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Books > Computing & IT > Applications of computing > Signal processing
This book collects selected papers from the 7th Conference on Signal and Information Processing, Networking and Computers held in Rizhao, China, on September 21-23, 2020. The 7th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) was held in Rizhao, China, on September 21-23, 2020.
In the past few years we have written and edited several books in the area of acousticandspeechsignalprocessing. Thereasonbehindthisendeavoristhat there were almost no books available in the literature when we ?rst started while there was (and still is) a real need to publish manuscripts summarizing the most useful ideas, concepts, results, and state-of-the-art algorithms in this important area of research. According to all the feedback we have received so far, we can say that we were right in doing this. Recently, several other researchers have followed us in this journey and have published interesting books with their own visions and perspectives. The idea of writing a book on Microphone Array Signal Processing comes from discussions we have had with many colleagues and friends. As a c- sequence of these discussions, we came up with the conclusion that, again, there is an urgent need for a monograph that carefully explains the theory and implementation of microphone arrays. While there are many manuscripts on antenna arrays from a narrowband perspective (narrowband signals and narrowband processing), the literature is quite scarce when it comes to s- sor arrays explained from a truly broadband perspective. Many algorithms for speech applications were simply borrowed from narrowband antenna - rays. However, a direct application of narrowband ideas to broadband speech processing may not be necessarily appropriate and can lead to many m- understandings.
Biomedical / Electrical Engineering Nonlinear Biomedical Signal
Processing Volume II: Dynamic Analysis and Modeling A volume in the
IEEE Press Series on Biomedical Engineering Metin Akay, Series
Editor Featuring current contributions by experts in signal
processing and biomedical engineering, this book introduces the
concepts, recent advances, and implementations of nonlinear dynamic
analysis methods. Together with Volume I in this series, this book
provides comprehensive coverage of nonlinear signal and image
processing techniques. Nonlinear Biomedical Signal Processing:
Volume II combines analytical and biological expertise in the
original mathematical simulation and modeling of physiological
systems. Detailed discussions of the analysis of steady-state and
dynamic systems, discrete-time system theory, and discrete modeling
of continuous-time systems are provided. Biomedical examples
include the analysis of the respiratory control system, the
dynamics of cardiac muscle and the cardiorespiratory function, and
neural firing patterns in auditory and vision systems. Examples
include relevant MATLAB(r) and Pascal programs. Topics covered
include:
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.
With the proliferation of mobile devices and hearing devices, including hearing aids and cochlear implants, there is a growing and pressing need to design algorithms that can improve speech intelligibility without sacrificing quality. Responding to this need, Speech Enhancement: Theory and Practice, Second Edition introduces readers to the basic problems of speech enhancement and the various algorithms proposed to solve these problems. Updated and expanded, this second edition of the bestselling textbook broadens its scope to include evaluation measures and enhancement algorithms aimed at improving speech intelligibility. Fundamentals, Algorithms, Evaluation, and Future Steps Organized into four parts, the book begins with a review of the fundamentals needed to understand and design better speech enhancement algorithms. The second part describes all the major enhancement algorithms and, because these require an estimate of the noise spectrum, also covers noise estimation algorithms. The third part of the book looks at the measures used to assess the performance, in terms of speech quality and intelligibility, of speech enhancement methods. It also evaluates and compares several of the algorithms. The fourth part presents binary mask algorithms for improving speech intelligibility under ideal conditions. In addition, it suggests steps that can be taken to realize the full potential of these algorithms under realistic conditions. What's New in This Edition Updates in every chapter A new chapter on objective speech intelligibility measures A new chapter on algorithms for improving speech intelligibility Real-world noise recordings (on downloadable resources) MATLAB (R) code for the implementation of intelligibility measures (on downloadable resources) MATLAB and C/C++ code for the implementation of algorithms to improve speech intelligibility (on downloadable resources) Valuable Insights from a Pioneer in Speech Enhancement Clear and concise, this book explores how human listeners compensate for acoustic noise in noisy environments. Written by a pioneer in speech enhancement and noise reduction in cochlear implants, it is an essential resource for anyone who wants to implement or incorporate the latest speech enhancement algorithms to improve the quality and intelligibility of speech degraded by noise. Includes downloadable resources with Code and Recordings The downloadable resources provide MATLAB implementations of representative speech enhancement algorithms as well as speech and noise databases for the evaluation of enhancement algorithms.
Probability and Random Processes, Second Edition presents pertinent applications to signal processing and communications, two areas of key interest to students and professionals in today's booming communications industry. The book includes unique chapters on narrowband random processes and simulation techniques. It also describes applications in digital communications, information theory, coding theory, image processing, speech analysis, synthesis and recognition, and others. Exceptional exposition and numerous worked out problems make this book extremely readable and accessible. The authors connect the applications discussed in class to the textbook. The new edition contains more real world signal processing and communications applications. It introduces the reader to the basics of probability theory and explores topics ranging from random variables, distributions and density functions to operations on a single random variable. There are also discussions on pairs of random variables; multiple random variables; random sequences and series; random processes in linear systems; Markov processes; and power spectral density. This book is intended for practicing engineers and students in graduate-level courses in the topic.
The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on the basis of observed data. The building of solutions involves the recognition of other pieces of a priori information. These solutions are then specific to the pieces of information taken into account. Clarifying and taking these pieces of information into account is necessary for grasping the domain of validity and the field of application for the solutions built. For too long, the interest in these problems has remained very limited in the signal-image community. However, the community has since recognized that these matters are more interesting and they have become the subject of much greater enthusiasm. From the application field s point of view, a significant part of the book is devoted to conventional subjects in the field of inversion: biological and medical imaging, astronomy, non-destructive evaluation, processing of video sequences, target tracking, sensor networks and digital communications. The variety of chapters is also clear, when we examine the acquisition modalities at stake: conventional modalities, such as tomography and NMR, visible or infrared optical imaging, or more recent modalities such as atomic force imaging and polarized light imaging.
With its exhaustive coverage of relevant theory, Signals and Systems Laboratory with MATLAB (R) is a powerful resource that provides simple, detailed instructions on how to apply computer methods to signals and systems analysis. Written for laboratory work in a course on signals and systems, this book presents a corresponding MATLAB implementation for each theoretical concept introduced, making it a powerful learning tool for engineers, scientists, and students alike. MATLAB code is used in problems and examples presented throughout the book. This code and other learning materials are available in a downloadable supplement. Due to the extensive-and truly unique-integration of MATLAB throughout this book, the authors provide a complete tutorial on use of the language for signals and systems analysis. With more than 5,000 lines of MATLAB code and more than 700 figures embedded in the text, the material teaches readers how to program in MATLAB and study signals and systems concepts at the same time, giving them the tools to harness the power of computers to quickly assess problems and then visualize their solutions. Among its many useful features, this book: Offers complete coverage of the signals and systems theory, starting with elementary signals and concluding with state-space modeling Contains more than 400 examples and chapter-end solved problems Executes commands one-by-one at the MATLAB command prompt, and results, along with comments, encouraging students to learn MATLAB on the fly Additional Pedagogical Features: A detailed MATLAB tutorial to introduce a beginner programmer to the language Laboratory exercises that give students hands-on experience and help professors organize a course laboratory component Presentation of continuous- and discrete-time in parallel fashion, effectively illustrating the similarities and differences between the two Step-by-step examples that present data in tabular format and usually offer several different solutions to each problem
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, coverage of autonomous vehicles that drive themselves, and information on multi-sensor fusion for driver ID and robust driver monitoring. "Digital Signal Processing for In-Vehicle Systems and Safety" is useful for engineering researchers, students, automotive manufacturers, government foundations and engineers working in the areas of control engineering, signal processing, audio-video processing, bio-mechanics, human factors and transportation engineering. "
This book focuses on broadband power amplifier design for wireless communication. Nonlinear model embedding is described as a powerful tool for designing broadband continuous Class-J and continuous class F power amplifiers. The authors also discuss various techniques for extending bandwidth of load modulation based power amplifiers, such as Doherty power amplifier and Chireix outphasing amplifiers. The book also covers recent trends on digital as well as analog techniques to enhance bandwidth and linearity in wireless transmitters. Presents latest trends in designing broadband power amplifiers; Covers latest techniques for using nonlinear model embedding in designing power amplifiers based on waveform engineering; Describes the latest techniques for extending bandwidth of load modulation based power amplifiers such as Doherty power amplifier and Chireix outphasing amplifiers; Includes coverage of hybrid analog/digital predistortion as wideband solution for wireless transmitters; Discusses recent trends on on-chip power amplifier design with GaN /GaAs MMICs for high frequency applications.
This book uses MATLAB as a computing tool to explore traditional DSP topics and solve problems. This greatly expands the range and complexity of problems that students can effectively study in signal processing courses. A large number of worked examples, computer simulations and applications are provided, along with theoretical aspects that are essential in order to gain a good understanding of the main topics. Practicing engineers may also find it useful as an introductory text on the subject.
A timely and authoritative guide to the state of the art of wave scattering Scattering of Electromagnetic Waves offers in three volumes a complete and up-to-date treatment of wave scattering by random discrete scatterers and rough surfaces. Written by leading scientists who have made important contributions to wave scattering over three decades, this new work explains the principles, methods, and applications of this rapidly expanding, interdisciplinary field. It covers both introductory and advanced material and provides students and researchers in remote sensing as well as imaging, optics, and electromagnetic theory with a one-stop reference to a wealth of current research results. Plus, Scattering of Electromagnetic Waves contains detailed discussions of both analytical and numerical methods, including cutting-edge techniques for the recovery of earth/land parametric information. The three volumes are entitled respectively Theories and Applications, Numerical Simulation, and Advanced Topics. In the second volume, Numerical Simulations, Leung Tsang (University of Washington) Jin Au Kong (MIT), Kung-Hau Ding (Air Force Research Lab), and Chi On Ao (MIT) cover:
This book deals with the autoregressive method for digital processing of random oscillations. The method is based on a one-to-one transformation of the numeric factors of the Yule series model to linear elastic system characteristics. This parametric approach allowed to develop a formal processing procedure from the experimental data to obtain estimates of logarithmic decrement and natural frequency of random oscillations. A straightforward mathematical description of the procedure makes it possible to optimize a discretization of oscillation realizations providing efficient estimates. The derived analytical expressions for confidence intervals of estimates enable a priori evaluation of their accuracy. Experimental validation of the method is also provided. Statistical applications for the analysis of mechanical systems arise from the fact that the loads experienced by machineries and various structures often cannot be described by deterministic vibration theory. Therefore, a sufficient description of real oscillatory processes (vibrations) calls for the use of random functions. In engineering practice, the linear vibration theory (modeling phenomena by common linear differential equations) is generally used. This theory's fundamental concepts such as natural frequency, oscillation decrement, resonance, etc. are credited for its wide use in different technical tasks. In technical applications two types of research tasks exist: direct and inverse. The former allows to determine stochastic characteristics of the system output X(t) resulting from a random process E(t) when the object model is considered known. The direct task enables to evaluate the effect of an operational environment on the designed object and to predict its operation under various loads. The inverse task is aimed at evaluating the object model on known processes E(t) and X(t), i.e. finding model (equations) factors. This task is usually met at the tests of prototypes to identify (or verify) its model experimentally. To characterize random processes a notion of "shaping dynamic system" is commonly used. This concept allows to consider the observing process as the output of a hypothetical system with the input being stationary Gauss-distributed ("white") noise. Therefore, the process may be exhaustively described in terms of parameters of that system. In the case of random oscillations, the "shaping system" is an elastic system described by the common differential equation of the second order: X (t)+2hX (t)+ _0^2 X(t)=E(t), where 0 = 2 / 0 is the natural frequency, T0 is the oscillation period, and h is a damping factor. As a result, the process X(t) can be characterized in terms of the system parameters - natural frequency and logarithmic oscillations decrement = hT0 as well as the process variance. Evaluation of these parameters is subjected to experimental data processing based on frequency or time-domain representations of oscillations. It must be noted that a concept of these parameters evaluation did not change much during the last century. For instance, in case of the spectral density utilization, evaluation of the decrement values is linked with bandwidth measurements at the points of half-power of the observed oscillations. For a time-domain presentation, evaluation of the decrement requires measuring covariance values delayed by a time interval divisible by T0. Both estimation procedures are derived from a continuous description of research phenomena, so the accuracy of estimates is linked directly to the adequacy of discrete representation of random oscillations. This approach is similar a concept of transforming differential equations to difference ones with derivative approximation by corresponding finite differences. The resulting discrete model, being an approximation, features a methodical error which can be decreased but never eliminated. To render such a presentation more accurate it is imperative to decrease the discretization interval and to increase realization size growing requirements for computing power. The spectral density and covariance function estimates comprise a non-parametric (non-formal) approach. In principle, any non-formal approach is a kind of art i.e. the results depend on the performer's skills. Due to interference of subjective factors in spectral or covariance estimates of random signals, accuracy of results cannot be properly determined or justified. To avoid the abovementioned difficulties, the application of linear time-series models with well-developed procedures for parameter estimates is more advantageous. A method for the analysis of random oscillations using a parametric model corresponding discretely (no approximation error) with a linear elastic system is developed and presented in this book. As a result, a one-to-one transformation of the model's numerical factors to logarithmic decrement and natural frequency of random oscillations is established. It allowed to develop a formal processing procedure from experimental data to obtain the estimates of and 0. The proposed approach allows researchers to replace traditional subjective techniques by a formal processing procedure providing efficient estimates with analytically defined statistical uncertainties.
In two editions spanning more than a decade, The Electrical Engineering Handbook stands as the definitive reference to the multidisciplinary field of electrical engineering. Our knowledge continues to grow, and so does the Handbook. For the third edition, it has expanded into a set of six books carefully focused on a specialized area or field of study. Each book represents a concise yet definitive collection of key concepts, models, and equations in its respective domain, thoughtfully gathered for convenient access. Circuits, Signals, and Speech and Image Processing presents all of the basic information related to electric circuits and components, analysis of circuits, the use of the Laplace transform, as well as signal, speech, and image processing using filters and algorithms. It also examines emerging areas such as text-to-speech synthesis, real-time processing, and embedded signal processing. Each article includes defining terms, references, and sources of further information. Encompassing the work of the world's foremost experts in their respective specialties, Circuits, Signals, and Speech and Image Processing features the latest developments, the broadest scope of coverage, and new material on biometrics.
Advances in the availability of computing power gave rise to an explosion of interest in the applications of smart antennas. Their ability to receive, block, and transmit signals simultaneously and in different directions renders them useful in areas from medical imaging to submarine sonar. This book examines the properties and applications of smart antennas. Detailed chapters address signal models, narrowband and broadband processing, adaptive algorithms, preprocessing techniques, and much more. Smart Antennas not only provides an instrument of learning that brings newcomers to the field quickly up to speed, but it also serves as an outstanding source of reference for thousands of practicing engineers.
Based on years of instruction and field expertise, this volume
offers the necessary tools to understand all scientific,
computational, and technological aspects of speech processing. The
book emphasizes mathematical abstraction, the dynamics of the
speech process, and the engineering optimization practices that
promote effective problem solving in this area of research and
covers many years of the authors' personal research on speech
processing. Speech Processing helps build valuable analytical
skills to help meet future challenges in scientific and
technological advances in the field and considers the complex
transition from human speech processing to computer speech
processing.
Describing non-parametric and parametric theoretic classification and the training of discriminant functions, this second edition includes new and expanded sections on neural networks, Fisher's discriminant, wavelet transform, and the method of principal components. It contains discussions on dimensionality reduction and feature selection, novel computer system architectures, proven algorithms for solutions to common roadblocks in data processing, computing models including the Hamming net, the Kohonen self-organizing map, and the Hopfield net, detailed appendices with data sets illustrating key concepts in the text, and more.
K.C. Chang presents an integrated approach to digital design principles, processes, and implementations to help the reader design increasingly complex systems within shorter design cycles. Chang introduces digital design concepts, VHDL coding, VHDL simulation, synthesis commands, and strategies together. "Digital Systems Design with VHDL and Synthesis" focuses on the ultimate product of the design cycle: the implementation of a digital design. Many of the design techniques and considerations illustrated in the text are examples of actual real-world designs. Unique features of the book include the following:
The book systematically introduces theories of frequently-used modern signal processing methods and technologies, and focuses discussions on stochastic signal, parameter estimation, modern spectral estimation, adaptive filter, high-order signal analysis and non-linear transformation in time-domain signal analysis. With abundant exercises, the book is an essential reference for graduate students in electrical engineering and information science.
Summarizing the latest research results for mitigating intersymbol interference (ISI), this pioneering reference/text introduces the new technique of modulated coding (MC) and considers three cases of MC encoding and decoding in which ISI channel information is: 1) available for both encoding and decoding, 2) not available for either encoding or decoding, and 3) available for encoding but not for decoding. Includes previously unpublished information and open problems on MC for ISI channels Focusing on transmitter-assisted equalization methods for ISI mitigation, Modulated Coding for Intersymbol Interference Channels reviews current ISI mitigation methods and formulates the capacity and information rates of an ISI channel details basic concepts related to MC and describes the combination of an MC and an ISI channel compares the coding of an MC and ISI channel to that of an uncoded Additive White Gaussian Noise (AWGN) channel considers the case of joint maximum-likelihood sequence estimation (MLSE) encoding and decoding of an MC coded ISI channel illustrates situations of suboptimal MC design given an ISI channel, such as Zero-Forcing Decision Feedback Equalizer (ZF-DFE) and Minimum Mean Square Error Decision Feedback Equalizer (MMSE-DFE) with corresponding MC designs considers multiple transmit and multiple receive antenna systems studies a channel-independent MC-coded orthogonal frequency division multiplexing (OFDM) system and also covers vector OFDM systems analyzes and applies polynomial ambiguity resistant MC (PARMC) to single-antenna and multiple-antenna systems and more Illustrated with over 900 equations and drawings, Modulated Coding for Intersymbol Interference Channels makes an excellent reference for electrical, electronics, signal processing, mechanical, image filtering and processing, computer circuit and systems, digital design, and communication engineers; and applied mathematicians; and a useful text
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.
Addresses a wide selection of multimedia applications, programmable and custom architectures for the implementations of multimedia systems, and arithmetic architectures and design methodologies. The book covers recent applications of digital signal processing algorithms in multimedia, presents high-speed and low-priority binary and finite field arithmetic architectures, details VHDL-based implementation approaches, and more.
Signal processing is a broad and timeless area. The term "signal" includes audio, video, speech, image, communication, geophysical, sonar, radar, medical, and more. Signal processing applies to the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.
Presenting statistical and stochastic methods for the analysis and design of technological systems in engineering and applied areas, this work documents developments in statistical modelling, identification, estimation and signal processing. The book covers such topics as subspace methods, stochastic realization, state space modelling, and identification and parameter estimation. |
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