Response to external input of chaotic neural networks based on Newman-Watts model

In this paper, the synchronization characteristics in response to external inputs are investigated for chaotic neural networks with coupled lattices based on the Newman-Watts model. The Newman-Watts model was originally proposed with a ring-coupled lattice as its initial structure. However, ring-coupled networks are not suitable for a number of applications, including image processing. Therefore, in this paper, the synchronization characteristics in response to external inputs are investigated in a coupled lattice based on a Newman-Watts network. As a result, we find that synchronized clusters are generated in response to spatially distributed external inputs, and recombination of neurons into clusters occurs in the case that the parameter values of a single neuron correspond to those giving chaotic dynamics. Moreover, we explore the possibility that chaotic dynamics are useful for separating two image segments that have similar grayscale values by using the proposed network with synchronization.