Dynamics of a Neural Network Composed by two Hopfield Subnetworks Interconnected Unidirectionally

By means of numerical simulations, the dynamical behaviour of a Neural Network composed of two Hopfield Subnetworks interconnected unidirectionally and updated synchronically (at zero temperature T = 0) is studied. These connections are such that each of the N neurons on the first subnet sends information to exclusively one of the N neurons on the second. A set of p patterns, composed by a subpattern for each of the subnets, is stored according to a Hebb-like rule. The recoverability of one particular subpattern by the second subnet is studied as a function of N and the load parameter α = p/N in the case when the first subnetwork has already recovered its corresponding subpattern