Principles Of Artificial Neural Networks (2nd Edition)
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A01=Daniel Graupe
Author_Daniel Graupe
Backpropagation
Case Studies
Category=UYQN
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Hopfield Network
LAMSTAR
Neural Networks
Product details
- ISBN 9789812706249
- Publication Date: 10 Apr 2007
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
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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 the 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.
