Authors:
Editors:
- 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
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Table of contents (13 chapters)
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Front Matter
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Back Matter
About this book
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.
Keywords
- Rouslan Leontievich Stratonovich
- Theory of Random Noise
- Conditional Markov Processes
- adaptive Bayesian inference
- information theory
- statistical thermodynamics
- Value of Information
- quantum information theory
- filtering theory
- non-commutative probability
- Boltzmann distribution
- exponential family distributions
- machine learning
- cognitive modelling
- temperature parameter
- AI algorithms
- data-driven economy
- stochastic processes
- data analysis
- develop stochastic calculus
Reviews
“The book could be useful in advanced graduate courses with students, who are not afraid of integrals and probabilities.” (Jaak Henno, zbMATH 1454.94002, 2021)
Authors, Editors and Affiliations
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Faculty of Science and Technology, Middlesex University, London, UK
Roman V. Belavkin
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Industrial and Systems Engineering, University of Florida, Gainesville, USA
Panos M. Pardalos
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Electrical & Computer Engineering, University of Florida, Gainesville, USA
Jose C. Principe
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(deceased), Moscow, Russia
Ruslan L. Stratonovich
Bibliographic Information
Book Title: Theory of Information and its Value
Authors: Ruslan L. Stratonovich
Editors: Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe
DOI: https://doi.org/10.1007/978-3-030-22833-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-22832-3Published: 15 January 2020
Softcover ISBN: 978-3-030-22835-4Published: 26 August 2021
eBook ISBN: 978-3-030-22833-0Published: 14 January 2020
Edition Number: 1
Number of Pages: XXII, 419
Number of Illustrations: 29 b/w illustrations, 4 illustrations in colour
Topics: Information and Communication, Circuits, Data Structures and Information Theory, Statistical Physics and Dynamical Systems, Quantum Information Technology, Spintronics, Optimization