时空时滞混沌系统反同步控制及应用研究

ANTI-SYNCHRONIZATION CONTROL FOR SPATIOTEMPORAL DELAYED CHAOTIC SYSTEMS AND ITS APPLICATION

针对一类新的时空时滞惯性神经网络,研究其反同步控制及在图像保密通信上的应用。采用变量代换准则,避免了原二阶微分系统固有的复杂特性;设计一个有效地输出反馈控制器,并结合詹森(Jensen)不等式和互凸组合(RCC)方法,得到了一个较小保守性的时空时滞惯性神经网络反同步定理;通过仿真实现了主要结果在图像保密通信上的应用并证明了所提加密方法的优越性。

For a novel class of spatiotemporal delayed inertial neural networks(SDINNs),its anti-synchronization control and application on image secure communication are studied.A variable substitution was used to avoid the inherent complex characteristics of the original second-order differential system.It designed an effective output feedback controller and combined with Jensen's inequality and the reciprocally convex combination(RCC)method,so that a less conservative anti-synchronization theorem of the SDINNs was obtained.The simulation realized the application of the main results on image secure communication and illustrated the superiority of the encryption method of this paper.