metoder og resultater relateret til clutterreduktion (clutter: uønskede reflekterede signaler) i jordradar- (eng. ground penetrating radar, GPR) signaler vha. statistiske signalbehandlingsmetoder baseret på Independent Component Analysis (ICA). Formålet ved denne...

  9. 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

  10. The Role of Interpretation and Diagnosis in Signal Processing

    Science.gov (United States)

    1988-01-01

    122b. TELEPHONE (Incude Area Code) 2cOFIESYMBOL Elisabeth Colford - RLE Contract Reports I(617)258-5871I DO Form 1473, JUN 84 Previous editions ame...6] S. Lee, E. Milios, R. Greiner , and J. Rossiter. Signal ab- stractions in the machine analysis of radar signals for ice profiling. In International

  11. Phosphorelays provide tunable signal processing capabilities for the cell

    DEFF Research Database (Denmark)

    Kothamachu, Varun B; Feliu, Elisenda; Wiuf, Carsten

    2013-01-01

    present here this relation for four-layered phosphorelays, which are signaling systems that are ubiquitous in prokaryotes and also found in lower eukaryotes and plants. We derive an analytical expression that relates the shape of the signal-response relationship in a relay to the kinetic rates of forward...

  12. Processing of dual-orthogonal cw polarimetric radar signals

    NARCIS (Netherlands)

    Babur, G.

    2009-01-01

    The thesis consists of two parts. The first part is devoted to the theory of dual-orthogonal polarimetric radar signals with continuous waveforms. The thesis presents a comparison of the signal compression techniques, namely correlation and de-ramping methods, for the dual-orthogonal sophisticated

  13. An imperfect dopaminergic error signal can drive temporal-difference learning.

    Directory of Open Access Journals (Sweden)

    Wiebke Potjans

    2011-05-01

    Full Text Available An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards.

  14. Introduction to section 1 - Learning as a process

    DEFF Research Database (Denmark)

    Sriskandarajah, Nadarajah; Cerf, Marianne; Noe, Egon

    2006-01-01

    As an introduction to the workshop where 18 papers and posters were presented on the theme of ‘Learning as a Process’, the linked nature of the learning – knowing – acting field in rural development in Europe is emphasised. The workshop took up the issues of human interactions in foster learning...... processes, capacity building and development of collective action as a bottom-up process....

  15. Simulation of signal and background processes for collider experiments

    International Nuclear Information System (INIS)

    Schumann, S.

    2008-01-01

    In this thesis new theoretical tools for the accurate simulation of scattering processes at present and future collider experiments have been developed. Special emphasis has thereby to be given to multi-particle/multi-jet final states that often constitute signals for interesting (new) physics. Considering final states with a number of hard jets, there seems to be enough evidence that the traditional simulation tools HERWIG and PYTHIA cannot fully accomplish their description. Starting from a 2→2 core process, they account only for soft and collinear QCD emissions through parton-shower models. Only recently, theoretical prescriptions have been found to consistently combine tree-level matrix-element calculations with the existing parton-shower algorithms. The gain of such methods is that phase-space regions covered by hard and by soft parton kinematics are simultaneously well described. In Chapter 2 of this thesis the working principles of such prescriptions have been discussed with special attention being paid to the merging scheme implemented in the SHERPA Monte Carlo. To consistently match QCD higher-order calculations (at one-loop or tree-level) with parton showers, a good analytical control over the perturbative terms present in the latter is required. This has triggered the demand for improved parton-shower models that facilitate the inclusion of exact matrix elements. In this line a completely new shower algorithm has been presented in Chapter 3. It is based on the Catani-Seymour dipole subtraction formalism, a universal method for calculating arbitrary processes at next-to-leading order in QCD. The splitting kernels used in the shower are justified approximations of the Catani-Seymour dipole functions. The kinematics of the individual splittings is accomplished such that exact four-momentum conservation can be ensured for each single branching. Accordingly, the shower can be stopped and started again at each intermediate stage of the evolution. The model

  16. Simulation of signal and background processes for collider experiments

    Energy Technology Data Exchange (ETDEWEB)

    Schumann, S.

    2008-10-08

    In this thesis new theoretical tools for the accurate simulation of scattering processes at present and future collider experiments have been developed. Special emphasis has thereby to be given to multi-particle/multi-jet final states that often constitute signals for interesting (new) physics. Considering final states with a number of hard jets, there seems to be enough evidence that the traditional simulation tools HERWIG and PYTHIA cannot fully accomplish their description. Starting from a 2{yields}2 core process, they account only for soft and collinear QCD emissions through parton-shower models. Only recently, theoretical prescriptions have been found to consistently combine tree-level matrix-element calculations with the existing parton-shower algorithms. The gain of such methods is that phase-space regions covered by hard and by soft parton kinematics are simultaneously well described. In Chapter 2 of this thesis the working principles of such prescriptions have been discussed with special attention being paid to the merging scheme implemented in the SHERPA Monte Carlo. To consistently match QCD higher-order calculations (at one-loop or tree-level) with parton showers, a good analytical control over the perturbative terms present in the latter is required. This has triggered the demand for improved parton-shower models that facilitate the inclusion of exact matrix elements. In this line a completely new shower algorithm has been presented in Chapter 3. It is based on the Catani-Seymour dipole subtraction formalism, a universal method for calculating arbitrary processes at next-to-leading order in QCD. The splitting kernels used in the shower are justified approximations of the Catani-Seymour dipole functions. The kinematics of the individual splittings is accomplished such that exact four-momentum conservation can be ensured for each single branching. Accordingly, the shower can be stopped and started again at each intermediate stage of the evolution. The

  17. Enhancing the Teaching-Learning Process: A Knowledge Management Approach

    Science.gov (United States)

    Bhusry, Mamta; Ranjan, Jayanthi

    2012-01-01

    Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…

  18. Explaining discontinuity in organizational learning : a process analysis

    NARCIS (Netherlands)

    Berends, J.J.; Lammers, I.S.

    2010-01-01

    This paper offers a process analysis of organizational learning as it unfolds in a social and temporal context. Building upon the 4I framework (Crossan et al. 1999), we examine organizational learning processes in a longitudinal case study of an implementation of knowledge management in an

  19. Contrasting dynamics of organizational learning : a process theory perspective

    NARCIS (Netherlands)

    Berends, J.J.; Lammers, I.S.

    2006-01-01

    In this paper we analyze the process characteristics of organizational learning. A wide variety of process models of organizational learning have been proposed in the literature, but these models have not been systematically investigated. In this paper we use Van de Ven and Poole's (1995) taxonomy

  20. Electrical Storm Simulation to Improve the Learning Physics Process

    Science.gov (United States)

    Martínez Muñoz, Miriam; Jiménez Rodríguez, María Lourdes; Gutiérrez de Mesa, José Antonio

    2013-01-01

    This work is part of a research project whose main objective is to understand the impact that the use of Information and Communication Technology (ICT) has on the teaching and learning process on the subject of Physics. We will show that, with the use of a storm simulator, physics students improve their learning process on one hand they understand…