Theory of Information and its Value | Buch

Cover: 9783030228323 | Theory of Information and its Value | Ruslan L. Stratonovich | Buch

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Sprache: Englisch

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Beschreibung

This English version of Ruslan L. Stratonovich¿s Theory of Information (1975) builds on theory and provides methods, techniques, and concepts toward utilizing critical applications. Unifying theories of information, optimization, and statistical physics, the value of information theory has gained recognition in data science, machine learning, and artificial intelligence. With the emergence of a data-driven economy, progress in machine learning, artificial intelligence algorithms, and increased computational resources, the need for comprehending information is essential. This book is even more relevant today than when it was first published in 1975. It extends the classic work of R.L. Stratonovich, one of the original developers of the symmetrized version of stochastic calculus and filtering theory, to name just two topics.
Each chapter begins with basic, fundamental ideas, supported by clear examples; the material then advances to great detail and depth. The reader is not required to be familiar with the more difficult and specific material. Rather, the treasure trove of examples of stochastic processes and problems makes this book accessible to a wide readership of researchers, postgraduates, and undergraduate students in mathematics, engineering, physics and computer science who are specializing in information theory, data analysis, or machine learning.

Zusammenfassung

Broadens understanding of information theory and the value of information

English translation of Rouslan L. Stratonovich's original "Theory of Information"

Unifies theories of information, optimization, and statistical physics

Supplies opportunities to practice techniques through unique examples

Inhaltsverzeichnis

Foreword.- Preface.- 1 Definition of information and entropy in the absence of noise- 2 Encoding of discrete information in the absence of noise and penalties.- 3 Encoding in the presence of penalties. The first variational problem- 4 The first asymptotic theorem and relative results.- 5 Computation of entropy for special cases. Entropy of stochastic processes.- 6 Information in the presence of noise. The Shannon's amount of information.- 7 Message transmission in the presence of noise. The second asymptotic theorem and its various formulations.- 8 Channel capacity. Important particular cases of channels.- 9 Definition of the value of information.- 10 The value of Shannon information for the most important Bayesian systems.- 11 Asymptotical results related to the value of information. The Third asymptotic theorem.- 12 Information theory and the second law of thermodynamics.- Appendix Some matrix (operator) identities.- Index.

Details

Erscheinungsjahr:	2020
Fachbereich:	Allgemeines
Genre:	Mathematik
Rubrik:	Naturwissenschaften & Technik
Medium:	Buch
Inhalt:	xxii 419 S. 29 s/w Illustr. 4 farbige Illustr. 419 p. 33 illus. 4 illus. in color.
ISBN-13:	9783030228323
ISBN-10:	3030228320
Sprache:	Englisch
Ausstattung / Beilage:	HC runder Rücken kaschiert
Einband:	Gebunden
Autor:	Stratonovich, Ruslan L.
Redaktion:	Pardalos, Panos M. Principe, Jose C. Belavkin, Roman V.
Herausgeber:	Roman V Belavkin/Panos M Pardalos/Jose C Principe
Auflage:	1st ed. 2020
Hersteller:	Springer International Publishing Springer International Publishing AG
Maße:	241 x 160 x 30 mm
Von/Mit:	Ruslan L. Stratonovich
Erscheinungsdatum:	15.01.2020
Gewicht:	0,828 kg

Artikel-ID: 116558091