Introduction to Coding and Information Theory
Author:   Steven Roman
Publisher:   Springer-Verlag New York Inc.
Edition:   1997 ed.
ISBN:  

9780387947044


Pages:   326
Publication Date:   26 November 1996
Format:   Hardback
Availability:   Out of print, replaced by POD   Availability explained
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Introduction to Coding and Information Theory


Overview

This book is intended to introduce coding theory and information theory to undergraduate students of mathematics and computer science. It begins with a review of probablity theory as applied to finite sample spaces and a general introduction to the nature and types of codes. The two subsequent chapters discuss information theory: efficiency of codes, the entropy of information sources, and Shannon's Noiseless Coding Theorem. The remaining three chapters deal with coding theory: communication channels, decoding in the presence of errors, the general theory of linear codes, and such specific codes as Hamming codes, the simplex codes, and many others.

Full Product Details

Author:   Steven Roman
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   1997 ed.
Dimensions:   Width: 17.80cm , Height: 2.00cm , Length: 25.40cm
Weight:   1.920kg
ISBN:  

9780387947044


ISBN 10:   0387947043
Pages:   326
Publication Date:   26 November 1996
Audience:   College/higher education ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

Table of Contents

Introduction: Preliminaries; Miscellany; Some Probability; Matrices 1. An Introduction to Codes Strings and Things; What are codes? Uniquely Decipherable Codes; Instantaneous Codes and Kraft's Theorem 2. Efficient Encoding Information Sources; Average Codeword Length; Huffman Encoding; The Proof that Huffman Encoding is the Most Efficient 3. Noiseless Coding Entropy; Properties of Entropy; Extensions of an Information 1= Source; The Noiseless Coding Theorem II Coding Theory 4. The Main Coding Theory Problem Communications Channels; Decision Rules; Nearest Neighbor Decoding;

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