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Theory of Information and its Value

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Cover of 'Theory of Information and its Value'

Table of Contents

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    Book Overview
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    Chapter 1 Definition of information and entropy in the absence of noise
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    Chapter 2 Encoding of discrete information in the absence of noise and penalties
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    Chapter 3 Encoding in the presence of penalties. First variational problem
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    Chapter 4 First asymptotic theorem and related results
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    Chapter 5 Computation of entropy for special cases. Entropy of stochastic processes
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    Chapter 6 Information in the presence of noise. Shannon’s amount of information
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    Chapter 7 Message transmission in the presence of noise. Second asymptotic theorem and its various formulations
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    Chapter 8 Channel capacity. Important particular cases of channels
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    Chapter 9 Definition of the value of information
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    Chapter 10 Value of Shannon’s information for the most important Bayesian systems
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    Chapter 11 Asymptotic results about the value of information. Third asymptotic theorem
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    Chapter 12 Information theory and the second law of thermodynamics
Attention for Chapter 10: Value of Shannon’s information for the most important Bayesian systems
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Chapter title
Value of Shannon’s information for the most important Bayesian systems
Chapter number 10
Book title
Theory of Information and its Value
Published by
Springer, Cham, January 2020
DOI 10.1007/978-3-030-22833-0_10
Book ISBNs
978-3-03-022832-3, 978-3-03-022833-0
Authors

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

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