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Journal of Applied Mathematics
Volume 2014, Article ID 705496, 8 pages
http://dx.doi.org/10.1155/2014/705496
Research Article

Global Exponential Robust Stability of High-Order Hopfield Neural Networks with S-Type Distributed Time Delays

1College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
2School of Mathematical Sciences, Ocean University of China, Qingdao 266100, China
3College of Marine Life Science and School of Mathematical Sciences, Ocean University of China, Qingdao 266100, China

Received 24 March 2014; Accepted 1 June 2014; Published 26 June 2014

Academic Editor: Reinaldo Martinez Palhares

Copyright © 2014 Haiyong Zheng 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.

Abstract

By employing differential inequality technique and Lyapunov functional method, some criteria of global exponential robust stability for the high-order neural networks with S-type distributed time delays are established, which are easy to be verified with a wider adaptive scope.