Information Theory, Inference and Learning Algorithms\n\nFun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.\n\nDavid J. C. MacKay (Author)\n\n9780521642989, Cambridge University Press\n\nHardback, published 25 September 2003\n\n640 pages\n25.4 x 19.5 x 3.4 cm, 1.525 kg\n\n'With its breadth, accessibility and handsome design, this book should prove to be quite popular. Highly recommended as a primer for students with no background in coding theory, the set of chapters on error correcting codes are an excellent brief introduction to the elements of modern sparse graph codes: LDPC, turbo, repeat-accumulate and fountain codes are described clearly and succinctly.' IEEE Transactions on Information Theory\n\nInformation theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recogni]