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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 236189, 12 pages
http://dx.doi.org/10.1155/2013/236189
Research Article

Stability of Almost Periodic Solution for a General Class of Discontinuous Neural Networks with Mixed Time-Varying Delays

College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China

Received 2 September 2013; Accepted 5 November 2013

Academic Editor: Huaiqin Wu

Copyright © 2013 Yingwei Li. 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.

Abstract

The global exponential stability issues are considered for almost periodic solution of the neural networks with mixed time-varying delays and discontinuous neuron activations. Some sufficient conditions for the existence, uniqueness, and global exponential stability of almost periodic solution are achieved in terms of certain linear matrix inequalities (LMIs), by applying differential inclusions theory, matrix inequality analysis technique, and generalized Lyapunov functional approach. In addition, the existence and asymptotically almost periodic behavior of the solution of the neural networks are also investigated under the framework of the solution in the sense of Filippov. Two simulation examples are given to illustrate the validity of the theoretical results.