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New Delay-Interval-Dependent Exponential Stability for Stochastic Neural Networks with Interval Time-Varying Delay and Distributed Delay

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Abstract

This paper deals with the problem of exponential stability for a class of stochastic neural networks with interval time-varying delay and distributed delay. Based on the idea of nonuniform partitioning for the delay interval, new delay-interval-dependent stability conditions are proposed in terms of linear matrix inequalities (LMIs) by constructing novel Augmented Lyapunov–Krasovskii functionals. Some numerical examples are presented to show the effectiveness and improvement of the proposed method.

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Acknowledgements

This work was supported the National Natural Science Foundation of China under Grant 61004046, 61174076, 61104117, the China Postdoctoral Science Foundation under Grant 20110491336, the Postdoctoral Science Foundation of Jiangsu Province under Grant 1001007C, the Young and Middle-Aged Scientists Research Awards Fund of Shandong Province under Grant 2009BSB01450.

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Authors and Affiliations

  1. School of Mathematics Science, Liaocheng University, Shandong, 252000, P.R. China

    Jianwei Xia & Hongxia Zheng

  2. School of Astronautics, Harbin Institute of Technology, Harbin, 150001, P.R. China

    JinYong Yu

  3. School of Science, Huzhou Teachers College, Huzhou, 313000, P.R. China

    Yongmin Li

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  1. Jianwei Xia
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  2. JinYong Yu
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  3. Yongmin Li
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  4. Hongxia Zheng
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Correspondence to Jianwei Xia.

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Xia, J., Yu, J., Li, Y. et al. New Delay-Interval-Dependent Exponential Stability for Stochastic Neural Networks with Interval Time-Varying Delay and Distributed Delay. Circuits Syst Signal Process 31, 1535–1557 (2012). https://doi.org/10.1007/s00034-011-9383-9

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  • DOI: https://doi.org/10.1007/s00034-011-9383-9

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