Retrieval properties of a neural network with an asymmetric learning rule
E. Gardner, Stephan Mertens, Alfred Zippelius · Journal of Physics A Mathematical and General · 1989
The author considers a Hebbian learning mechanism, which gives rise to a change in synaptic efficacies only if the postsynaptic neuron is active. The model is solved analytically in the limit of strong dilution. The network is shown to classify initial configurations according to their mean activity and their overlap with one of the learnt patterns. The capacity of the network is calculated as a function of threshold.