ISBN10: 0486604349, ISBN13: 9780486604343, [publisher: Dover Publications, Incorporated] Softcover Used book that is in excellent condition. May show signs of wear or have minor defects.
[Reno, NV, U.S.A.] [Publication Year: 2003]

Dover Publications, Date: 1957. Paperback. Good. Missing dust jacket; Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.Dust jacket quality is not guaranteed. Dover Publications ISBN 0486604349 9780486604343 [US]

Dover Publications, Incorporated, Date: 1957. Paperback. Acceptable. Disclaimer:A readable copy. All pages are intact, and the cover is intact. Pages can include considerable notes-in pen or highlighter-but the notes cannot obscure the text. At ThriftBooks, our motto is: Read More, Spend Less.Dust jacket quality is not guaranteed. Dover Publications, Incorporated ISBN 0486604349 9780486604343 [US]

Dover Publications, Incorporated. Used - Good. Used book that is in clean, average condition without any missing pages. Dover Publications, Incorporated ISBN 0486604349 9780486604343 [US]

Dover Publications, Incorporated. Used - Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects. Dover Publications, Incorporated ISBN 0486604349 9780486604343 [US]

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[Grandview Heights, OH, U.S.A.] [Publication Year: 1957]

Paperback / softback. New. ISBN 0486604349 9780486604343 [GB]

ISBN10: 0486604349, ISBN13: 9780486604343, [publisher: Dover Publications] Softcover New. In shrink wrap. Looks like an interesting title! 0.3
[North Las Vegas, NV, U.S.A.] [Publication Year: 1957]

ISBN10: 0486604349, ISBN13: 9780486604343, [publisher: Dover Publications Inc., New York] Softcover Paperback. The first comprehensive introduction to information theory, this book places the work begun by Shannon and continued by McMillan, Feinstein, and Khinchin on a rigorous mathematical basis. For the first time, mathematicians, statisticians, physicists, cyberneticists, and communications engineers are offered a lucid, comprehensive introduction to this rapidly growing field.In his first paper, Dr. Khinchin develops the concept of entropy in probability theory as a measure of uncertainty of a finite ""scheme,"" and discusses a simple application to coding theory. The second paper investigates the restrictions previously placed on the study of sources, channels, and codes and attempts ""to give a complete, detailed proof of both . Shannon theorems, assuming any ergodic source and any stationary channel with a finite memory.""Partial Contents: I. The Entropy Concept in Probability Theory - Entropy of Finite Schemes. The Uniqueness Theorem. Entropy of Markov chains. Application to Coding Theory. II. On the Fundamental Theorems of Information Theory - Two generalizations of Shannon's inequality. Three inequalities of Feinstein. Concept of a source. Stationarity. Entropy. Ergodic sources. The E property. The martingale concept. Noise. Anticipation and memory. Connection of the channel to the source. Feinstein's ...

ISBN10: 0486604349, ISBN13: 9780486604343, [publisher: Dover Publications Inc., New York] Softcover Paperback. The first comprehensive introduction to information theory, this book places the work begun by Shannon and continued by McMillan, Feinstein, and Khinchin on a rigorous mathematical basis. For the first time, mathematicians, statisticians, physicists, cyberneticists, and communications engineers are offered a lucid, comprehensive introduction to this rapidly growing field.In his first paper, Dr. Khinchin develops the concept of entropy in probability theory as a measure of uncertainty of a finite ""scheme,"" and discusses a simple application to coding theory. The second paper investigates the restrictions previously placed on the study of sources, channels, and codes and attempts ""to give a complete, detailed proof of both . Shannon theorems, assuming any ergodic source and any stationary channel with a finite memory.""Partial Contents: I. The Entropy Concept in Probability Theory - Entropy of Finite Schemes. The Uniqueness Theorem. Entropy of Markov chains. Application to Coding Theory. II. On the Fundamental Theorems of Information Theory - Two generalizations of Shannon's inequality. Three inequalities of Feinstein. Concept of a source. Stationarity. Entropy. Ergodic sources. The E property. The martingale concept. Noise. Anticipation and memory. Connection of the channel to the source. Feinstein's ...