1. In a neural-network associative memory having means for storing a set of N-tuple neuron-state vectors as terminal attractors, an iterative neural dynamic system for retrieving one of said stored vectors which best matches an input vector x'.sub.i in which the iterative neural dynamics of said system are given by ##EQU40## where T.sub.ij is the ith row and jth column element of a weight matrix, and g(x.sub.i) is a sigmoidal threshold function, where ##EQU41## is a parameter that is the inner product between one of said stored vectors and a vector of a preceding iteration that has a similarity between said one of said stored vectors and said computed vector, .beta..sup.m.sub.i is a constant .beta..sup.m, and g(x.sub.j) is a sigmoidal function of tanh ax.sub.j, where lim.sub.a.fwdarw..infin. g(x.sub.j) is a binary component, and ##EQU42##