New conditions for synchronization of a class of chaotic neural networks

摘要

Chaos control and synchronization in the chaotic neural networks is discussed in this paper. Based on the stability theory of a cascade-connected system, adaptive control laws are presented to achieve chaos synchronization. The sliding model synchronization controller designed to satisfy the external disturbance vector with unknown upper bound. The advantage of the proposed controllers is that they are linear and have lower dimensions than that of the states. Simulation results for chaotic systems are provided to illustrate the effectiveness of the proposed scheme.