Generalized Information Measures and Their Applications
by Inder Jeet Taneja
Publisher: Universidade Federal de Santa Catarina 2001
Contents: Shannon's Entropy; Information and Divergence Measures; Entropy-Type Measures; Generalized Information and Divergence Measures; M-Dimensional Divergence Measures and Their Generalizations; Unified (r,s)-Multivariate Entropies; Noiseless Coding and Generalized Information Measures; Channel Capacity and Source Coding Theorems; Statistical Aspects of Information Measures; Bayesian Probability of Error and Generalized Information Measures; Fuzzy Sets and Information Measures.
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by Alexander Shen - arXiv.org
Algorithmic information theory studies description complexity and randomness. This text covers the basic notions of algorithmic information theory: Kolmogorov complexity, Solomonoff universal a priori probability, effective Hausdorff dimension, etc.
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The aim of this book is to provide an overview of current work addressing topics of research that explore the geometric structures of information and entropy. This survey will motivate readers to explore the emerging domain of Science of Information.
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Processing of information is necessarily a physical process. It is not surprising that physics and the theory of information are inherently connected. Quantum information theory is a research area whose goal is to explore this connection.
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