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Volume 2017 (2017), Article ID 3826729, 12 pages
Research Article

Impulsive Disturbances on the Dynamical Behavior of Complex-Valued Cohen-Grossberg Neural Networks with Both Time-Varying Delays and Continuously Distributed Delays

1Key Laboratory of Fluid and Power Machinery, Ministry of Education, Xihua University, Chengdu 610039, China
2Key Laboratory of Automotive Measurement, Control and Safety, Sichuan Province, Xihua University, Chengdu 610039, China
3National Traction Power Laboratory, Southwest Jiaotong University, Chengdu 610031, China
4School of Technology, Xihua University, Chengdu 610039, China
5Institute of Information Research, Southwest Jiaotong University, Chengdu 610031, China

Correspondence should be addressed to Xiaohui Xu

Received 18 May 2017; Accepted 20 September 2017; Published 31 October 2017

Academic Editor: Sigurdur F. Hafstein

Copyright © 2017 Xiaohui Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper studies the global exponential stability for a class of impulsive disturbance complex-valued Cohen-Grossberg neural networks with both time-varying delays and continuously distributed delays. Firstly, the existence and uniqueness of the equilibrium point of the system are analyzed by using the corresponding property of -matrix and the theorem of homeomorphism mapping. Secondly, the global exponential stability of the equilibrium point of the system is studied by applying the vector Lyapunov function method and the mathematical induction method. The established sufficient conditions show the effects of both delays and impulsive strength on the exponential convergence rate. The obtained results in this paper are with a lower level of conservatism in comparison with some existing ones. Finally, three numerical examples with simulation results are given to illustrate the correctness of the proposed results.