Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control.
This paper investigates the exponential synchronization of coupled memristor-based chaotic neural networks with both time-varying delays and general activation functions. And here, we adopt nonsmooth analysis and control theory to handle memristor-based chaotic neural networks with discontinuous right-hand side. In particular, several new criteria ensuring exponential synchronization of two memristor-based chaotic neural networks are obtained via periodically intermittent control. In addition, the new proposed results here are very easy to verify and also complement, extend the earlier publications. Numerical simulations on the chaotic systems are presented to illustrate the effectiveness of the theoretical results.
School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China. Electronic address: zgdhbnu@163.com.
Guodong
G
Zhang
School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China. Electronic address: yishen64@163.com.
Yi
Y
Shen
D000465:Algorithms; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors
Chaotic dynamical systems; Exponential synchronization; Intermittent control; Memristor; Time-varying delays