Information Theory, Inference and Learning Algorithms (Taschenbuch) von David MacKay   Synopsis: This textbook has two main themes. It offers a comprehensive coverage of Shannon's theory of information as well as the theory of neural networks and probabilistic data modelling. Shannon's source encoding theorem and noisy channel theorem are explained and proved. Accompanying these theoretical results are descriptions of practical data compression systems including the Huffman coding algorithm and the less well known arithmetic coding algorithm. The treatment of neural networks is approached from two perspectives. On the one hand, the information-theoretic capabilities of some neural network algorithms are examined and on the other hand, neural networks are motivated as statistical models. With many examples and exercises this book is ideal for students to use as the text for a course, or as a resource for researchers who need to work with neural networks or state of the art error correcting codes. Rezensionen ansehen...   Angebote zu  Information ,  Theory ,  Inference  ab 1 Euro! Siehe auch folgende Artikel: Pattern Recognition and Machine Learning (Information Science and Statistics) von Christopher M. Bishop An Introduction to Information Theory von John R. Pierce Probability Theory. The Logic of Science: Principles and Elementary Applications Vol 1 von E. T. Jaynes Information Theory von Robert B. Ash Mehr zu  Information Theory,  Modeling & Simulation,  Computers & Internet,  Programming,  Software Home ...,    Angebote ansehen ...,    Begleitseite ... Herausgeber dieser Seite ist DomainLoc.com GmbH - Partner von Amazon.de Copyright © DomainLoc.com GmbH (Impressum)