Comparing performance of Hebbian and delta-trained Hopfield networks

We define 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 uiing the Hebbian rule, and that a novel combination of the two training strategies yields a performance which is superior to either