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Introduction to Coding and Information Theory / Edition 1
     

Introduction to Coding and Information Theory / Edition 1

by Steven Roman
 

ISBN-10: 0387947043

ISBN-13: 9780387947044

Pub. Date: 11/26/1996

Publisher: Springer New York

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

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.

Product Details

ISBN-13:
9780387947044
Publisher:
Springer New York
Publication date:
11/26/1996
Series:
Undergraduate Texts in Mathematics Series
Edition description:
1997
Pages:
326
Sales rank:
829,180
Product dimensions:
10.00(w) x 7.00(h) x 0.88(d)

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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