Offers the most complete, up-to-date coverage available on the principles of digital communications. Focuses on basic issues, relating theory to practice wherever possible. Numerous examples, worked out in detail, have been included to help the reader develop an intuitive grasp of the theory. Topics covered include the sampling process, digital modulation techniques, error-control coding, robust quantization for pulse-code modulation, coding speech at low bit radio, information theoretic concepts, coding and computer communication. Because the book covers a broad range of topics in digital communications, it should satisfy a variety of backgrounds and interests.

Simon Haykin is a University Professor at McMaster University, Hamilton, Ontario, Canada. His research interests include nonlinear dynamics, neural networks and adaptive filters and their applications in radar and communications systems. Dr. Haykin is the editor for a series of books on "Adaptive and Learning Systems for Signal Processing, Communications and Control" published by John Wiley & Sons, Inc. He is both an IEEE Fellow and Fellow of the Royal Society of Canada.

Chapters
* Introduction
* Fourier Analysis of Signals and Systems
* Probability Theory and Bayesian Inference
* Stochastic Processes
* Information Theory
* Conversion of Analog Waveforms into Coded Pulses
* Signaling over AWGN Channels
* Signaling over Band-Limited Channels
* Signaling over Fading Channels
* Error-control Coding
Appendices
* Advanced Probabilistic Models
* Bounds on the Q-Function
* Bessel Functions
* Method of Lagrange Multipliers
* Information Capacity of MIMO Channels
* Interleaving
* The Peak-Power Reduction Problem in OFDM
* Nonlinear Solid-State Power Amplifiers
* Monte Carlo Integration
* Maximal-Length Sequences
Mathematical Tables
Glossary
Bibliography
Index