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Book Synopsis Fundamentals of Statistical Signal Processing: Detection theory by : Steven M. Kay
Download or read book Fundamentals of Statistical Signal Processing: Detection theory written by Steven M. Kay and published by Pearson. This book was released on 1998 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: V.2 Detection theory -- V.1 Estimation theory.
Book Synopsis Fundamentals Of Statistical Processing, Volume 2: Detection Theory by : Steven M. Kay
Download or read book Fundamentals Of Statistical Processing, Volume 2: Detection Theory written by Steven M. Kay and published by Pearson Education India. This book was released on 2009-09 with total page 580 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. Authoer 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 Fundamentals of Statistical Signal Processing by : Steven M. Kay (Statistiek)
Download or read book Fundamentals of Statistical Signal Processing written by Steven M. Kay (Statistiek) and published by . This book was released on 1993 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fundamentals of Statistical Signal Processing: Estimation theory by : Steven M. Kay
Download or read book Fundamentals of Statistical Signal Processing: Estimation theory written by Steven M. Kay and published by . This book was released on 2013 with total page 0 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 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 Optimal Combining and Detection by : Jinho Choi
Download or read book Optimal Combining and Detection written by Jinho Choi and published by Cambridge University Press. This book was released on 2010-01-28 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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 . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fundamentals Of Statistical Processing, Volume 2: Detection Theory by : Steven M. Kay
Download or read book Fundamentals Of Statistical Processing, Volume 2: Detection Theory written by Steven M. Kay and published by Pearson Education India. This book was released on 2009-09 with total page 672 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. Authoer 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 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 Prentice Hall. This book was released on 1993 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fundamentals of Statistical Signal Processing, Volume III by : Steven M. Kay
Download or read book Fundamentals of Statistical Signal Processing, Volume III written by Steven M. Kay and published by Prentice Hall. This book was released on 2013-04-05 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Complete, Modern Guide to Developing Well-Performing Signal Processing Algorithms In Fundamentals of Statistical Signal Processing, Volume III: Practical Algorithm Development, author Steven M. Kay shows how to convert theories of statistical signal processing estimation and detection into software algorithms that can be implemented on digital computers. This final volume of Kay’s three-volume guide builds on the comprehensive theoretical coverage in the first two volumes. Here, Kay helps readers develop strong intuition and expertise in designing well-performing algorithms that solve real-world problems. Kay begins by reviewing methodologies for developing signal processing algorithms, including mathematical modeling, computer simulation, and performance evaluation. He links concepts to practice by presenting useful analytical results and implementations for design, evaluation, and testing. Next, he highlights specific algorithms that have “stood the test of time,” offers realistic examples from several key application areas, and introduces useful extensions. Finally, he guides readers through translating mathematical algorithms into MATLAB® code and verifying solutions. Topics covered include Step by step approach to the design of algorithms Comparing and choosing signal and noise models Performance evaluation, metrics, tradeoffs, testing, and documentation Optimal approaches using the “big theorems” Algorithms for estimation, detection, and spectral estimation Complete case studies: Radar Doppler center frequency estimation, magnetic signal detection, and heart rate monitoring Exercises are presented throughout, with full solutions. This new volume is invaluable to engineers, scientists, and advanced students in every discipline that relies on signal processing; researchers will especially appreciate its timely overview of the state of the practical art. Volume III complements Dr. Kay’s Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory (Prentice Hall, 1993; ISBN-13: 978-0-13-345711-7), and Volume II: Detection Theory (Prentice Hall, 1998; ISBN-13: 978-0-13-504135-2).
Book Synopsis Fundamentals of Statistical Signal Processing, Volume 1: Estimation Theory by : Kay
Download or read book Fundamentals of Statistical Signal Processing, Volume 1: Estimation Theory written by Kay and published by Pearson Education India. This book was released on with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fundamentals of Statistical Signal Processing. Vol.2(양장본 HardCover) by : Steven M. Kay
Download or read book Fundamentals of Statistical Signal Processing. Vol.2(양장본 HardCover) written by Steven M. Kay and published by . This book was released on 2012-01-13 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fundamentals of Statistical Signal Processing by : Steven Kay
Download or read book Fundamentals of Statistical Signal Processing written by Steven Kay and published by . This book was released on 2013 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Complete, Modern Guide to Developing Well-Performing Signal Processing Algorithms In Fundamentals of Statistical Signal Processing, Volume III: Practical Algorithm Development, author Steven M. Kay shows how to convert theories of statistical signal processing estimation and detection into software algorithms that can be implemented on digital computers. This final volume of Kay's three-volume guide builds on the comprehensive theoretical coverage in the first two volumes. Here, Kay helps readers develop strong intuition and expertise in designing well-performing algorithms that solve real-world problems. Kay begins by reviewing methodologies for developing signal processing algorithms, including mathematical modeling, computer simulation, and performance evaluation. He links concepts to practice by presenting useful analytical results and implementations for design, evaluation, and testing. Next, he highlights specific algorithms that have "stood the test of time," offers realistic examples from several key application areas, and introduces useful extensions. Finally, he guides readers through translating mathematical algorithms into MATLAB® code and verifying solutions. Topics covered include Step by step approach to the design of algorithms Comparing and choosing signal and noise models Performance evaluation, metrics, tradeoffs, testing, and documentation Optimal approaches using the "big theorems" Algorithms for estimation, detection, and spectral estimation Complete case studies: Radar Doppler center frequency estimation, magnetic signal detection, and heart rate monitoring Exercises are presented throughout, with full solutions. This new volume is invaluable to engineers, scientists, and advanced students in every discipline that relies on signal processing; researchers will especially appreciate its timely overview of the state of the practical art. Volume III complements Dr. Kay's Fundamentals of Statistical Signal Processing, Volume I: Estimation Theory (Prentice Hall, 1993; ISBN-13: 978-0-13-345711-7), and Volume II: Detection Theory (Prentice Hall, 1998; ISBN-13: 978-0-13-504135-2).
Author :Vyacheslav P. Tuzlukov Publisher :Springer Science & Business Media ISBN 13 :146120187X Total Pages :741 pages Book Rating :4.4/5 (612 download)
Book Synopsis Signal Detection Theory by : Vyacheslav P. Tuzlukov
Download or read book Signal Detection Theory written by Vyacheslav P. Tuzlukov and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasing the noise immunity of complex signal processing systems is the main problem in various areas of signal processing. At the present time there are many books and periodical articles devoted to signal detection, but many important problems remain to be solved. New approaches to complex problems allow us not only to summarize investigations, but also to improve the quality of signal detection in noise. This book is devoted to fundamental problems in the generalized approach to signal processing in noise based on a seemingly abstract idea: the introduction of an additional noise source that does not carry any information about the signal in order to improve the qualitative performance of complex signal processing systems. Theoretical and experimental studies carried out by the author lead to the conclusion that the proposed generalized approach to signal processing in noise allows us to formulate a decision-making rule based on the determi nation of the jointly sufficient statistics of the mean and variance of the likelihood function (or functional). Classical and modern signal detection theories allow us to define only the sufficient statistic of the mean of the likelihood function (or functional). The presence of additional information about the statistical characteristics of the like lihood function (or functional) leads to better-quality signal detection in comparison with the optimal signal detection algorithms of classical and modern theories.
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 Digital Signal Processing Fundamentals by : Vijay Madisetti
Download or read book Digital Signal Processing Fundamentals written by Vijay Madisetti and published by CRC Press. This book was released on 2017-12-19 with total page 904 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now available in a three-volume set, this updated and expanded edition of the bestselling The Digital Signal Processing Handbook continues to provide the engineering community with authoritative coverage of the fundamental and specialized aspects of information-bearing signals in digital form. Encompassing essential background material, technical details, standards, and software, the second edition reflects cutting-edge information on signal processing algorithms and protocols related to speech, audio, multimedia, and video processing technology associated with standards ranging from WiMax to MP3 audio, low-power/high-performance DSPs, color image processing, and chips on video. Drawing on the experience of leading engineers, researchers, and scholars, the three-volume set contains 29 new chapters that address multimedia and Internet technologies, tomography, radar systems, architecture, standards, and future applications in speech, acoustics, video, radar, and telecommunications. Emphasizing theoretical concepts, Digital Signal Processing Fundamentals provides comprehensive coverage of the basic foundations of DSP and includes the following parts: Signals and Systems; Signal Representation and Quantization; Fourier Transforms; Digital Filtering; Statistical Signal Processing; Adaptive Filtering; Inverse Problems and Signal Reconstruction; and Time–Frequency and Multirate Signal Processing.
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 . This book was released on 2010 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt:
