Anti-synchronization of complex-valued memristor-based delayed neural networks.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

This paper investigates the anti-synchronization of complex-valued memristor-based neural networks with time delays via designed external controllers. By constructing appropriate Lyapunov functions and using inequality technique, two different types of controllers are derived to guarantee the exponential anti-synchronization of complex-valued memristor-based delayed neural networks. Compared with existing relevant results, the proposed results of this paper are more general and less conservative. In addition, the presented theoretical results are easy to be checked with the parameters of systems themselves. Finally, an example with numerical simulations illustrates the effectiveness of the obtained results.

Authors

  • Dan Liu
    Department of Bioengineering, Temple University, Philadelphia, PA, United States.
  • Song Zhu
    College of Sciences, China University of Mining and Technology, Xuzhou, 221116, China. Electronic address: songzhu82@gmail.com.
  • Kaili Sun
    School of Mathematics, China University of Mining and Technology, Xuzhou 221116, China.