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Books > Computing & IT > Applications of computing > Signal processing
Identification of Time-Varying Processes offers a comprehensive
treatment of the key issue in adaptive systems: tracking of
time-varying system parameters. Time-varying identification
techniques facilitate many challenging applications in different
areas including telecommunications (channel equalization,
predictive coding of signals, adaptive noise reduction and echo
cancellation) and automatic control (adaptive control and failure
detection). The processes also assist signal processing in areas
such as adaptive noise reduction, prediction of time series,
restoration of archive audio recordings and spectrum estimation.
Includes:
"Multiscale Signal Analysis and Modeling" presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory.
Analysis, design, and realization of digital filters have experienced major developments since the 1970s, and have now become an integral part of the theory and practice in the field of contemporary digital signal processing. Digital Filter Design and Realization is written to present an up-to-date and comprehensive account of the analysis, design, and realization of digital filters. It is intended to be used as a text for graduate students as well as a reference book for practitioners in the field. Prerequisites for this book include basic knowledge of calculus, linear algebra, signal analysis, and linear system theory. Technical topics discussed in the book include: Discrete-Time Systems and z-Transformation Stability and Coefficient Sensitivity State-Space Models FIR Digital Filter Design Frequency-Domain Digital Filter Design Time-Domain Digital Filter Design Interpolated and Frequency-Response-Masking FIR Digital Filter Design Composite Digital Filter Design Finite Word Length Effects Coefficient Sensitivity Analysis and Minimization Error Spectrum Shaping Roundoff Noise Analysis and Minimization Generalized Transposed Direct-Form II Block-State Realization
Compressed Sensing in Li-Fi and Wi-Fi Networks features coverage of the first applications in optical telecommunications and wireless. After extensive development of basic theory, many techniques are presented, such as non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and the use of graphical models. The book can be used as a comprehensive manual for teaching and research in courses covering advanced signal processing, efficient data processing algorithms, and telecommunications. After a thorough review of the basic theory of compressed sensing, many mathematical techniques are presented, including advanced signal modeling, Nyquist sub-sampling of analog signals, the non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and the use of graphical models.
Blending theoretical results with practical applications, this book provides an introduction to random matrix theory and shows how it can be used to tackle a variety of problems in wireless communications. The Stieltjes transform method, free probability theory, combinatoric approaches, deterministic equivalents and spectral analysis methods for statistical inference are all covered from a unique engineering perspective. Detailed mathematical derivations are presented throughout, with thorough explanation of the key results and all fundamental lemmas required for the reader to derive similar calculus on their own. These core theoretical concepts are then applied to a wide range of real-world problems in signal processing and wireless communications, including performance analysis of CDMA, MIMO and multi-cell networks, as well as signal detection and estimation in cognitive radio networks. The rigorous yet intuitive style helps demonstrate to students and researchers alike how to choose the correct approach for obtaining mathematically accurate results.
This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random processes and signal modelling are discussed with basic communication theory estimation and detection. MATLAB simulations are included for each concept with output of the program with case studies and project ideas. The chapters progressively introduce and explain the concepts of random signals and cover multiple applications for signal processing. The book is designed to cater to a wide audience starting from the undergraduates (electronics, electrical, instrumentation, computer, and telecommunication engineering) to the researchers working in the pertinent fields. Key Features: * Aimed at random signal processing with parametric signal processing-using appropriate segment size. * Covers speech, image, medical images, EEG and ECG signal processing. * Reviews optimal detection and estimation. * Discusses parametric modeling and signal processing in transform domain. * Includes MATLAB codes and relevant exercises, case studies and solved examples including multiple choice questions
The considerable growth of RFID is currently accompanied by the development of numerous identification technologies that complement those already available while seeking to answer new problems. Chipless RFID is one example. The goal is to both significantly reduce the price of the tag and increase the amount of information it contains, in order to compete with the barcode while retaining the benefits of a flexible reading approach based on radio communication. To solve the problem of the number of bits, this book describes the possibility of coding the information at the level of the overall shape of the RCS of the tag, which would facilitate reaching very large quantities. The design of the tags then returns to the resolution of the inverse problem of the electromagnetic signature. The proposed design methodology regularizes the problem by decomposing the signature on a basis of elementary patterns whose signature is chosen in advance.
Your cutting-edge introduction to radar signal processing-fully updated for the latest advances This up-to-date guide provides in-depth coverage of the full breadth of foundational radar signal processing methods of waveform design, Doppler processing, detection, tracking, imaging, and adaptive processing from a digital signal processing perspective. The techniques of linear systems, filtering, sampling, and Fourier analysis are used throughout to provide a unified tutorial approach. Developed from the author's extensive academic and professional experience, Fundamentals of Radar Signal Processing, Third Edition has been revised and updated throughout. Readers will find the solid foundations of earlier editions enhanced with new material on such topics as keystone formatting, detection in spiky clutter, range migration and backprojection imaging, virtual arrays, ground moving target indication, and many more. Presents complete coverage of foundational digital radar signal processing techniques Integrates linear FMCW techniques of emerging fields such as automotive radar with pulsed methods Includes additional homework problems in all chapters Comes with an online suite of answer keys, solutions manuals, tutorial MATLAB demos, and technical notes
Artificial Vision is a rapidly growing discipline, aiming to build
computational models of the visual functionalities in humans, as
well as machines that emulate them. Visual communication in itself
involves a numberof challenging topics with a dramatic impact on
contemporary culture where human-computer interaction and human
dialogue play a more and more significant role.
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
Spectacular advances during the last decade have altered the
related disciplines of computing and telecommunications beyond all
recognition. The developments in the"enabling technologies,"which
have made these advances possible, have been less obvious to the
casual observer. The subject of this book is one of these
technologies--the coding of still images and picture sequences
(video).
The rapid advancements in image communication technologies are documented in the book series, Advances in Image Communication. Each publication provides an in-depth exploration of an intrinsic element of the multi-disciplinary field and together they form a comprehensive overview of the whole. This volume, the fifth in the series, examines the definition, study and use of the wavelet transform in communications for two-dimensional (2-D) digital signals. The transform is used for signal reorganization before compression and the trade-off between these two steps and the whole compression process is discussed. The five chapters specifically present the theory of wavelets applied to images, then applications of compression of still images and sequences. Chapter 1 introduces biorthogonal bases of compactly supported wavelets: this generalization of orthonormal wavelet theory allows the use of linear phase filters. A non rectangular wavelet representation of 2-D signals is developed in the second chapter: the properties usually used with wavelets, phase, linearity, and regularity are discussed. Chapter 3 is composed of three parts: a description of commonly used biorthogonal wavelets; a presentation of vector quantization algorithms; a consideration of lattice vector quantization followed by a discussion of the bit allocation procedure (with experimental results given). The fourth chapter deals with a region-based discrete wavelet transform for image coding. Chapter 5 investigates the transmission of image sequences: wavelet transforms and motion estimation are detailed in a multiconstraint approach of image sequence coding.
Image communication technologies have advanced rapidly in recent years and the book series, Advances in Image Communication is dedicated to documenting these developments. Third in the series, this publication contributes as effectively as its forerunners to the multidisciplinary overview afforded by the series as a whole. At the same time, it stands alone as a comprehensive synopsis of its own particular area of interest. The book specifically explores two complementary topics, namely: the coding algorithms made to compress the data rate of digital moving-picture sequences (video-telephony, television TV] and high-definition television HDTV]) and the transmission on Asynchronous Transfer Mode ATM] networks (packet-switching transmission media). It provides an in-depth view of the current state-of-the-art and endeavors to stimulate increasing research efforts for the future.
Multiculturalism and diversity have raised a number of challenges for liberal democracy, not least the stigmatization of people in response to these developments. In this book, leading experts from a range of disciplines look at the responses to stigmatization from the perspectives of ordinary people. They use a range of case studies drawn from the US, Brazil, Canada, France, Israel, South Africa, and Sweden: the first systematic qualitative and cross-national exploration of how diverse minority groups respond to stigmatization in the course of their everyday lives. The chapters in this book tackle a range of theoretical questions about stigmatization, including how they make sense of their experiences, how they shape subsequent behaviour, and how they negotiate and transform social and symbolic boundaries within a range of social and institutional contexts. Responses to Stigmatization in Comparative Perspective provides new data and analysis of how stigmatization affects a range of societies, and its original research and analysis will be important reading for those studying Ethnicity, as well as Sociologists, Political Scientists, and Anthropologists. This book was originally published as a special issue of Ethnic and Racial Studies.
The design and construction of three-dimensional 3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains.
Providing specific knowledge in the theory of image analysis, optics, fluorescence, and imaging devices in biomedical laboratories, this timely and indispensable volume focuses on the theory and applications of detection, morphometry, and motility measurement techniques applied to bacteria, fungi, yeasts and protozoa.
Drawing from physics and philosophical debates, Ismael combines a set of essays on the time worn debate of symmetry from both fields.
With signal combining and detection methods now representing a key application of signal processing in communication systems, this book provides a range of key techniques for receiver design when multiple received signals are available. Various optimal and suboptimal signal combining and detection techniques are explained in the context of multiple-input multiple-output (MIMO) systems, including successive interference cancellation (SIC) based detection and lattice reduction (LR) aided detection. The techniques are then analyzed using performance analysis tools. The fundamentals of statistical signal processing are also covered, with two chapters dedicated to important background material. With a carefully balanced blend of theoretical elements and applications, this book is ideal for both graduate students and practising engineers in wireless communications.
Gain a detailed understanding of the protocols, network architectures and techniques being considered for 5G wireless networks with this authoritative guide to the state of the art. * Get up to speed with key topics such as cloud radio access networks, mobile edge computing, full duplexing, massive MIMO, mmWave, NOMA, Internet of things, M2M communications, D2D communications, mobile data offloading, interference mitigation techniques, radio resource management, visible light communications, and smart data pricing. * Learn from leading researchers in academia and industry about the most recent theoretical developments in the field. * Discover how each potential technology can increase the capacity, spectral efficiency, and energy efficiency of wireless systems. Providing the most comprehensive overview of 5G technologies to date, this is an essential reference for researchers, practicing engineers and graduate students working in wireless communications and networking.
A Unique, Cutting-Edge Approach to Optical Filter Design With more and more information being transmitted over fiber-optic lines, optical filtering has become crucial to the advanced functionality of today’s communications networks. Helping researchers and engineers keep pace with this rapidly evolving technology, this book presents digital processing techniques for optical filter design. This higher-level approach focuses on filter characteristics and enables readers to quickly calculate the filter response as well as tackle larger and more complex filters. The authors incorporate numerous theoretical and experimental results from the literature and discuss applications to a variety of systems—including the new wavelength division multiplexing (WDM) technology, which is fast becoming the preferred method for system upgrade and expansion. Special features of this book include:
A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.
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 first volume, Theories and Applications, Leung Tsang (University of Washington) Jin Au Kong (MIT), and Kung-Hau Ding (Air Force Research Lab) cover:
Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate- or graduate-level understanding of mathematics-including familiarity with Fourier series, matrices, probability, and statistics-this Second Edition: Contains new chapters on convolution and the vector DFT, plane-wave propagation, and the BLUE and Kalman filters Expands the material on Fourier analysis to three new chapters to provide additional background information Presents real-world examples of applications that demonstrate how mathematics is used in remote sensing Featuring problems for use in the classroom or practice, Signal Processing: A Mathematical Approach, Second Edition covers topics such as Fourier series and transforms in one and several variables; applications to acoustic and electro-magnetic propagation models, transmission and emission tomography, and image reconstruction; sampling and the limited data problem; matrix methods, singular value decomposition, and data compression; optimization techniques in signal and image reconstruction from projections; autocorrelations and power spectra; high-resolution methods; detection and optimal filtering; and eigenvector-based methods for array processing and statistical filtering, time-frequency analysis, and wavelets.
This book provides the reader with empirical findings on innovative signal processing approaches to detecting pathologies in infant cries, by comparing new technological approaches to standard ones. The contributors examine novel approaches to machine adaptation to dysarthric speech.
This book provides a full representation of Inverse Synthetic Aperture Radar (ISAR) imagery, which is a popular and important radar signal processing tool. The book covers all possible aspects of ISAR imaging. The book offers a fair amount of signal processing techniques and radar basics before introducing the inverse problem of ISAR and the forward problem of Synthetic Aperture Radar (SAR). Important concepts of SAR such as resolution, pulse compression and image formation are given together with associated MATLAB codes. After providing the fundamentals for ISAR imaging, the book gives the detailed imaging procedures for ISAR imaging with associated MATLAB functions and codes. To enhance the image quality in ISAR imaging, several imaging tricks and fine-tuning procedures such as zero-padding and windowing are also presented. Finally, various real applications of ISAR imagery, like imaging the antenna-platform scattering, are given in a separate chapter. For all these algorithms, MATLAB codes and figures are included. The final chapter considers advanced concepts and trends in ISAR imaging. |
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