On the storage of correlated patterns in Hopfield's model

Abstract

The effects of storing p statistically independent but effectively correlated patterns in the Hopfield model of associative memory are studied. This leads us to propose a local learning rule which by enhancing the differences among the patterns allows the network to store them with an efficiency comparable to nonlocal learning rules.

Additional details