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Abstract and Applied Analysis
Volume 2014, Article ID 560861, 12 pages
Research Article

Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

1College of Automation, Chongqing University, Chongqing 400044, China
2Department of Mathematics and Information Engineering, Chongqing University of Education, Chongqing 400065, China
3School of Engineering, University of Guelph, Guelph, ON, Canada N1G 2W1

Received 5 March 2014; Accepted 2 May 2014; Published 27 May 2014

Academic Editor: Gani Stamov

Copyright © 2014 Wei Feng 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.


The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties. The results we obtained in this paper are delay-derivative-dependent and establish various relationships between the network parameters only. Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported literature results. Two numerical examples are illustrated to verify our results.