Theory of Information and its Value - Softcover

Stratonovich, Ruslan L.

Softcover

ISBN 10: 3030228355 ISBN 13: 9783030228354

Verlag: Springer, 2021

Inhaltsangabe

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.

Über diesen Titel

Über die Autorin bzw. den Autor

 

Von der hinteren Coverseite

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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2021
• Sprache: Englisch
• ISBN 10: 3030228355
• ISBN 13: 9783030228354
• Einband: Tapa blanda
• Auflage: 1
• Anzahl der Seiten: 444
• Herausgeber: Belavkin Roman V., Pardalos Panos M., Principe Jose C.
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Deutschland