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.