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Novel Delay-Dependent Stability Results for Neural Networks with Time-Varying Delays

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Abstract

This paper is concerned with the stability of static neural networks with time-varying delays. With the construction of a new Lyapunov functional and advanced techniques for calculating its derivative, a delay-dependent stability criterion is obtained that is less conservative than existing ones. A delay-independent criterion is also given that, together with the delay-dependent one, can be checked using recently developed algorithms. Examples are provided to illustrate the effectiveness and the reduced conservatism of the proposed results.

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Authors and Affiliations

  1. School of Electrical and Information Automation, Qufu Normal University, Rizhao, Shandong, 276826, China

    Hanyong Shao

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  1. Hanyong Shao
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Correspondence to Hanyong Shao.

Additional information

This work was supported in part by Shandong Provincial Nature Science Foundation of China under Grant ZR2009AM018, and in part by Science Research Foundation of Qufu Normal University under Grant XJZ200854.

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Shao, H. Novel Delay-Dependent Stability Results for Neural Networks with Time-Varying Delays. Circuits Syst Signal Process 29, 637–647 (2010). https://doi.org/10.1007/s00034-010-9164-x

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  • DOI: https://doi.org/10.1007/s00034-010-9164-x

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