Neural Networks : An Introduction

Berndt Müller

ISBN 10: 3540602070 / ISBN 13: 9783540602071

Verlag: Springer Berlin Heidelberg, 1995

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - 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.

Bestandsnummer des Verkäufers 9783540602071

Bibliografische Details

• Titel: Neural Networks : An Introduction
• Verlag: Springer Berlin Heidelberg
• Erscheinungsjahr: 1995
• Sprache: Englisch
• ISBN-10: 3540602070
• ISBN-13: 9783540602071
• Einband: Taschenbuch
• Auflage: 2. Auflage
• Zustand: Neu
• Abmessungen: 235B x 155 H x 19 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 19 mm
• Gewicht: 528 Gramm

Über diesen Titel

Inhaltsangabe

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.

Von der hinteren Coverseite

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.