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Higher Order Statistical Signal Processing
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Book Synopsis Higher-Order Statistical Signal Processing by : Boualem Boashash
Download or read book Higher-Order Statistical Signal Processing written by Boualem Boashash and published by *Halsted Press. This book was released on 1995 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Higher-Order Statistical Signal Processing brings together some most recent innovations in the field of higher-order statistical signal processing. It is structured to provide a comprehensive understanding of the fundamentals of the discipline, as well as a treatment of recent advances.
Book Synopsis Algorithms for Statistical Signal Processing by : John G. Proakis
Download or read book Algorithms for Statistical Signal Processing written by John G. Proakis and published by . This book was released on 2002 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keeping pace with the expanding, ever more complex applications of DSP, this authoritative presentation of computational algorithms for statistical signal processing focuses on "advanced topics" ignored by other books on the subject. Algorithms for Convolution and DFT. Linear Prediction and Optimum Linear Filters. Least-Squares Methods for System Modeling and Filter Design. Adaptive Filters. Recursive Least-Squares Algorithms for Array Signal Processing. QRD-Based Fast Adaptive Filter Algorithms. Power Spectrum Estimation. Signal Analysis with Higher-Order Spectra. For Electrical Engineers, Computer Engineers, Computer Scientists, and Applied Mathematicians.
Book Synopsis An Introduction to Statistical Signal Processing by : Robert M. Gray
Download or read book An Introduction to Statistical Signal Processing written by Robert M. Gray and published by Cambridge University Press. This book was released on 2004-12-02 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.
Book Synopsis Signal Analysis and Prediction by : Ales Prochazka
Download or read book Signal Analysis and Prediction written by Ales Prochazka and published by Springer Science & Business Media. This book was released on 1998-12-23 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods of signal analysis represent a broad research topic with applications in many disciplines, including engineering, technology, biomedicine, seismography, eco nometrics, and many others based upon the processing of observed variables. Even though these applications are widely different, the mathematical background be hind them is similar and includes the use of the discrete Fourier transform and z-transform for signal analysis, and both linear and non-linear methods for signal identification, modelling, prediction, segmentation, and classification. These meth ods are in many cases closely related to optimization problems, statistical methods, and artificial neural networks. This book incorporates a collection of research papers based upon selected contri butions presented at the First European Conference on Signal Analysis and Predic tion (ECSAP-97) in Prague, Czech Republic, held June 24-27, 1997 at the Strahov Monastery. Even though the Conference was intended as a European Conference, at first initiated by the European Association for Signal Processing (EURASIP), it was very gratifying that it also drew significant support from other important scientific societies, including the lEE, Signal Processing Society of IEEE, and the Acoustical Society of America. The organizing committee was pleased that the re sponse from the academic community to participate at this Conference was very large; 128 summaries written by 242 authors from 36 countries were received. In addition, the Conference qualified under the Continuing Professional Development Scheme to provide PD units for participants and contributors.
Book Synopsis Blind Estimation Using Higher-Order Statistics by : Asoke Nandi
Download or read book Blind Estimation Using Higher-Order Statistics written by Asoke Nandi and published by Springer Science & Business Media. This book was released on 1999-01-31 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the signal-processing research community, a great deal of progress in higher-order statistics (HOS) began in the mid-1980s. These last fifteen years have witnessed a large number of theoretical developments as well as real applications. Blind Estimation Using Higher-Order Statistics focuses on the blind estimation area and records some of the major developments in this field. Blind Estimation Using Higher-Order Statistics is a welcome addition to the few books on the subject of HOS and is the first major publication devoted to covering blind estimation using HOS. The book provides the reader with an introduction to HOS and goes on to illustrate its use in blind signal equalisation (which has many applications including (mobile) communications), blind system identification, and blind sources separation (a generic problem in signal processing with many applications including radar, sonar and communications). There is also a chapter devoted to robust cumulant estimation, an important problem where HOS results have been encouraging. Blind Estimation Using Higher-Order Statistics is an invaluable reference for researchers, professionals and graduate students working in signal processing and related areas.
Book Synopsis Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, June 14-16, 1999, Caesarea, Israel by :
Download or read book Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, June 14-16, 1999, Caesarea, Israel written by and published by IEEE. This book was released on 1999 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains papers from a June 1999 workshop, covering theories, techniques, implementations, and applications of statistical signal processing, with particular emphasis on methods involving the use of higher order statistics (HOS). Papers represent the latest advances in areas of signal processing for communications, convolutive mixtures, HOS-based signal processing theory and methods, heavy-tailed models and processing, Bayesian methods of signal processing, non-stationary signal processing, and HOS-signal processing applications. Specific subjects include higher-order statistical models of visual images, cumulant matrix subspace algorithms for blind single FIR channel identification, and Bayesian wavelet denoising using Besov priors. Lacks a subject index. Annotation copyrighted by Book News, Inc., Portland, OR
Book Synopsis Statistical Signal Processing by : Debasis Kundu
Download or read book Statistical Signal Processing written by Debasis Kundu and published by Springer Science & Business Media. This book was released on 2012-05-24 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal processing may broadly be considered to involve the recovery of information from physical observations. The received signal is usually disturbed by thermal, electrical, atmospheric or intentional interferences. Due to the random nature of the signal, statistical techniques play an important role in analyzing the signal. Statistics is also used in the formulation of the appropriate models to describe the behavior of the system, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Statistical signal processing basically refers to the analysis of random signals using appropriate statistical techniques. The main aim of this book is to introduce different signal processing models which have been used in analyzing periodic data, and different statistical and computational issues involved in solving them. We discuss in detail the sinusoidal frequency model which has been used extensively in analyzing periodic data occuring in various fields. We have tried to introduce different associated models and higher dimensional statistical signal processing models which have been further discussed in the literature. Different real data sets have been analyzed to illustrate how different models can be used in practice. Several open problems have been indicated for future research.
Book Synopsis Statistical Signal Processing by : T. Chonavel
Download or read book Statistical Signal Processing written by T. Chonavel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The only book on the subject at this level, this is a well written formalised and concise presentation of the basis of statistical signal processing. It teaches a wide variety of techniques, demonstrating how they can be applied to many different situations.
Book Synopsis Higher-order Spectra Analysis by : Chrysostomos L. Nikias
Download or read book Higher-order Spectra Analysis written by Chrysostomos L. Nikias and published by Prentice Hall. This book was released on 1993 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: This manual will be valuable to practicing engineers who need an introduction to polyspectra from a signal processing perspective. In response to the recent growth of interest in polyspectra, this timely text provides an introduction to signal processing methods that are based on polyspectra and cumulants concepts. The emphasis of the book is placed on the presentation of signal processing tools for use in situations where the more common power spectrum estimation techniques fall short.
Book Synopsis Introduction to Applied Statistical Signal Analysis by : Richard Shiavi
Download or read book Introduction to Applied Statistical Signal Analysis written by Richard Shiavi and published by Elsevier. This book was released on 2010-07-19 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Applied Statistical Signal Analysis, Third Edition, is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech. Topics presented include mathematical bases, requirements for estimation, and detailed quantitative examples for implementing techniques for classical signal analysis. This book includes over one hundred worked problems and real world applications. Many of the examples and exercises use measured signals, most of which are from the biomedical domain. The presentation style is designed for the upper level undergraduate or graduate student who needs a theoretical introduction to the basic principles of statistical modeling and the knowledge to implement them practically. Includes over one hundred worked problems and real world applications. Many of the examples and exercises in the book use measured signals, many from the biomedical domain.
Book Synopsis Genomic Signal Processing and Statistics by : Edward R. Dougherty
Download or read book Genomic Signal Processing and Statistics written by Edward R. Dougherty and published by Hindawi Publishing Corporation. This book was released on 2005 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in genomic studies have stimulated synergetic research and development in many cross-disciplinary areas. Processing the vast genomic data, especially the recent large-scale microarray gene expression data, to reveal the complex biological functionality, represents enormous challenges to signal processing and statistics. This perspective naturally leads to a new field, genomic signal processing (GSP), which studies the processing of genomic signals by integrating the theory of signal processing and statistics. Written by an international, interdisciplinary team of authors, this invaluable edited volume is accessible to students just entering this emergent field, and to researchers, both in academia and in industry, in the fields of molecular biology, engineering, statistics, and signal processing. The book provides tutorial-level overviews and addresses the specific needs of genomic signal processing students and researchers as a reference book. The book aims to address current genomic challenges by exploiting potential synergies between genomics, signal processing, and statistics, with special emphasis on signal processing and statistical tools for structural and functional understanding of genomic data. The first part of this book provides a brief history of genomic research and a background introduction from both biological and signal-processing/statistical perspectives, so that readers can easily follow the material presented in the rest of the book. In what follows, overviews of state-of-the-art techniques are provided. We start with a chapter on sequence analysis, and follow with chapters on feature selection, classification, and clustering of microarray data. We then discuss the modeling, analysis, and simulation of biological regulatory networks, especially gene regulatory networks based on Boolean and Bayesian approaches. Visualization and compression of gene data, and supercomputer implementation of genomic signal processing systems are also treated. Finally, we discuss systems biology and medical applications of genomic research as well as the future trends in genomic signal processing and statistics research.
Book Synopsis Statistical Signal Processing by : Louis L. Scharf
Download or read book Statistical Signal Processing written by Louis L. Scharf and published by Prentice Hall. This book was released on 1991 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book embraces the many mathematical procedures that engineers and statisticians use to draw inference from imperfect or incomplete measurements. This book presents the fundamental ideas in statistical signal processing along four distinct lines: mathematical and statistical preliminaries; decision theory; estimation theory; and time series analysis.
Book Synopsis Statistical Signal Processing for Neuroscience and Neurotechnology by : Karim G. Oweiss
Download or read book Statistical Signal Processing for Neuroscience and Neurotechnology written by Karim G. Oweiss and published by Academic Press. This book was released on 2010-09-22 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents new theory, algorithms, software and hardware tools that are specifically tailored to the nature of the neurobiological environment. It gives a broad overview of the basic principles, theories and methods in statistical signal processing for basic and applied neuroscience problems. Written by experts in the field, the book is an ideal reference for researchers working in the field of neural engineering, neural interface, computational neuroscience, neuroinformatics, neuropsychology and neural physiology. By giving a broad overview of the basic principles, theories and methods, it is also an ideal introduction to statistical signal processing in neuroscience. A comprehensive overview of the specific problems in neuroscience that require application of existing and development of new theory, techniques, and technology by the signal processing community Contains state-of-the-art signal processing, information theory, and machine learning algorithms and techniques for neuroscience research Presents quantitative and information-driven science that has been, or can be, applied to basic and translational neuroscience problems
Book Synopsis Fundamentals of Statistical Signal Processing by : Steven M. Kay
Download or read book Fundamentals of Statistical Signal Processing written by Steven M. Kay and published by Pearson Education. This book was released on 2013 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: "For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.
Book Synopsis Nonlinear Signal Processing by : Gonzalo R. Arce
Download or read book Nonlinear Signal Processing written by Gonzalo R. Arce and published by John Wiley & Sons. This book was released on 2005-01-03 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Signal Processing: A Statistical Approach focuses on unifying the study of a broad and important class of nonlinear signal processing algorithms which emerge from statistical estimation principles, and where the underlying signals are non-Gaussian, rather than Gaussian, processes. Notably, by concentrating on just two non-Gaussian models, a large set of tools is developed that encompass a large portion of the nonlinear signal processing tools proposed in the literature over the past several decades. Key features include: * Numerous problems at the end of each chapter to aid development and understanding * Examples and case studies provided throughout the book in a wide range of applications bring the text to life and place the theory into context * A set of 60+ MATLAB software m-files allowing the reader to quickly design and apply any of the nonlinear signal processing algorithms described in the book to an application of interest is available on the accompanying FTP site.
Book Synopsis Statistical Signal Processing of Complex-Valued Data by : Peter J. Schreier
Download or read book Statistical Signal Processing of Complex-Valued Data written by Peter J. Schreier and published by Cambridge University Press. This book was released on 2010-02-04 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex-valued random signals are embedded in the very fabric of science and engineering, yet the usual assumptions made about their statistical behavior are often a poor representation of the underlying physics. This book deals with improper and noncircular complex signals, which do not conform to classical assumptions, and it demonstrates how correct treatment of these signals can have significant payoffs. The book begins with detailed coverage of the fundamental theory and presents a variety of tools and algorithms for dealing with improper and noncircular signals. It provides a comprehensive account of the main applications, covering detection, estimation, and signal analysis of stationary, nonstationary, and cyclostationary processes. Providing a systematic development from the origin of complex signals to their probabilistic description makes the theory accessible to newcomers. This book is ideal for graduate students and researchers working with complex data in a range of research areas from communications to oceanography.
Book Synopsis Discrete Random Signals and Statistical Signal Processing by : Charles W. Therrien
Download or read book Discrete Random Signals and Statistical Signal Processing written by Charles W. Therrien and published by . This book was released on 1992 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
