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Stability of uncertain impulsive stochastic fuzzy neural networks with two additive time delays in the leakage term

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Abstract

This paper is concerned with the stability problem for a class of impulsive neural networks model, which includes simultaneously parameter uncertainties, stochastic disturbances and two additive time-varying delays in the leakage term. By constructing a suitable Lyapunov–Krasovskii functional that uses the information on the lower and upper bound of the delay sufficiently, a delay-dependent stability criterion is derived by using the free-weighting matrices method for such Takagi–Sugeno fuzzy uncertain impulsive stochastic recurrent neural networks. The obtained conditions are expressed with linear matrix inequalities (LMIs) whose feasibility can be checked easily by MATLAB LMI Control toolbox. Finally, the theoretical result is validated by simulations.

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Acknowledgments

This work was supported by the Fundamental Research Funds for the Central Universities (JUSRP51317B, JUSRP211A21).

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Authors and Affiliations

  1. Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Institute of Automation, Jiangnan University, Wuxi, 214122, China

    Manfeng Hu

  2. School of Science, Jiangnan University, Wuxi, 214122, China

    Jun Li, Manfeng Hu, Liuxiao Guo, Yongqing Yang & Yinghua Jin

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  1. Jun Li
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  2. Manfeng Hu
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  3. Liuxiao Guo
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  4. Yongqing Yang
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  5. Yinghua Jin
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Correspondence to Manfeng Hu.

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Li, J., Hu, M., Guo, L. et al. Stability of uncertain impulsive stochastic fuzzy neural networks with two additive time delays in the leakage term. Neural Comput & Applic 26, 417–427 (2015). https://doi.org/10.1007/s00521-014-1737-3

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  • DOI: https://doi.org/10.1007/s00521-014-1737-3

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