Chaotic recurrent neural net and learning procedure

摘要

The chaotic recurrent neural net consists of N chaotic neural nets, which each receive an external input ai(t) and the output of N-1 chaotic neural nets among the N chaotic neural nets, to perform an operation given by a dynamic mathematical equation. This equation is tau 1 Yi(t+1) = EPSILON Wij Zi (t) + kYi (t) - alpha Xi(t) where Xi(t) = fi Yi(t). fi is the output function of a neuron. Wij is a synapse connection coefficient of the feedback input from the jth neuron to the ith neuron and Xi(t) is the output of the ith neuron at time t. tau i, a and k are a time delay constant, a non-negative parameter and a refractory time attenuation constant. Zi(t) represents Xi(t) when i belongs to the neuron group I, or ai(t) when i belongs to the external input group E.