Robust stability of uncertain Markovian jumping Cohen–Grossberg neural networks with mixed time-varying delays

Li Sheng and Huizhong Yang

Chaos, Solitons & Fractals, 2009, vol. 42, issue 4, 2120-2128

Abstract: 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.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:42:y:2009:i:4:p:2120-2128

DOI: 10.1016/j.chaos.2009.03.161

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