Neural Networks and Simulation Methods
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This work explains network dynamics, learning paradigms, and computational capabilities of feedforward, self-organization, and feedback neural network models-addressing specific problems such as data fusion and data modeling. It goes on to describe a neural network simulation software package - USTCNET and gives some segments of the program.
Table of Contents
General concepts of pattern recognition; feedforward neural networks; feedforward neural networks for functional approximation; applications of feedforward neural networks; fuzzy neural networks; competitive learning and self-organization; adaptive self-organization; associative memory; optimization through neural networks.
". . .very well written and organized. "