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 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 John Watrous - University of Calgary
The focus is on the mathematical theory of quantum information. We will begin with basic principles and methods for reasoning about quantum information, and then move on to a discussion of various results concerning quantum information.
by David J. C. MacKay - University of Cambridge
This text discusses the theorems of Claude Shannon, starting from the source coding theorem, and culminating in the noisy channel coding theorem. Along the way we will study simple examples of codes for data compression and error correction.
by Peter D. Gruenwald, Paul M.B. Vitanyi - CWI
We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain this quantitative approach to defining information and discuss the extent to which Kolmogorov's and Shannon's theory have a common purpose.