Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 19, Issue 11, Pages 1942-1955Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2008.2006337
Keywords
Cohen-Grossberg neural networks; Halanay inequality; interval neural networks; linear matrix inequality (LMI); M-matrix; robust stability; time-varying delays
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Funding
- National Natural Science Foundation of China [60534010, 60572070, 60728307, 60774048, 60774093]
- Program for Cheung Kong Scholars and Innovative Research Groups of China [60521003]
- National High Technology Research and Development Program of China [2006AA04Z183]
- I I I Project of China Ministry of Education [B08015]
- Natural Science Foundation of Liaoning Province [20072025]
- Postdoctoral Foundation of Northeastern University [20080314]
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In this paper, robust stability problems for interval Cohen-Grossberg neural networks with unknown time-varying delays are investigated. Using linear matrix inequality, M-matrix theory, and Halanay inequality techniques, new sufficient conditions independent of time-varying delays are derived to guarantee the uniqueness and the global robust stability of the equilibrium point of interval Cohen-Grossberg neural networks with time-varying delays. All these results have no restriction on the rate of change of the time-varying delays. Compared to some existing results, these new criteria are less conservative and are more convenient to check. Two numerical examples are used to show the effectiveness of the present results.
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