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Information Theory(1965)
ÁöÀºÀÌ
:
Robert B. Ash
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Dover
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first editon
ÆäÀÌÁö¼ö
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352
ISBN
:
0486665216
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Excellent introduction treats three major areas: analysis of channel models and proof of coding theorems; study of specific coding systems; and study of statistical properties of information sources. Appendix summarizes Hilbert space background and results from the theory of stochastic processes. Advanced undergraduate to graduate level. Bibliography.
"This is the best book for self-study of information theory which I have found, and I looked hard because I needed to learn the basics of information theory in grad school. As far as content, Ash covers all the major topics in information theory, from definitions of basic quantities like mutual information to the mathematical representation of continuous communication channels. One of the best aspects of the book is a set of problem sets at the end of each chapter, each with detailed solutions at the end of the book. They serve as very useful checks on one's understanding. As for structure, Ash manages to cover these topics in a way that is concise and illuminating yet without sacrificing mathematical rigour (note that the book assumes you know basic probability theory and calculus). If anyone wants to learn the mathematical theory of communication, I highly recommend using this book as your guide."
"This 1990 Dover publication of the original 1965 edition serves as a great introduction to "the statistical communication theory", otherwise known as Information Theory, a subject which concerns the theoretical underpinnings of a broad class of communication devices. The exposition here is based on the Shannon's (not Wiener's) formulation or model of the theory, having been initiated in his breakthrough 1948 paper. I purchased this book more than a couple of years ago as a beginning math grad student mainly interested to (quickly and affordably) learn some basics about the subject, without necessarily intending to specialize in it. The text in my opinion should also be accessible to any engineering student with a one or two semester background in real analysis, and a working knowledge of the theory of probability (also summarized at the beginning of the book). Topics discussed include: noiseless coding, discrete memoryless channels, error correcting codes, information sources, channels with memory, and continuous channels. There are some very illuminating historical notes + remarks, and also problem sets at the end of each chapter, with solutions included at the back of the book, making an ideal setting for self-study. Aside from being a great resource for learning the basics however, one sole setback of the book is that all the results and theorems presented therein date from the 50's and early 60's, so one will have to look elsewhere to find out about some of the more recent developments in the field."
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