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Theory of Information and its Value (Hardcover, 1st ed. 2020) Loot Price: R3,486
Discovery Miles 34 860
Theory of Information and its Value (Hardcover, 1st ed. 2020): Roman V. Belavkin

Theory of Information and its Value (Hardcover, 1st ed. 2020)

Roman V. Belavkin; Ruslan L. Stratonovich; Edited by Panos M. Pardalos, Jose C. Principe

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Loot Price R3,486 Discovery Miles 34 860 | Repayment Terms: R327 pm x 12*

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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.

General

Imprint: Springer Nature Switzerland AG
Country of origin: Switzerland
Release date: 2020
First published: 2020
Editors: Roman V. Belavkin
Authors: Ruslan L. Stratonovich
Editors: Panos M. Pardalos • Jose C. Principe
Dimensions: 235 x 155mm (L x W)
Format: Hardcover
Pages: 419
Edition: 1st ed. 2020
ISBN-13: 978-3-03-022832-3
Categories: Books > Computing & IT > General theory of computing > Data structures
Books > Computing & IT > Computer programming > Algorithms & procedures
Books > Science & Mathematics > Mathematics > Optimization > General
Books > Science & Mathematics > Mathematics > Applied mathematics > General
Books > Science & Mathematics > Physics > Thermodynamics & statistical physics > Statistical physics
Books > Science & Mathematics > Physics > Quantum physics (quantum mechanics) > General
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LSN: 3-03-022832-0
Barcode: 9783030228323

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