Stability and Existence of Anti-Periodic Solution for FCNNs With Time-Varying Delays and Impulsive Impacts

Abstract

This paper deals with the problem of anti-periodic solution for fuzzy cellular neural networks (FCNNs) with time-varying delays and impulsive impacts. Utilizing Krasnoselski's fixed point theorem and contraction principle, developing some appropriate Lyapunov functional, some adequate conditions are set up for the global exponential stability and existence of anti-periodic solutions of FCNNs with time-varying delays and impulsive impacts. In addition, a model is exhibited to represent results setup.INDEX TERMS Exponential stability, anti-periodic solution, fuzzy cellular neural networks, time-varying delays, impulsive impacts.

Existence and Exponential Stability of Anti-Periodic Solutions for Inertial Quaternion-Valued High-Order Hopfield Neural Networks With State-Dependent Delays

“…In addition, as we know, periodicity, anti-periodicity, and almost periodicity are important dynamic properties of timevarying neural network systems, and since neural network signal transmission processes can often be described as anti-periodic processes, many authors have studied the antiperiodicity of various types of neural networks [20]- [27].…”