Fundamentals Of Statistical Signal Processing Volume Iii
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Fundamentals Of Statistical Signal Processing Detection Theory
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Author : Steven M. Kay
language : en
Publisher: Pearson
Release Date : 1998
Fundamentals Of Statistical Signal Processing Detection Theory written by Steven M. Kay and has been published by Pearson this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.
V.2 Detection theory -- V.1 Estimation theory.
Fundamentals Of Statistical Signal Processing Volume Iii
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Author : Steven M. Kay
language : en
Publisher: Prentice Hall
Release Date : 2013-04-05
Fundamentals Of Statistical Signal Processing Volume Iii written by Steven M. Kay and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-05 with Technology & Engineering categories.
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).
Statistical Digital Signal Processing And Modeling
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Author : Monson H. Hayes
language : en
Publisher: John Wiley & Sons
Release Date : 1996-04-19
Statistical Digital Signal Processing And Modeling written by Monson H. Hayes and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-04-19 with Technology & Engineering categories.
This new text responds to the dramatic growth in digital signal processing (DSP) over the past decade, and is the product of many years of teaching an advanced DSP course at Georgia Tech. While the focal point of the text is signal modeling, it integrates and explores the relationships of signal modeling to the important problems of optimal filtering, spectrum estimation, and adaptive filtering. Coverage is equally divided between the theory and philosophy of statistical signal processing, and the algorithms that are used to solve related problems. The text reflects the author's philosophy that a deep understanding of signal processing is accomplished best through working problems. For this reason, the book is loaded with worked examples, homework problems, and MATLAB computer exercises. While the examples serve to illustrate the ideas developed in the book, the problems seek to motivate and challenge the student and the computer exercises allow the student to experiment with signal processing algorithms on complex signals. Professor Hayes is recognized as a leader in the signal processing community, particularly for his work in signal reconstruction and image processing. This text is suitable for senior/graduate level courses in advanced DSP or digital filtering found in Electrical Engineering Departments. Prerequisites include basic courses in DSP and probability theory.
Fundamentals Of Statistical Signal Processing
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Author : Steven Kay
language : en
Publisher:
Release Date : 2013
Fundamentals Of Statistical Signal Processing written by Steven Kay and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Engineering categories.
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).
Modern Spectral Estimation
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Author : Steven M. Kay
language : en
Publisher: Prentice-Hall PTR
Release Date : 1999-03-01
Modern Spectral Estimation written by Steven M. Kay and has been published by Prentice-Hall PTR this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-03-01 with Education categories.
Probability Random Processes And Statistical Analysis
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Author : Hisashi Kobayashi
language : en
Publisher: Cambridge University Press
Release Date : 2011-12-15
Probability Random Processes And Statistical Analysis written by Hisashi Kobayashi and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-15 with Technology & Engineering categories.
Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities, bound and approximation, maximum-likelihood estimation and the expectation-maximization (EM) algorithm, geometric Brownian motion and Itô process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum–Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, and queueing and loss networks are treated in detail. The book will be useful to students and researchers in such areas as communications, signal processing, networks, machine learning, bioinformatics, econometrics and mathematical finance. With a solutions manual, lecture slides, supplementary materials and MATLAB programs all available online, it is ideal for classroom teaching as well as a valuable reference for professionals.
Algorithms For Statistical Signal Processing
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Author : John G. Proakis
language : en
Publisher:
Release Date : 2002
Algorithms For Statistical Signal Processing written by John G. Proakis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
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.
Statistical And Adaptive Signal Processing
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Author : Dimitris G. Manolakis
language : en
Publisher: Artech House Publishers
Release Date : 2005
Statistical And Adaptive Signal Processing written by Dimitris G. Manolakis and has been published by Artech House Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with COMPUTERS categories.
This authoritative volume on statistical and adaptive signal processing offers you a unified, comprehensive and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. Packed with over 3,000 equations and more than 300 illustrations, this unique resource provides you with balanced coverage of implementation issues, applications, and theory, making it a smart choice for professional engineers and students alike.
Multivariate Statistical Analysis
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Author : Parimal Mukhopadhyay
language : en
Publisher: World Scientific
Release Date : 2009
Multivariate Statistical Analysis written by Parimal Mukhopadhyay and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Mathematics categories.
"This textbook presents a classical approach to some techniques of multivariate analysis in a simple and transparent manner. It offers clear and concise development of the concepts; interpretation of the output of the analysis; and criteria for selection of the methods, taking into account the strengths and weaknesses of each." "This book is ideal as an advanced textbook for graduate students in statistics and other disciplines like social, biological and physical sciences. It will also be of benefit to professional statisticians." --Book Jacket.
A First Course In Statistics For Signal Analysis
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Author : Wojbor A. Woyczyński
language : en
Publisher: Birkhäuser
Release Date : 2019-10-17
A First Course In Statistics For Signal Analysis written by Wojbor A. Woyczyński and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-17 with Mathematics categories.
This self-contained and user-friendly textbook is designed for a first, one-semester course in statistical signal analysis for a broad audience of students in engineering and the physical sciences. The emphasis throughout is on fundamental concepts and relationships in the statistical theory of stationary random signals, which are explained in a concise, yet rigorous presentation. With abundant practice exercises and thorough explanations, A First Course in Statistics for Signal Analysis is an excellent tool for both teaching students and training laboratory scientists and engineers. Improvements in the second edition include considerably expanded sections, enhanced precision, and more illustrative figures.