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Artificial Neural Networks
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| Format: | Printed Book |
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Tata McGraw-Hill
1997
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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.