Exponential convergence rate estimation for uncertain delayed neural networks of neutral type

Chang-Hua Lien, Ker-Wei Yu, Yen-Feng Lin, Yeong-Jay Chung and Long-Yeu Chung

Chaos, Solitons & Fractals, 2009, vol. 40, issue 5, 2491-2499

Abstract: The global exponential stability for a class of uncertain delayed neural networks (DNNs) of neutral type is investigated in this paper. Delay-dependent and delay-independent criteria are proposed to guarantee the robust stability of DNNs via LMI and Razumikhin-like approaches. For a given delay, the maximal allowable exponential convergence rate will be estimated. Some numerical examples are given to illustrate the effectiveness of our results. The simulation results reveal significant improvement over the recent results.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:40:y:2009:i:5:p:2491-2499

DOI: 10.1016/j.chaos.2007.10.043

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