An Introduction to Statistical Communication Theory: An IEEE Press Classic Reissue
Autor David Middletonen Limba Engleză Hardback – 24 apr 1996
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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Specificații
ISBN-13: 9780780311787
ISBN-10: 0780311787
Pagini: 1184
Dimensiuni: 156 x 234 x 66 mm
Greutate: 1.65 kg
Ediția:An IEEE Press Classic Reissue
Editura: Wiley-IEEE Press
Locul publicării:Hoboken, United States
ISBN-10: 0780311787
Pagini: 1184
Dimensiuni: 156 x 234 x 66 mm
Greutate: 1.65 kg
Ediția:An IEEE Press Classic Reissue
Editura: Wiley-IEEE Press
Locul publicării:Hoboken, United States
Descriere
" a unique sourcebook in statistical communications no other book treats mathematical and physical foundations of the discipline in the comprehensive, interdisciplinary way found here [it] offers the reader a distinct advantage in terms of understanding, as well as a significant value in terms of compactness of resources."
From the foreword by H. Vincent Poor This IEEE Press Classic Reissue provides an advanced level, yet uniquely fundamental, treatment of the applications of Statistical Communication Theory to a vast spectrum of important physical problems. Included are general treatments of signal detection, estimation, and measurement, and related topics involving information transfer. Using the Bayesian statistical 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 applications. This book offers a detailed treatment and an array of problems and results covering an exceptionally broad range of technical subjects in the communications field, including among others:
From the foreword by H. Vincent Poor This IEEE Press Classic Reissue provides an advanced level, yet uniquely fundamental, treatment of the applications of Statistical Communication Theory to a vast spectrum of important physical problems. Included are general treatments of signal detection, estimation, and measurement, and related topics involving information transfer. Using the Bayesian statistical 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 applications. This book offers a detailed treatment and an array of problems and results covering an exceptionally broad range of technical subjects in the communications field, including among others:
- Specific applications of Fourier as well as single– and two–sided LaPlace transform methods
- Evaluation of covariance functions and intensity spectra
- Signal–to–noise ratios in nonlinear systems
- Sampling and interpolation
- Langevin, Fokker–Planck, and Boltzmann equations
- Amplitude, phase, and frequency modulation by noise and signals
- Detection probabilities
- Optimum estimators
- Minimum detectable signals
- Neyman–Pearson and Ideal Observer detection algorithms
- Multiple alternative detection algorithms and performance measures
Textul de pe ultima copertă
" a unique sourcebook in statistical communications no other book treats mathematical and physical foundations of the discipline in the comprehensive, interdisciplinary way found here [it] offers the reader a distinct advantage in terms of understanding, as well as a significant value in terms of compactness of resources."
From the foreword by H. Vincent Poor This IEEE Press Classic Reissue provides an advanced level, yet uniquely fundamental, treatment of the applications of Statistical Communication Theory to a vast spectrum of important physical problems. Included are general treatments of signal detection, estimation, and measurement, and related topics involving information transfer. Using the Bayesian statistical 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 applications. This book offers a detailed treatment and an array of problems and results covering an exceptionally broad range of technical subjects in the communications field, including among others:
From the foreword by H. Vincent Poor This IEEE Press Classic Reissue provides an advanced level, yet uniquely fundamental, treatment of the applications of Statistical Communication Theory to a vast spectrum of important physical problems. Included are general treatments of signal detection, estimation, and measurement, and related topics involving information transfer. Using the Bayesian statistical 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 applications. This book offers a detailed treatment and an array of problems and results covering an exceptionally broad range of technical subjects in the communications field, including among others:
- Specific applications of Fourier as well as single– and two–sided LaPlace transform methods
- Evaluation of covariance functions and intensity spectra
- Signal–to–noise ratios in nonlinear systems
- Sampling and interpolation
- Langevin, Fokker–Planck, and Boltzmann equations
- Amplitude, phase, and frequency modulation by noise and signals
- Detection probabilities
- Optimum estimators
- Minimum detectable signals
- Neyman–Pearson and Ideal Observer detection algorithms
- Multiple alternative detection algorithms and performance measures
Cuprins
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.
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.
Notă biografică
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.