Compensation of edge effect in neuron-like layer nets with local feedbacks

Abstract

One or two-dimensional layer nets with local feedback between neuron-like elements were investigated. The mutual influence between elements of the net is based on the principle of lateral inhibition. A properly adapted and modified Z-transform method applied to a difference equation describing the function of the net allowed us to characterize the properties and dynamics of the net and to define its stability region. Finite dimensions of the net cause "reflections" of signals from the edges of the structure. This makes the detection of pattern difficult or even impossible and therefore the problem of compensation of the edge-effects appears. Several methods of compensation, involving discrete or continuous change of coupling weights, are described. A comparison of the behavior of a compensated and uncompensated net, as modelled on a digital computer, shows the advantages of the compensation.