期刊
CHAOS SOLITONS & FRACTALS
卷 42, 期 4, 页码 2120-2128出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2009.03.161
关键词
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资金
- National Natural Science Foundation of China [60674092]
- High-tech R & D Program of Jiangsu (Industry) [BG2006010]
This paper considers the robust stability of a class of uncertain Markovian jumping Cohen-Grossberg neural networks (UMJCGNNs) with mixed time-varying delays. The parameter uncertainties are norm-bounded and the mixed time-varying delays comprise discrete and distributed time delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. An example is given to show the effectiveness of the proposed results. (C) 2009 Elsevier Ltd. All rights reserved.
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