Finite-Time Synchronization of Coupled Hierarchical Hybrid Neural Networks With Time-Varying Delays
研究了耦合分层混合时滞神经网络的有限时间同步问题，网络包含高层切换和低层马尔可夫跳变，通过加权积分不等式和随机Lyapunov泛函得到同步判据，使状态轨迹在时间区间内保持在预设界内。
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.