An Introduction To Statistical Communication Theory (An Ieee Press Classic Reissue)

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.)

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.

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).

AN INTRODUCTION TO STATISTICAL COMMUNICATION THEORY.

Statistical Preliminaries.

Operations on Ensembles.

Spectra, Covariance, and Correlation Functions.

Sampling, Interpolation, and Random Pulse Trains.

Signals and Noise in Nonlinear Systems.

An Introduction to Information Theory.

RANDOM NOISE PROCESSES.

The Normal Random Process: Gaussian Variates.

The Normal Random Process: Gaussian Functionals.

Processes Derived from the Normal.

The Equations of Langevin, Fokker-Planck, and Boltzmann.

Thermal, Shot, and Impulse Noise.

APPLICATIONS TO SPECIAL SYSTEMS.

Amplitude Modulation and Conversion.

Rectification of Amplitude-modulated Waves: Second-momentTheory.

Phase and Frequency Modulation.

Detection of Frequency-modulated Waves: Second-moment Theory.

Linear Measurements, Prediction, and Optimum Filtering.

Some Distribution Problems.

A STATISTICAL THEORY OF RECEPTION.

Reception as a Decision Problem.

Binary Detection Systems Minimizing Average Risk. General Theory.

Binary Detection Systems Minimizing Average Risk. Examples.

Extraction Systems Minimizing Average Risk;
Signal Analysis.

Information Measures in Reception.

Generalizations and Extensions.

Appendix 1. Special Functions and Integrals.

Appendix 2. Solutions of Selected Integral Equations.

Supplementary References and Bibliography.

Selected Supplementary References (1996).

Name Index to Selected Supplementary References.

Glossary of Principal Symbols.

Name Index.

Subject Index.

Author's Biography.