Finite-Time Synchronization of Coupled Hierarchical Hybrid Neural Networks With Time-Varying Delays

This paper is concerned with the finite-time synchronization problem of coupled hierarchical hybrid delayed neural networks. This coupled hierarchical hybrid neural networks consist of a higher level switching and a lower level Markovian jumping. The time-varying delays are dependent on not only switching signal but also jumping mode. By using a less conservative weighted integral inequality and stochastic multiple Lyapunov-Krasovskii functional, new finite-time synchronization criteria are obtained, which makes the state trajectories be kept within the prescribed bound in a time interval. Finally, an example is proposed to demonstrate the effectiveness of the obtained results.

I. Introduction

Complex networks have gained widespread concerns ever since small-world networks and scale-free networks were investigated in [1]–[3]. There are many applications in complex networks, such as electrical power grids [4], cellular and metabolic networks [5], and neural adaptive controllers applied in robot systems firstly [6], [7]. At the same time, the coupled neural networks system, as a special kind of complex networks, has been widely investigated by many researchers [8]–[16].