Finite-time Synchronization of Fuzzy Cellular Neural Networks with Stochastic Perturbations and Mixed Delays

Abstract

This paper investigates finite-time synchronization for fuzzy cellular neural networks (FCNNs). In contrast to correlative studies, discrete time delays, distributed delays and stochastic perturbations are taken into consideration. A mathematical model of this kind of FCNN is considered for the first time. By employing the Lyapunov method, graph theory, the feedback control technique and stochastic finite-time synchronization theory, several sufficient conditions for finite-time synchronization of FCNNs are derived. The upper bound of the stochastic settling time is explicitly proposed and has a close relationship with the topological structure of the neural network. Finally, a numerical example is used to validate the practicability and feasibility of the theoretical results we propose.