| 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. |
Readership: Graduate students and research mathematicians interested in information theory.
| Contents |
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
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| Authors, editors,
and contributors | Te Sun Han, The University of Electro-Communications, Tokyo and Kingo Kobayashi, The University of Electro-Communications Toyko
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