Açıklama
Book Jacket:
> This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks.
Publisher Description:
> This textbook offers comprehensive coverage of Shannon's theory of information as well as the theory of neural networks and probabilistic data modelling. It includes explanations of Shannon's important source encoding theorem and noisy channel theorem as well as descriptions of practical data compression systems. Many examples and exercises make the book ideal for students to use as a class textbook, or as a resource for researchers who need to work with neural networks or state-of-the-art error-correcting codes.
Baskılar ve ISBN
- 2004
- University of Cambridge ESOL Examinations · İngilizce · 640 sayfa
ISBN 9780521644440 - 2003
- CAMBRIDGE UNIV PRESS · Root · 628 sayfa
ISBN 0521642981 - 2003
- Cambridge University Press · İngilizce · 640 sayfa
ISBN 9780521642989
Künye
- Yazar
- David J.C. MacKay
- İlk yayın
- 2003
- Yayınevleri
- TBS, University of Cambridge ESOL Examinations, CAMBRIDGE UNIV PRESS, Cambridge University Press
- Sayfa (ortalama)
- 640
- Baskı sayısı
- 3
- Kaynak
- Open Library