Publisher: Wikibooks 2011
Data compression is useful in some situations because 'compressed data' will save time (in reading and on transmission) and space if compared to the unencoded information it represent. In this book, we describe the decompressor first, for several reasons...
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by Gregory J. Chaitin - Springer
The final version of a course on algorithmic information theory and the epistemology of mathematics. The book discusses the nature of mathematics in the light of information theory, and sustains the thesis that mathematics is quasi-empirical.
by Inder Jeet Taneja - Universidade Federal de Santa Catarina
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; etc.
by Keith Devlin - ESSLLI
An introductory, comparative account of three mathematical approaches to information: the classical quantitative theory of Claude Shannon, a qualitative theory developed by Fred Dretske, and a qualitative theory introduced by Barwise and Perry.
by Venkatesan Guruswami, Atri Rudra, Madhu Sudan - University at Buffalo
Error-correcting codes are clever ways of representing data so that one can recover the original information even if parts of it are corrupted. The basic idea is to introduce redundancy so that the original information can be recovered ...