Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19167
Title: Deriving sufficient conditions for global asymptotic stability of delayed neural networks via nonsmooth analysis - II
Authors: Qi, H
Qi, L 
Yang, X 
Keywords: Equilibrium point
Global asymptotic stability
Lipschitzian functions
Neural networks
Nonsmooth analysis
Issue Date: 2005
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on neural networks, 2005, v. 16, no. 6, p. 1701-1706 How to cite?
Journal: IEEE transactions on neural networks 
Abstract: Following our recent approach of nonsmooth analysis, we report a new set of sufficient conditions and its implications for the global asymptotic stability of delayed cellular neural networks (DCNN). The new conditions not only unify a string of previous stability results, but also yield strict improvement over them by allowing the symmetric part of the feedback matrix positive definite, hence enlarging the application domain of DCNNs. Advantages of the new results over existing ones are illustrated with examples. We also compare our results with those related results obtained via LMI approach.
URI: http://hdl.handle.net/10397/19167
ISSN: 1045-9227
DOI: 10.1109/TNN.2005.852975
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