Back Propagation Learning Using a Super Stable Motion

Abstract

The ability of back propagation learning in a neural network, whose neuron is governed by coupled logistic maps, is investigated. High speed learning is obtained with the use of the super stable point a = 2 of the logistic map f = ax(1 - x), which is faster than a conventional neural network.