Information theory and inference, often taught separately, are hereunited in one entertaining textbook. These topics lie at the heart ofmany exciting areas of contemporary science and engineering communication, signal processing, data mining, machine learning,pattern recognition, computational neuroscience, bioinformatics, andcryptography. This textbook introduces theory in tandem withapplications. Information theory is taught alongside practicalcommunication systems, such as arithmetic coding for data compressionand sparsegraph codes for errorcorrection. A toolbox of inferencetechniques, including messagepassing algorithms, Monte Carlomethods, and variational approximations, are developed alongsideapplications of these tools to clustering, convolutional codes,independent component analysis, and neural networks. The final partof the book describes the state of the art in errorcorrecting codes,including lowdensity paritycheck codes, turbo codes, and digitalfountain codes — the twentyfirst century standards for satellitecommunications, disk drives, and data broadcast. Richly illustrated,filled with worked examples and over 400 exercises, some withdetailed solutions, David MacKay's groundbreaking book is ideal forselflearning and for undergraduate or graduate courses. Interludeson crosswords, evolution, and sex provide entertainment along theway. In sum, this is a textbook on information, communication, andcoding for a new generation of students, and an unparalleled entrypoint into these subjects for professionals in areas as diverse ascomputational biology, financial engineering, and machine learning.

Authors: MacKay D.J.C.  Pages: 640 Year: 2003 
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