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Author: Boualem Boashash
Publisher: *Halsted Press
Published: 1995
Total Pages: 560
ISBN-13:
DOWNLOAD EBOOK →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.
Author: T. Chonavel
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 334
ISBN-13: 1447101391
DOWNLOAD EBOOK →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.
Author: John G. Proakis
Publisher:
Published: 2002
Total Pages: 584
ISBN-13:
DOWNLOAD EBOOK →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.
Author: Ales Prochazka
Publisher: Springer Science & Business Media
Published: 1998-12-23
Total Pages: 536
ISBN-13: 9780817640422
DOWNLOAD EBOOK →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.
Author: Chrysostomos L. Nikias
Publisher: Prentice Hall
Published: 1993
Total Pages: 570
ISBN-13:
DOWNLOAD EBOOK →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.
Author: Asoke Nandi
Publisher: Springer Science & Business Media
Published: 1999-01-31
Total Pages: 298
ISBN-13: 9780792384427
DOWNLOAD EBOOK →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.
Author: Boualem Boashash
Publisher:
Published: 1995
Total Pages: 560
ISBN-13:
DOWNLOAD EBOOK →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.
Author:
Publisher: IEEE
Published: 1999
Total Pages: 406
ISBN-13: 9780769501406
DOWNLOAD EBOOK →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
Author: Debasis Kundu
Publisher: Springer Science & Business Media
Published: 2012-05-24
Total Pages: 142
ISBN-13: 8132206282
DOWNLOAD EBOOK →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.
Author: Robert M. Gray
Publisher: Cambridge University Press
Published: 2004-12-02
Total Pages: 479
ISBN-13: 1139456288
DOWNLOAD EBOOK →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.
