Information Theory and Coding
by John Daugman
Publisher: University of Cambridge 2009
Number of pages: 75
Description:
The aims of this course are to introduce the principles and applications of information theory. The course will study how information is measured in terms of probability and entropy, and the relationships among conditional and joint entropies; how these are used to calculate the capacity of a communication channel, with and without noise; coding schemes, including error correcting codes; how discrete channels and measures of information generalize to their continuous forms; etc.
Download or read it online for free here:
Download link
(1.4MB, PDF)
Similar books
Information, Entropy and Their Geometric Structuresby Frederic Barbaresco, Ali Mohammad-Djafari - MDPI AG
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.
(9937 views)
Around Kolmogorov Complexity: Basic Notions and Resultsby 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.
(8693 views)
Generalized Information Measures and Their Applicationsby 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.
(13193 views)
The Limits of Mathematicsby 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.
(14970 views)