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The Resource Theory of Information and its Value, by Ruslan L. Stratonovich ; edited by Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe, (electronic resource)
Theory of Information and its Value, by Ruslan L. Stratonovich ; edited by Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe, (electronic resource)
Resource Information
The item Theory of Information and its Value, by Ruslan L. Stratonovich ; edited by Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Theory of Information and its Value, by Ruslan L. Stratonovich ; edited by Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 Summary
 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 datadriven 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
 Language
 eng
 Edition
 1st ed. 2020.
 Extent
 XXII, 419 p. 33 illus., 4 illus. in color.
 Contents

 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.
 Isbn
 9783030228330
 Label
 Theory of Information and its Value
 Title
 Theory of Information and its Value
 Statement of responsibility
 by Ruslan L. Stratonovich ; edited by Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe
 Subject

 Mathematical optimization
 Optimization
 Quantum Information Technology, Spintronics
 Quantum computers
 Spintronics
 Statistical Physics and Dynamical Systems
 Statistical physics
 Data Structures and Information Theory
 Data structures (Computer science)
 Electronic resources
 Information and Communication, Circuits
 Information theory
 Language
 eng
 Summary
 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 datadriven 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
 http://library.link/vocab/creatorName
 Stratonovich, Ruslan L
 http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
 wtX_b5nF6K8
 http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsedt

 xyMZBy1czMM
 BfBATnCpGv4
 0HgfjdkbdtU
 Image bit depth
 0
 LC call number

 Q350390
 QA10.4
 Literary form
 non fiction
 http://library.link/vocab/relatedWorkOrContributorName

 Belavkin, Roman V.
 Pardalos, Panos M.
 PrÃncipe, J. C.
 http://library.link/vocab/subjectName

 Information theory
 Data structures (Computer science)
 Statistical physics
 Quantum computers
 Spintronics
 Mathematical optimization
 Information and Communication, Circuits
 Data Structures and Information Theory
 Statistical Physics and Dynamical Systems
 Quantum Information Technology, Spintronics
 Optimization
 Label
 Theory of Information and its Value, by Ruslan L. Stratonovich ; edited by Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 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.
 Dimensions
 unknown
 Edition
 1st ed. 2020.
 Extent
 XXII, 419 p. 33 illus., 4 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9783030228330
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other control number
 10.1007/9783030228330
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9783030228330
 Label
 Theory of Information and its Value, by Ruslan L. Stratonovich ; edited by Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 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.
 Dimensions
 unknown
 Edition
 1st ed. 2020.
 Extent
 XXII, 419 p. 33 illus., 4 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9783030228330
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other control number
 10.1007/9783030228330
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9783030228330
Subject
 Mathematical optimization
 Optimization
 Quantum Information Technology, Spintronics
 Quantum computers
 Spintronics
 Statistical Physics and Dynamical Systems
 Statistical physics
 Data Structures and Information Theory
 Data structures (Computer science)
 Electronic resources
 Information and Communication, Circuits
 Information theory
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<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.bu.edu/portal/TheoryofInformationanditsValuebyRuslanL./aULUqj0VYE/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.bu.edu/portal/TheoryofInformationanditsValuebyRuslanL./aULUqj0VYE/">Theory of Information and its Value, by Ruslan L. Stratonovich ; edited by Roman V. Belavkin, Panos M. Pardalos, Jose C. Principe, (electronic resource)</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.bu.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.bu.edu/">Boston University Libraries</a></span></span></span></span></div>