Stability Analysis of Fuzzy Hopfield Neural Networks with Timevarying Delays

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Volume 13, Issue 3

Qifeng Xun and Caigen Zhou

J. Info. Comput. Sci. , 13 (2018), pp. 212-222.

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Abstract

School of Information Engineering, Yancheng Teachers University, 224002 Yancheng, China (Received June 07 2018, accepted August 22 2018) In this paper, the problem of asymptotic stability for Takagi-Sugeno (T-S) fuzzy Hopfield neural networks with time-varying delays is studied. Based on the Lyapunov functional method, considering the system with uncertainties or without uncertainties, new delay-dependent stability criteria are derived in terms of Linear Matrix Inequalities (LMIs) that can be calculated easily by the LMI Toolbox in MATLAB. The proposed approach does not involve free weighting matrices and can provide less conservative results than some existing ones. Besides, numerical examples are given to show the effectiveness of the proposed approach.

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@Article{JICS-13-212, author = {Qifeng Xun and Caigen Zhou}, title = {Stability Analysis of Fuzzy Hopfield Neural Networks with Timevarying Delays}, journal = {Journal of Information and Computing Science}, year = {2018}, volume = {13}, number = {3}, pages = {212--222}, abstract = {School of Information Engineering, Yancheng Teachers University, 224002 Yancheng, China (Received June 07 2018, accepted August 22 2018) In this paper, the problem of asymptotic stability for Takagi-Sugeno (T-S) fuzzy Hopfield neural networks with time-varying delays is studied. Based on the Lyapunov functional method, considering the system with uncertainties or without uncertainties, new delay-dependent stability criteria are derived in terms of Linear Matrix Inequalities (LMIs) that can be calculated easily by the LMI Toolbox in MATLAB. The proposed approach does not involve free weighting matrices and can provide less conservative results than some existing ones. Besides, numerical examples are given to show the effectiveness of the proposed approach. }, issn = {3080-180X}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22447.html} }

TY - JOUR T1 - Stability Analysis of Fuzzy Hopfield Neural Networks with Timevarying Delays AU - Qifeng Xun and Caigen Zhou JO - Journal of Information and Computing Science VL - 3 SP - 212 EP - 222 PY - 2018 DA - 2018/09 SN - 13 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22447.html KW - AB - School of Information Engineering, Yancheng Teachers University, 224002 Yancheng, China (Received June 07 2018, accepted August 22 2018) In this paper, the problem of asymptotic stability for Takagi-Sugeno (T-S) fuzzy Hopfield neural networks with time-varying delays is studied. Based on the Lyapunov functional method, considering the system with uncertainties or without uncertainties, new delay-dependent stability criteria are derived in terms of Linear Matrix Inequalities (LMIs) that can be calculated easily by the LMI Toolbox in MATLAB. The proposed approach does not involve free weighting matrices and can provide less conservative results than some existing ones. Besides, numerical examples are given to show the effectiveness of the proposed approach.

Qifeng Xun and Caigen Zhou. (2018). Stability Analysis of Fuzzy Hopfield Neural Networks with Timevarying Delays. Journal of Information and Computing Science. 13 (3). 212-222. doi:

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