SICNNs with Li-Yorke Chaotic Outputs on a Time Scale

TL;DR

This paper proves the existence of Li-Yorke chaos in SICNNs on time scales, demonstrates control of this chaos, and supports findings with simulations, marking a novel contribution to neural network dynamics on time scales.

Contribution

It is the first study to establish the existence and controllability of Li-Yorke chaos in SICNNs on time scales, combining theoretical proofs with simulation validation.

Findings

SICNNs exhibit Li-Yorke chaos on time scales.

Chaos controllability is demonstrated using Pyragas control.

Theoretical results are supported by simulations.

Abstract

In the present study, we investigate the existence of Li-Yorke chaos in the dynamics of shunting inhibitory cellular neural networks (SICNNs) on time scales. It is rigorously proved by taking advantage of external inputs that the outputs of SICNNs exhibit Li-Yorke chaos. The theoretical results are supported by simulations, and the controllability of chaos on the time scale is demonstrated by means of the Pyragas control technique. This is the first time in the literature that the existence as well as the control of chaos are provided for neural networks on time scales.