Journal
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
Volume 56, Issue 3, Pages 616-629Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSI.2008.2002556
Keywords
Cohen-Grossberg neural networks; distributed delays; global asymptotic stability; linear matrix inequality (LMI); multiple time-varying delays; nonnegative equilibrium points; robust stability
Categories
Funding
- National Natural Science Foundation of China [60534010, 60572070, 60728307, 60774048, 60774093]
- Ministry of Education ofChina [B08015]
- Natural Science Foundation of Liaoning Province [20072025]
- Innovative Research Groups of China [60521003]
- National High Technology Research and Development Program of China [2006AA04Z 183]
- Postdoctor Foundation of Northeastern University [20080314]
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This paper is concerned with the global asymptotic stability of a class of Cohen-Grossberg neural networks with both multiple time-varying delays and continuously distributed delays. Two classes of amplification functions are considered, and some sufficient stability criteria are established to ensure the global asymptotic stability of the concerned neural networks, which can be expressed in the form of linear matrix inequality and are easy to check. Furthermore, some sufficient conditions guaranteeing the global robust stability are also established in the case of parameter uncertainties.
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