Introduction to Statistical Signal Processing by Robert M. Gray
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Introduction to Statistical Signal Processing
By Robert M. Gray

An Introduction to Statistical Signal Processing

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Format: Hardback

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Introduction to Statistical Signal Processing by Robert M. Gray

Book Description

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.

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Book Details

ISBN: 9780521838603
ISBN-10: 0521838606
Format: Hardback
(247mm x 174mm x 27mm)
Pages: 478
Imprint: Cambridge University Press
Publisher: Cambridge University Press
Publish Date: 2-Dec-2004
Country of Publication: United Kingdom

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Books By Author Robert M. Gray

Introduction to Statistical Signal Processing by Robert M. Gray Introduction to Statistical Signal Processing, Paperback (February 2010)

A guide to the essential tools and techniques of statistical signal processing, along with applications.

» View all books by Robert M. Gray

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Author Biography - Robert M. Gray

Robert M. Gray received his PhD from the University of Southern California, and is Professor and Vice Chair of Electrical Engineering at Stanford University. He has written over 200 scientific papers in areas including information theory, applied probability, signal processing, speech and image processing and coding, ergodic thoery, and the theory of Toeplitz matrices. He is a Fellow of the IEEE and the Institute of Mathematical Statistics. Lee D. Davisson received his PhD from Princeton University, and is an Emeritus Professor of Electrical Engineering at the University of Maryland, College Park. He is the author or co-author of three books and over one hundred scientific papers. He is a Fellow of the IEEE.

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