Neural networks. An introduction.

Müller, Berndt:

ISBN 10: 3540602070 / ISBN 13: 9783540602071

Editore: Berlin, Springer, 1995

Riguardo questo articolo

XV, 329 S. Ex-library with stamp and library-signature. GOOD condition, some traces of use. C-02791 9783540602071 Sprache: Englisch Gewicht in Gramm: 1050.

Codice articolo 2488672

Dati bibliografici

• Titolo: Neural networks. An introduction.
• Editore: Berlin, Springer
• Data di pubblicazione: 1995
• Lingua: Inglese
• ISBN 10: 3540602070
• ISBN 13: 9783540602071
• Rilegatura: Softcover
• Edizione: 2. updated and corr. ed.
• Cataloghi dei venditori:
  • SA MATHEMATIK

Descrizione articolo

Riassunto

Neural Networks presents concepts of neural-network models and techniques of parallel distributed processing in a three-step approach: - A brief overview of the neural structure of the brain and the history of neural-network modeling introduces to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers subjects like statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - The final part discusses nine programs with practical demonstrations of neural-network models. The software and source code in C are on a 3 1/2" MS-DOS diskette can be run with Microsoft, Borland, Turbo-C, or compatible compilers.

Dalla quarta di copertina

Neural Networks The concepts of neural-network models and techniques of parallel distributed processing are comprehensively presented in a three-step approach: - After a brief overview of the neural structure of the brain and the history of neural-network modeling, the reader is introduced to associative memory, preceptrons, feature-sensitive networks, learning strategies, and practical applications. - The second part covers more advanced subjects such as the statistical physics of spin glasses, the mean-field theory of the Hopfield model, and the "space of interactions" approach to the storage capacity of neural networks. - In the self-contained final part, seven programs that provide practical demonstrations of neural-network models and their learning strategies are discussed. The software is included on a 3 1/2-inch MS-DOS diskette. The source code can be modified using Borland's TURBO-C 2.0 compiler, the Microsoft C compiler (5.0), or compatible compilers.