MIXTURE STATES AND STORAGE WITH CORRELATED PATTERNS IN HOPFIELD'S MODEL

The Hopfield model of associative memory with the Hebb learning rule is studied for a finite number p of correlated patterns. The storage capacity α = P/N is considered in a network with further P − p embedded uncorrelated patterns, and the corresponding phase diagrams are exhibited. Numerical simulations are carried out to discuss the retrieval quality and the basins of attraction of the network.