Model Based Signal Processing

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Model-Based Signal Processing

Author : James V. Candy
Publisher : John Wiley & Sons
ISBN 13 : 0471732664
Total Pages : 702 pages
Book Rating : 4.4/5 (717 download)

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Book Synopsis Model-Based Signal Processing by : James V. Candy

Download or read book Model-Based Signal Processing written by James V. Candy and published by John Wiley & Sons. This book was released on 2005-10-27 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique treatment of signal processing using a model-based perspective Signal processing is primarily aimed at extracting useful information, while rejecting the extraneous from noisy data. If signal levels are high, then basic techniques can be applied. However, low signal levels require using the underlying physics to correct the problem causing these low levels and extracting the desired information. Model-based signal processing incorporates the physical phenomena, measurements, and noise in the form of mathematical models to solve this problem. Not only does the approach enable signal processors to work directly in terms of the problem's physics, instrumentation, and uncertainties, but it provides far superior performance over the standard techniques. Model-based signal processing is both a modeler's as well as a signal processor's tool. Model-Based Signal Processing develops the model-based approach in a unified manner and follows it through the text in the algorithms, examples, applications, and case studies. The approach, coupled with the hierarchy of physics-based models that the author develops, including linear as well as nonlinear representations, makes it a unique contribution to the field of signal processing. The text includes parametric (e.g., autoregressive or all-pole), sinusoidal, wave-based, and state-space models as some of the model sets with its focus on how they may be used to solve signal processing problems. Special features are provided that assist readers in understanding the material and learning how to apply their new knowledge to solving real-life problems. * Unified treatment of well-known signal processing models including physics-based model sets * Simple applications demonstrate how the model-based approach works, while detailed case studies demonstrate problem solutions in their entirety from concept to model development, through simulation, application to real data, and detailed performance analysis * Summaries provided with each chapter ensure that readers understand the key points needed to move forward in the text as well as MATLAB(r) Notes that describe the key commands and toolboxes readily available to perform the algorithms discussed * References lead to more in-depth coverage of specialized topics * Problem sets test readers' knowledge and help them put their new skills into practice The author demonstrates how the basic idea of model-based signal processing is a highly effective and natural way to solve both basic as well as complex processing problems. Designed as a graduate-level text, this book is also essential reading for practicing signal-processing professionals and scientists, who will find the variety of case studies to be invaluable. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department

Signal Processing

Author : James V. Candy
Publisher : McGraw-Hill Companies
ISBN 13 :
Total Pages : 264 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Signal Processing by : James V. Candy

Download or read book Signal Processing written by James V. Candy and published by McGraw-Hill Companies. This book was released on 1986 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Biomedical Signal Processing And Signal Modeling

Author : Bruce
Publisher : John Wiley & Sons
ISBN 13 : 9788126511112
Total Pages : 540 pages
Book Rating : 4.5/5 (111 download)

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Book Synopsis Biomedical Signal Processing And Signal Modeling by : Bruce

Download or read book Biomedical Signal Processing And Signal Modeling written by Bruce and published by John Wiley & Sons. This book was released on 2007-01-20 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unique framework for understanding signal processing of biomedical signals and what it tells us about signal sources and their behavior in response to perturbation. Using a modeling-based approach, the author shows how to perform signal processing by developing and manipulating a model of the signal source, providing a logical, coherent basis for recognizing signal types and for tackling the special challenges posed by biomedical signals-including the effects of noise on the signal, changes in basic properties, or the fact that these signals contain large stochastic components and may even be fractal or chaotic. Each chapter begins with a detailed biomedical example, illustrating the methods under discussion and highlighting the interconnection between the theoretical concepts and applications. · The Nature of Biomedical Signals· Memory and Correlation· The Impulse Response· Frequency Response· Modeling Continuous-Time Signals as Sums of Sine Waves· Responses of Linear Continuous-Time Filters to Arbitrary Inputs· Modeling Signals as Sums of Discrete-Time Sine Waves· Noise Removal and Signal Compensation· Modeling Stochastic Signals as Filtered White Noise· Scaling and Long-Term Memory· Nonlinear Models of Signals· Assessing Stationarity and Reproducibility

Signals and Systems in Biomedical Engineering

Author : Suresh R. Devasahayam
Publisher : Springer Science & Business Media
ISBN 13 : 1461542995
Total Pages : 348 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Signals and Systems in Biomedical Engineering by : Suresh R. Devasahayam

Download or read book Signals and Systems in Biomedical Engineering written by Suresh R. Devasahayam and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past few years Biomedical Engineering has received a great deal of attention as one of the emerging technologies in the last decade and for years to come, as witnessed by the many books, conferences, and their proceedings. Media attention, due to the applications-oriented advances in Biomedical Engineering, has also increased. Much of the excitement comes from the fact that technology is rapidly changing and new technological adventures become available and feasible every day. For many years the physical sciences contributed to medicine in the form of expertise in radiology and slow but steady contributions to other more diverse fields, such as computers in surgery and diagnosis, neurology, cardiology, vision and visual prosthesis, audition and hearing aids, artificial limbs, biomechanics, and biomaterials. The list goes on. It is therefore hard for a person unfamiliar with a subject to separate the substance from the hype. Many of the applications of Biomedical Engineering are rather complex and difficult to understand even by the not so novice in the field. Much of the hardware and software tools available are either too simplistic to be useful or too complicated to be understood and applied. In addition, the lack of a common language between engineers and computer scientists and their counterparts in the medical profession, sometimes becomes a barrier to progress.

Digital Signal Processing with Kernel Methods

Author : Jose Luis Rojo-Alvarez
Publisher : John Wiley & Sons
ISBN 13 : 1118611799
Total Pages : 665 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Digital Signal Processing with Kernel Methods by : Jose Luis Rojo-Alvarez

Download or read book Digital Signal Processing with Kernel Methods written by Jose Luis Rojo-Alvarez and published by John Wiley & Sons. This book was released on 2018-02-05 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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: http://github.com/DSPKM • Presents the necessary basic ideas from both digital signal processing and machine learning concepts • Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing • Surveys advances in kernel signal processing beyond SVM algorithms to present other highly relevant kernel methods for digital signal processing An excellent book for signal processing researchers and practitioners, Digital Signal Processing with Kernel Methods will also appeal to those involved in machine learning and pattern recognition.

Bayesian Signal Processing

Author : James V. Candy
Publisher : John Wiley & Sons
ISBN 13 : 1119125480
Total Pages : 640 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Bayesian Signal Processing by : James V. Candy

Download or read book Bayesian Signal Processing written by James V. Candy and published by John Wiley & Sons. This book was released on 2016-06-20 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the Bayesian approach to statistical signal processing for a variety of useful model sets This book aims to give readers a unified Bayesian treatment starting from the basics (Baye’s rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to “fill-in-the gaps” of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical “sanity testing” lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed and applied. These expansions of the book have been updated to provide a more cohesive discussion of Bayesian processing with examples and applications enabling the comprehension of alternative approaches to solving estimation/detection problems. The second edition of Bayesian Signal Processing features: “Classical” Kalman filtering for linear, linearized, and nonlinear systems; “modern” unscented and ensemble Kalman filters: and the “next-generation” Bayesian particle filters Sequential Bayesian detection techniques incorporating model-based schemes for a variety of real-world problems Practical Bayesian processor designs including comprehensive methods of performance analysis ranging from simple sanity testing and ensemble techniques to sophisticated information metrics New case studies on adaptive particle filtering and sequential Bayesian detection are covered detailing more Bayesian approaches to applied problem solving MATLAB® notes at the end of each chapter help readers solve complex problems using readily available software commands and point out other software packages available Problem sets included to test readers’ knowledge and help them put their new skills into practice Bayesian Signal Processing, Second Edition is written for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.

Digital Signal Processing with Matlab Examples, Volume 3

Author : Jose Maria Giron-Sierra
Publisher : Springer
ISBN 13 : 9811025401
Total Pages : 431 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Digital Signal Processing with Matlab Examples, Volume 3 by : Jose Maria Giron-Sierra

Download or read book Digital Signal Processing with Matlab Examples, Volume 3 written by Jose Maria Giron-Sierra and published by Springer. This book was released on 2016-11-21 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the third 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 primarily focuses on filter banks, wavelets, and images. While the Fourier transform is adequate for periodic signals, wavelets are more suitable for other cases, such as short-duration signals: bursts, spikes, tweets, lung sounds, etc. Both Fourier and wavelet transforms decompose signals into components. Further, both are also invertible, so the original signals can be recovered from their components. Compressed sensing has emerged as a promising idea. One of the intended applications is networked devices or sensors, which are now becoming a reality; accordingly, this topic is also addressed. A selection of experiments that demonstrate image denoising applications are also included. In the interest of reader-friendliness, the longer programs have been grouped in an appendix; further, a second appendix on optimization has been added to supplement the content of the last chapter.

Event-Based Control and Signal Processing

Author : Marek Miskowicz
Publisher : CRC Press
ISBN 13 : 1482256568
Total Pages : 558 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Event-Based Control and Signal Processing by : Marek Miskowicz

Download or read book Event-Based Control and Signal Processing written by Marek Miskowicz and published by CRC Press. This book was released on 2018-09-03 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Event-based systems are a class of reactive systems deployed in a wide spectrum of engineering disciplines including control, communication, signal processing, and electronic instrumentation. Activities in event-based systems are triggered in response to events usually representing a significant change of the state of controlled or monitored physical variables. Event-based systems adopt a model of calls for resources only if it is necessary, and therefore, they are characterized by efficient utilization of communication bandwidth, computation capability, and energy budget. Currently, the economical use of constrained technical resources is a critical issue in various application domains because many systems become increasingly networked, wireless, and spatially distributed. Event-Based Control and Signal Processing examines the event-based paradigm in control, communication, and signal processing, with a focus on implementation in networked sensor and control systems. Featuring 23 chapters contributed by more than 60 leading researchers from around the world, this book covers: Methods of analysis and design of event-based control and signal processing Event-driven control and optimization of hybrid systems Decentralized event-triggered control Periodic event-triggered control Model-based event-triggered control and event-triggered generalized predictive control Event-based intermittent control in man and machine Event-based PID controllers Event-based state estimation Self-triggered and team-triggered control Event-triggered and time-triggered real-time architectures for embedded systems Event-based continuous-time signal acquisition and DSP Statistical event-based signal processing in distributed detection and estimation Asynchronous spike event coding technique with address event representation Event-based processing of non-stationary signals Event-based digital (FIR and IIR) filters Event-based local bandwidth estimation and signal reconstruction Event-Based Control and Signal Processing is the first extensive study on both event-based control and event-based signal processing, presenting scientific contributions at the cutting edge of modern science and engineering.

Multimedia Signal Processing

Author : Saeed V. Vaseghi
Publisher : John Wiley & Sons
ISBN 13 : 9780470066492
Total Pages : 680 pages
Book Rating : 4.0/5 (664 download)

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Book Synopsis Multimedia Signal Processing by : Saeed V. Vaseghi

Download or read book Multimedia Signal Processing written by Saeed V. Vaseghi and published by John Wiley & Sons. This book was released on 2007-10-22 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimedia Signal Processing is a comprehensive and accessible text to the theory and applications of digital signal processing (DSP). The applications of DSP are pervasive and include multimedia systems, cellular communication, adaptive network management, radar, pattern recognition, medical signal processing, financial data forecasting, artificial intelligence, decision making, control systems and search engines. This book is organised in to three major parts making it a coherent and structured presentation of the theory and applications of digital signal processing. A range of important topics are covered in basic signal processing, model-based statistical signal processing and their applications. Part 1: Basic Digital Signal Processing gives an introduction to the topic, discussing sampling and quantization, Fourier analysis and synthesis, Z-transform, and digital filters. Part 2: Model-based Signal Processing covers probability and information models, Bayesian inference, Wiener filter, adaptive filters, linear prediction hidden Markov models and independent component analysis. Part 3: Applications of Signal Processing in Speech, Music and Telecommunications explains the topics of speech and music processing, echo cancellation, deconvolution and channel equalization, and mobile communication signal processing. Covers music signal processing, explains the anatomy and psychoacoustics of hearing and the design of MP3 music coder Examines speech processing technology including speech models, speech coding for mobile phones and speech recognition Covers single-input and multiple-inputs denoising methods, bandwidth extension and the recovery of lost speech packets in applications such as voice over IP (VoIP) Illustrated throughout, including numerous solved problems, Matlab experiments and demonstrations Companion website features Matlab and C++ programs with electronic copies of all figures. This book is ideal for researchers, postgraduates and senior undergraduates in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be a valuable text to professional engineers in telecommunications and audio and signal processing industries.

Maximum-Likelihood Deconvolution

Author : Jerry M. Mendel
Publisher : Springer Science & Business Media
ISBN 13 : 1461233704
Total Pages : 233 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Maximum-Likelihood Deconvolution by : Jerry M. Mendel

Download or read book Maximum-Likelihood Deconvolution written by Jerry M. Mendel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convolution is the most important operation that describes the behavior of a linear time-invariant dynamical system. Deconvolution is the unraveling of convolution. It is the inverse problem of generating the system's input from knowledge about the system's output and dynamics. Deconvolution requires a careful balancing of bandwidth and signal-to-noise ratio effects. Maximum-likelihood deconvolution (MLD) is a design procedure that handles both effects. It draws upon ideas from Maximum Likelihood, when unknown parameters are random. It leads to linear and nonlinear signal processors that provide high-resolution estimates of a system's input. All aspects of MLD are described, from first principles in this book. The purpose of this volume is to explain MLD as simply as possible. To do this, the entire theory of MLD is presented in terms of a convolutional signal generating model and some relatively simple ideas from optimization theory. Earlier approaches to MLD, which are couched in the language of state-variable models and estimation theory, are unnecessary to understand the essence of MLD. MLD is a model-based signal processing procedure, because it is based on a signal model, namely the convolutional model. The book focuses on three aspects of MLD: (1) specification of a probability model for the system's measured output; (2) determination of an appropriate likelihood function; and (3) maximization of that likelihood function. Many practical algorithms are obtained. Computational aspects of MLD are described in great detail. Extensive simulations are provided, including real data applications.

Financial Signal Processing and Machine Learning

Author : Ali N. Akansu
Publisher : John Wiley & Sons
ISBN 13 : 1118745639
Total Pages : 312 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Financial Signal Processing and Machine Learning by : Ali N. Akansu

Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu and published by John Wiley & Sons. This book was released on 2016-04-21 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.

Model-Based Processing

Author : James V. Candy
Publisher : John Wiley & Sons
ISBN 13 : 1119457777
Total Pages : 544 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Model-Based Processing by : James V. Candy

Download or read book Model-Based Processing written by James V. Candy and published by John Wiley & Sons. This book was released on 2019-03-15 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: A bridge between the application of subspace-based methods for parameter estimation in signal processing and subspace-based system identification in control systems Model-Based Processing: An Applied Subspace Identification Approach provides expert insight on developing models for designing model-based signal processors (MBSP) employing subspace identification techniques to achieve model-based identification (MBID) and enables readers to evaluate overall performance using validation and statistical analysis methods. Focusing on subspace approaches to system identification problems, this book teaches readers to identify models quickly and incorporate them into various processing problems including state estimation, tracking, detection, classification, controls, communications, and other applications that require reliable models that can be adapted to dynamic environments. The extraction of a model from data is vital to numerous applications, from the detection of submarines to determining the epicenter of an earthquake to controlling an autonomous vehicles—all requiring a fundamental understanding of their underlying processes and measurement instrumentation. Emphasizing real-world solutions to a variety of model development problems, this text demonstrates how model-based subspace identification system identification enables the extraction of a model from measured data sequences from simple time series polynomials to complex constructs of parametrically adaptive, nonlinear distributed systems. In addition, this resource features: Kalman filtering for linear, linearized, and nonlinear systems; modern unscented Kalman filters; as well as Bayesian particle filters Practical processor designs including comprehensive methods of performance analysis Provides a link between model development and practical applications in model-based signal processing Offers in-depth examination of the subspace approach that applies subspace algorithms to synthesized examples and actual applications Enables readers to bridge the gap from statistical signal processing to subspace identification Includes appendices, problem sets, case studies, examples, and notes for MATLAB Model-Based Processing: An Applied Subspace Identification Approach is essential reading for advanced undergraduate and graduate students of engineering and science as well as engineers working in industry and academia.

Starting Digital Signal Processing in Telecommunication Engineering

Author : Tomasz P. Zieliński
Publisher : Springer Nature
ISBN 13 : 3030492567
Total Pages : 874 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Starting Digital Signal Processing in Telecommunication Engineering by : Tomasz P. Zieliński

Download or read book Starting Digital Signal Processing in Telecommunication Engineering written by Tomasz P. Zieliński and published by Springer Nature. This book was released on 2021-01-29 with total page 874 pages. Available in PDF, EPUB and Kindle. Book excerpt: This hands-on, laboratory driven textbook helps readers understand principles of digital signal processing (DSP) and basics of software-based digital communication, particularly software-defined networks (SDN) and software-defined radio (SDR). In the book only the most important concepts are presented. Each book chapter is an introduction to computer laboratory and is accompanied by complete laboratory exercises and ready-to-go Matlab programs with figures and comments (available at the book webpage and running also in GNU Octave 5.2 with free software packages), showing all or most details of relevant algorithms. Students are tasked to understand programs, modify them, and apply presented concepts to recorded real RF signal or simulated received signals, with modelled transmission condition and hardware imperfections. Teaching is done by showing examples and their modifications to different real-world telecommunication-like applications. The book consists of three parts: introduction to DSP (spectral analysis and digital filtering), introduction to DSP advanced topics (multi-rate, adaptive, model-based and multimedia - speech, audio, video - signal analysis and processing) and introduction to software-defined modern telecommunication systems (SDR technology, analog and digital modulations, single- and multi-carrier systems, channel estimation and correction as well as synchronization issues). Many real signals are processed in the book, in the first part – mainly speech and audio, while in the second part – mainly RF recordings taken from RTL-SDR USB stick and ADALM-PLUTO module, for example captured IQ data of VOR avionics signal, classical FM radio with RDS, digital DAB/DAB+ radio and 4G-LTE digital telephony. Additionally, modelling and simulation of some transmission scenarios are tested in software in the book, in particular TETRA, ADSL and 5G signals. Provides an introduction to digital signal processing and software-based digital communication; Presents a transition from digital signal processing to software-defined telecommunication; Features a suite of pedagogical materials including a laboratory test-bed and computer exercises/experiments.

Signal Processing for Neuroscientists

Author : Wim van Drongelen
Publisher : Elsevier
ISBN 13 : 008046775X
Total Pages : 319 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Signal Processing for Neuroscientists by : Wim van Drongelen

Download or read book Signal Processing for Neuroscientists written by Wim van Drongelen and published by Elsevier. This book was released on 2006-12-18 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the ‘golden trio’ in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. Multiple color illustrations are integrated in the text Includes an introduction to biomedical signals, noise characteristics, and recording techniques Basics and background for more advanced topics can be found in extensive notes and appendices A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Model Based Signal Enhancement for Impulse Response Measurement

Author : Xun Wang
Publisher : Logos Verlag Berlin GmbH
ISBN 13 : 3832536302
Total Pages : 148 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Model Based Signal Enhancement for Impulse Response Measurement by : Xun Wang

Download or read book Model Based Signal Enhancement for Impulse Response Measurement written by Xun Wang and published by Logos Verlag Berlin GmbH. This book was released on 2014 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Impulse response measurements that are performed outdoors are highly susceptible to the uncertainties caused by the non-perfect measurement setup, the presence of background noise, and fluctuations in media such as wind and temperature drift. This work concentrates on two scenarios: the measurement of reflection coefficients of noise barriers and the influence of temperature variances in machinery cavities. Regarding the sound barrier measurement outdoors, a linear four-microphone array can be used to separate direct sound and reflected sound if the sound barrier does not include complicated scattering structures. With regard to the impulse response of an air-borne sound measurement for a machine monitoring system, a time-warping model for inter-period and intra-period temperature variances is investigated.

Advanced Signal Processing Handbook

Author : Stergios Stergiopoulos
Publisher : CRC Press
ISBN 13 : 135136944X
Total Pages : 752 pages
Book Rating : 4.3/5 (513 download)

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Book Synopsis Advanced Signal Processing Handbook by : Stergios Stergiopoulos

Download or read book Advanced Signal Processing Handbook written by Stergios Stergiopoulos and published by CRC Press. This book was released on 2017-09-08 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in digital signal processing algorithms and computer technology have combined to produce real-time systems with capabilities far beyond those of just few years ago. Nonlinear, adaptive methods for signal processing have emerged to provide better array gain performance, however, they lack the robustness of conventional algorithms. The challenge remains to develop a concept that exploits the advantages of both-a scheme that integrates these methods in practical, real-time systems. The Advanced Signal Processing Handbook helps you meet that challenge. Beyond offering an outstanding introduction to the principles and applications of advanced signal processing, it develops a generic processing structure that takes advantage of the similarities that exist among radar, sonar, and medical imaging systems and integrates conventional and nonlinear processing schemes.

Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309159474
Total Pages : 251 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles by : National Research Council

Download or read book Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles written by National Research Council and published by National Academies Press. This book was released on 2010-07-30 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles evaluates various technologies and methods that could improve the fuel economy of medium- and heavy-duty vehicles, such as tractor-trailers, transit buses, and work trucks. The book also recommends approaches that federal agencies could use to regulate these vehicles' fuel consumption. Currently there are no fuel consumption standards for such vehicles, which account for about 26 percent of the transportation fuel used in the U.S. The miles-per-gallon measure used to regulate the fuel economy of passenger cars. is not appropriate for medium- and heavy-duty vehicles, which are designed above all to carry loads efficiently. Instead, any regulation of medium- and heavy-duty vehicles should use a metric that reflects the efficiency with which a vehicle moves goods or passengers, such as gallons per ton-mile, a unit that reflects the amount of fuel a vehicle would use to carry a ton of goods one mile. This is called load-specific fuel consumption (LSFC). The book estimates the improvements that various technologies could achieve over the next decade in seven vehicle types. For example, using advanced diesel engines in tractor-trailers could lower their fuel consumption by up to 20 percent by 2020, and improved aerodynamics could yield an 11 percent reduction. Hybrid powertrains could lower the fuel consumption of vehicles that stop frequently, such as garbage trucks and transit buses, by as much 35 percent in the same time frame.