The back-propagation training technique for feed-forward neural networks is extended to networks with delay elements in the connections. Such an extension has previously been described for discrete-time presentation of training patterns and weight updates [1]. Here we present a continuous-time generalization of these results. Such networks can be used for temporal and spatio-temporal pattern recognition.
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