Research Catalog

Title

Principles of artificial neural networks / Daniel Graupe.

Author

Graupe, Daniel.

Publication

Hackensack, N.J. : World Scientific, 2007.

Items in the Library & Off-site

Holdings

Details

Description

xv, 303 pages : illustrations; 25 cm.

Summary

"The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and computer scientists in the industry. Covering major neural network approaches and architectures with theories, this text presents detailed case studies for each of the approaches, accompanied with complete computer codes and the corresponding computed results. The case studies are designed to allow easy comparison of network performance to illustrate strengths and weaknesses of the different networks."--BOOK JACKET.

Series Statement

Advanced series on circuits and systems ; vol. 6

Uniform Title

Advanced series on circuits and systems ; v. 6.

Subject

• Neural networks (Computer science)

Bibliography (note)

• Includes bibliographical references (p.291-297) and indexes.

Contents

Ch. 1. Introduction and role of artificial neural networks -- Ch. 2. Fundamentals of biological neural networks -- Ch. 3. Basic principles of ANNs and their early structures -- Ch. 4. The perceptron -- Ch. 5. The madaline -- Ch. 6. Back propagation -- Ch. 7. Hopfield networks -- Ch. 8. Counter propagation -- Ch. 9. Adaptive resonance theory -- Ch. 10. The cognitron and the neocognitron -- Ch. 11. Statistical training -- Ch. 12. Recurrent (time cycling) back propagation networks -- Ch. 13. Large scale memory storage and retrieval (LAMSTAR) network.

ISBN

• 9812706240
• 9789812706249

OCLC

• ocn141384911
• 141384911
• SCSB-5362514

Owning Institutions

Columbia University Libraries