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Computational Intelligence and Neuroscience
Volume 2016, Article ID 3587271, 13 pages
http://dx.doi.org/10.1155/2016/3587271
Research Article

Almost Periodic Dynamics for Memristor-Based Shunting Inhibitory Cellular Neural Networks with Leakage Delays

Research Center of Modern Enterprise Management of Guilin University of Technology, Guilin University of Technology, Guilin 541004, China

Received 16 May 2016; Accepted 31 July 2016

Academic Editor: Paolo Del Giudice

Copyright © 2016 Lin Lu and Chaoling 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

We investigate a class of memristor-based shunting inhibitory cellular neural networks with leakage delays. By applying a new Lyapunov function method, we prove that the neural network which has a unique almost periodic solution is globally exponentially stable. Moreover, the theoretical findings of this paper on the almost periodic solution are applied to prove the existence and stability of periodic solution for memristor-based shunting inhibitory cellular neural networks with leakage delays and periodic coefficients. An example is given to illustrate the effectiveness of the theoretical results. The results obtained in this paper are completely new and complement the previously known studies of Wu (2011) and Chen and Cao (2002).