Neural Networks: A Comprehensive Foundation: United States Edition
Language: English
Published by Pearson Education, 1998
- Hardcover
- Used
Seller: Optimon Books, Gravesend, Kent, United KingdomOptimon Books
AbeBooks seller since December 22, 2022
Condition: Used - Very good
£ 41.99
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Add to basketItem description from seller
For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Thoroughly revised.
Seller Inventory # 453986
- Title
- Neural Networks: A Comprehensive Foundation: United States Edition
- Author
- Simon S. Haykin
- Publisher
- Pearson Education
- Publication year
- 1998
- Condition
- Very Good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0132733501
- ISBN 13
- 9780132733502
For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science.
Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Thoroughly revised.
"Synopsis" may belong to another edition of this title.
From the Back Cover
Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Thoroughly revised.
NEW TO THIS EDITION- NEW―New chapters now cover such areas as:
- Support vector machines.
- Reinforcement learning/neurodynamic programming.
- Dynamically driven recurrent networks.
- NEW-End―of-chapter problems revised, improved and expanded in number.
- Extensive, state-of-the-art coverage exposes the reader to the many facets of neural networks and helps them appreciate the technology's capabilities and potential applications.
- Detailed analysis of back-propagation learning and multi-layer perceptrons.
- Explores the intricacies of the learning process―an essential component for understanding neural networks.
- Considers recurrent networks, such as Hopfield networks, Boltzmann machines, and meanfield theory machines, as well as modular networks, temporal processing, and neurodynamics.
- Integrates computer experiments throughout, giving the opportunity to see how neural networks are designed and perform in practice.
- Reinforces key concepts with chapter objectives, problems, worked examples, a bibliography, photographs, illustrations, and a thorough glossary.
- Includes a detailed and extensive bibliography for easy reference.
- Computer-oriented experiments distributed throughout the book
- Uses Matlab SE version 5.
"About the title" may belong to another edition of this title.
Optimon Books
Gravesend, Kent, United Kingdom
AbeBooks seller since December 22, 2022
Shipping rates from United Kingdom to U.S.A.
| Item | 14 to 45 business days | 5 to 10 business days |
|---|---|---|
| First item | £ 18.00 | £ 40.00 |
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