Logic and Information
by Keith Devlin
Publisher: ESSLLI 2001
An introductory, comparative account of three mathematical approaches to information: the classical quantitative theory of Claude Shannon, developed in the 1940s and 50s, a quantitative-based, qualitative theory developed by Fred Dretske in the 1970s, and a qualitative theory introduced by Jon Barwise and John Perry in the early 1980s and pursued by Barwise, Israel, Devlin, Seligman and others in the 1990s.
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by Felix Effenberger - arXiv
This chapter is supposed to give a short introduction to the fundamentals of information theory, especially suited for people having a less firm background in mathematics and probability theory. The focus will be on neuroscientific topics.
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 Robert H. Schumann - arXiv
A short review of ideas in quantum information theory. Quantum mechanics is presented together with some useful tools for quantum mechanics of open systems. The treatment is pedagogical and suitable for beginning graduates in the field.
by Neri Merhav - arXiv
Lecture notes for a graduate course focusing on the relations between Information Theory and Statistical Physics. The course is aimed at EE graduate students in the area of Communications and Information Theory, or graduate students in Physics.