
Mathematics of Information and Coding
American Mathematical Society (Publisher)
Published in January 2002
Book
Hardback
296 pages
978-0-8218-0534-3 (ISBN)
Description
This book is intended to provide engineering and/or statistics students, communications engineers, and mathematicians with the firm theoretic basis of source coding (or data compression) in information theory. Although information theory consists of two main areas, source coding and channel coding, the authors choose here to focus only on source coding. The reason is that, in a sense, it is more basic than channel coding, and also because of recent achievements in source coding and compression. An important feature of the book is that whenever possible, the author describes universal coding methods, i.e., the methods that can be used without prior knowledge of the statistical properties of the data. The authors approach the subject of source coding from the very basics to the top frontiers in an intuitively transparent, but mathematically sound manner. The book serves as a theoretical reference for communication professionals and statisticians specializing in information theory.
It will also serve as an excellent introductory text for advanced-level and graduate students taking elementary or advanced courses in telecommunications, electrical engineering, statistics, mathematics, and computer science.
It will also serve as an excellent introductory text for advanced-level and graduate students taking elementary or advanced courses in telecommunications, electrical engineering, statistics, mathematics, and computer science.
More details
Series
Language
English
Place of publication
Providence
United States
Target group
College/higher education
Professional and scholarly
Illustrations
bibliography, index
Dimensions
Height: 254 mm
Width: 190 mm
Weight
740 gr
ISBN-13
978-0-8218-0534-3 (9780821805343)
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Schweitzer Classification
Persons
Content
What is information theory?; Basics of information theory; Source and coding; Arithmetic code; Universal coding of integers; Universal coding of texts; Universal coding of compound sources; Data analysis and MDL principle; Bibliography; Index