General asymmetric neural networks and structure design by genetic algorithms: a learning rule for temporal patterns

A learning algorithm based on genetic algorithms for asymmetric neural networks with an arbitrary structure is presented. It is suited for the learning of temporal patterns and leads to stable neural networks with feedback.<<ETX>>

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