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An Introduction to Statistical Communication Theory

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This IEEE Classic Reissue provides at an advanced level, a uniquely fundamental exposition of the applications of Statistical Communication Theory to a vast spectrum of important physical problems. Included are general analysis of signal detection, estimation, measurement, and related topics involving information transfer.

Using the statistical Bayesian viewpoint, renowned author David Middleton employs statistical decision theory specifically tailored for the general tasks of ...

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Overview

This IEEE Classic Reissue provides at an advanced level, a uniquely fundamental exposition of the applications of Statistical Communication Theory to a vast spectrum of important physical problems. Included are general analysis of signal detection, estimation, measurement, and related topics involving information transfer.

Using the statistical Bayesian viewpoint, renowned author David Middleton employs statistical decision theory specifically tailored for the general tasks of signal processing. Dr. Middleton also provides a special focus on physical modeling of the canonical channel with real-world examples relating to radar, sonar, and general telecommunications. This book offers a detailed treatment and an array of problems and results spanning an exceptionally broad range of technical subjects in the communications field.

Complete with special functions, integrals, solutions of integral equations, and an extensive, updated bibliography by chapter, An Introduction to Statistical Communication Theory is a seminal reference, particularly for anyone working in the field of communications, as well as in other areas of statistical physics. (Originally published in 1960.)

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Editorial Reviews

Booknews
An advanced level treatment of the applications of statistical communication theory to various physical problems, originally published in 1960 by McGraw-Hill, Inc. Coverage includes signal detection, estimation, and information transfer, plus statistical decision theory via the Bayesian statistical viewpoint, and special focus on physical modeling of the canonical channel with real-world examples involving radar, sonar, and general telecommunications applications. Useful as a reference for anyone working in the field of communications, as well as in other areas of statistical physics. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780932146151
  • Publisher: Peninsula Publishing
  • Publication date: 6/1/1987
  • Pages: 1140

Meet the Author

David Middleton is a consulting physicist, applied mathematician, educator and author who is an internationally recognized pioneer in statistical communication theory, a field in which he has been active for more than fifty years. He is author of Topics in Communication Theory (1965–1967, 1987-) and more than 160 papers. Dr. Middleton is currently Adjunct Professor of Electrical Engineering at the University of Rhode Island.
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Table of Contents

Foreword to the IEEE PRESS Reissue
Preface to the Second Reprint Edition (1996)
Preface to the First Reprint Edition (1987-1995)
Preface to the First Edition (1960)
Ch. 1 Statistical Preliminaries 3
Ch. 2 Operations on Ensembles 65
Ch. 3 Spectra, Covariance, and Correlation Functions 124
Ch. 4 Sampling, Interpolation, and Random Pulse Trains 200
Ch. 5 Signals and Noise in Nonlinear Systems 239
Ch. 6 An Introduction to Information Theory 290
Ch. 7 The Normal Random Process: Gaussian Variates 335
Ch. 8 The Normal Random Process: Gaussian Functionals 369
Ch. 9 Processes Derived from the Normal 396
Ch. 10 The Equations of Langevin, Fokker-Planck, and Boltzmann 438
Ch. 11 Thermal, Shot, and Impulse Noise 467
Ch. 12 Amplitude Modulation and Conversion 513
Ch. 13 Rectification of Amplitude-modulated Waves: Second-moment Theory 539
Ch. 14 Phase and Frequency Modulation 599
Ch. 15 Detection of Frequency-modulated Waves; Second-moment Theory 636
Ch. 16 Linear Measurements, Prediction, and Optimum Filtering 679
Ch. 17 Some Distribution Problems 723
Ch. 18 Reception as a Decision Problem 773
Ch. 19 Binary Detection Systems Minimizing Average Risk. General Theory 801
Ch. 20 Binary Detection Systems Minimizing Average Risk. Examples 834
Ch. 21 Extraction Systems Minimizing Average Risk; Signal Analysis 940
Ch. 22 Information Measures in Reception 1008
Ch. 23 Generalizations and Extensions 1024
Appendix 1. Special Functions and Integrals 1071
Appendix 2. Solutions of Selected Integral Equations 1082
Supplementary References and Bibliography 1103
Selected Supplementary References (1996) 1111
Name Index to Selected Supplementary References 1119
Glossary of Principal Symbols 1121
Name Index 1131
Subject Index 1137
Author's Biography 1151
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