Finite-time stability of neutral-type neural networks with random time-varying delays

M. Syed Ali, S. Saravanan and Quanxin Zhu

International Journal of Systems Science, 2017, vol. 48, issue 15, 3279-3295

Abstract: This paper is devoted to the finite-time stability analysis of neutral-type neural networks with random time-varying delays. The randomly time-varying delays are characterised by Bernoulli stochastic variable. This result can be extended to analysis and design for neutral-type neural networks with random time-varying delays. On the basis of this paper, we constructed suitable Lyapunov–Krasovskii functional together and established a set of sufficient linear matrix inequalities approach to guarantee the finite-time stability of the system concerned. By employing the Jensen's inequality, free-weighting matrix method and Wirtinger's double integral inequality, the proposed conditions are derived and two numerical examples are addressed for the effectiveness of the developed techniques.

Date: 2017
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DOI: 10.1080/00207721.2017.1367434

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