Neural Networks: An Introduction. Physics of Neural Networks

Müller, B. and J. Reinhardt:

ISBN 10: 3540523804 / ISBN 13: 9783540523802

Verlag: Spinger Verlag;, 1990

Beschreibung

266 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten wissenschaftlichen Bibliothek und trägt die entsprechenden Kennzeichnungen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. Leichte altersbedingte Anbräunung des Papiers. Das Buch ist in eine Plastikfolie eingeklebt. Der Bucheinband ist verschmutzt. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 580.

Bestandsnummer des Verkäufers 2092573

Bibliografische Details

• Titel: Neural Networks: An Introduction. Physics of Neural Networks
• Verlag: Spinger Verlag
• Erscheinungsjahr: 1990
• Sprache: Englisch
• ISBN-10: 3540523804
• ISBN-13: 9783540523802
• Einband: gebundene Ausgabe
• Zustand: Gut
• Gewicht: 580 Gramm
• Verkäuferkataloge:
  • 2033 Anthropologie

Über diesen Titel

Inhaltsangabe

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 modelling, the reader is introduced to "neural" information processing, such as 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 programmes that provide practical demonstrations of neural-network models and their learning strategies. Software is included with the text 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.

Reseña del editor

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.