Neural networks an introduction B. Müller ; J. Reinhardt / Physics of neural networks

Müller, Berndt (Verfasser) and Joachim (Verfasser) Reinhardt:

ISBN 10: 3540523804 / ISBN 13: 9783540523802

Published by Berlin ; Heidelberg : Springer, 1990

About this Item

XIII, 266 S. : 83 graph. Darst. ; 25 cm , 711g LEIDER OHNE FLOPPY-DISK, sonst sehr gut --- Flopyy disk is missing unfortunately, but the book is in very good condition Sprache: Englisch Gewicht in Gramm: 711.

Seller Inventory # 49478

Bibliographic Details

• Title: Neural networks an introduction B. Müller ; J. Reinhardt / Physics of neural networks
• Publisher: Berlin ; Heidelberg : Springer
• Publication Date: 1990
• Language: English
• ISBN 10: 3540523804
• ISBN 13: 9783540523802
• Binding: *geb.
• Condition: Sehr gut
• Weight: 711 grams
• Seller catalogs:
  • Physik

About this title

Synopsis

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 "neural" information processing, i.e. associative memory, perceptrons, feature-sensitive networks, learning strategies, and practical applications. - Part 2 covers more advanced subjects such as spin glasses, the mean-field theory of the Hopfield model, and the space of interactions in neural networks. - The self-contained final part discusses seven programs that provide practical demonstrations of neural-network models and their learning strategies. Ample opportunity is given to improve and modify the source codes. The software is included on a 5 1/4 inch MS DOS diskette and can be run using Borland's TURBO C 2.0 compiler, the Microsoft C compiler (5.0), or compatible compilers.

From the Back Cover

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.