Adaptive exponential synchronization of complex-valued Cohen-Grossberg neural networks with known and unknown parameters.

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

Abstract

The complex-valued Cohen-Grossberg neural network is a special kind of complex-valued neural network. In this paper, the synchronization problem of a class of complex-valued Cohen-Grossberg neural networks with known and unknown parameters is investigated. By using Lyapunov functionals and the adaptive control method based on parameter identification, some adaptive feedback schemes are proposed to achieve synchronization exponentially between the drive and response systems. The results obtained in this paper have extended and improved some previous works on adaptive synchronization of Cohen-Grossberg neural networks. Finally, two numerical examples are given to demonstrate the effectiveness of the theoretical results.

Authors

  • Jin Hu
    Department of Mathematics, Chongqing Jiaotong University, Chongqing, China. Electronic address: windyvictor@gmail.com.
  • Chunna Zeng
    College of Mathematical Sciences, Chongqing Normal University, Chongqing, China. Electronic address: zengchn@163.com.