Comparing performance of Hebbian- and delta-trained Hopfield networks

Defines a new performance parameter, ´associativity´, which measures the error-correcting capability of the Hopfield network. Simulations show that the associativity of a delta-trained network is inferior to one trained using the Hebbian rule, and that a novel combination of the two training strategies yields a performance which is superior to either.