Stability Analysis of Fuzzy Hopfield Neural Networks with Timevarying Delays
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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 = {2024},
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 = {1746-7659},
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 - 2024
DA - 2024/01
SN - 13
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22447.html
KW - asymptotic stability
KW - T-S fuzzy model
KW - Hopfield neural networks
KW - time-varying delay
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. (2024). 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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