Information theory & 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 recognition computational neuroscience bioinformatics & cryptography The book introduces theory in tandem with applications Information theory is taught alongside practical communication systems such as arithmetic coding for data compression & sparse-graph codes for error-correction Inference techniques including message-passing algorithms Monte Carlo methods & variational approximations are developed alongside applications to clustering convolutional codes independent component analysis & neural networks Uniquely the book covers state-of-the-art error-correcting codes including low-density-parity-check codes turbo codes & digital fountain codes
- the twenty-first-century standards for satellite communications disk drives & data broadcast Richly illustrated filled with worked examples & over 400 exercises some with detailed solutions the book is ideal for self-learning & for undergraduate or graduate courses It also provides an unparalleled entry point for professionals in areas as diverse as computational biology financial engineering & machine learning