Artificial neural networks
Artificial Neural Networks brings together an identifiable core of ideas, techniques, and applications that characterize this emerging field. The text is intended for beginning graduate / advanced undergraduate students as well as practicing engineers and scientists.
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| Format: | Book |
| Language: | English |
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New York, NY
McGraw-Hill
1997
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| Series: | McGraw-Hill series in computer science. / Artificial intelligence
McGraw-Hill series in electrical and computer engineering |
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Table of Contents:
- Overview: artificial neural networks and neural computing
- Mathematical fundamentals for ANN study
- Elementary ANN building blocks
- Single-unit mappings and the perceptron
- Introduction to neural mappings and pattern associator applications
- Feedforward networks and training: part 1
- Feedforward networks, part 2: extensions and advanced topics
- Recurrent networks
- Competitive and self-organizing networks
- Radial Basis Function (RBF) networks and Time Delay Neural Networks (TDNNs)
- Fuzzy neural networks including fuzzy sets and logic and ANN implementations
- ANN hardware and implementation concerns