@article{article_455799, title={Equilibrium and Stability Analysis of Takagi-Sugeno Fuzzy Delayed Cohen-Grossberg Neural Networks}, journal={Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics}, volume={68}, pages={1411–1426}, year={2019}, DOI={10.31801/cfsuasmas.455799}, author={Ozcan, Neyir}, keywords={Stability Theory,Equilibrium Analysis,Cohen-Grossberg Neural Networks,Delayed T-S Fuzzy Systems}, abstract={<span style="font-size:12.6px;">This paper carries out an investigation into the problem of the global asymptotic </span> <span style="font-size:12px;">  </span> <span style="font-size:12px;">stability of the class of Takagi-Sugeno (T-S) fuzzy delayed Cohen-Grossberg neural  </span> <span style="font-size:12px;">networks with discrete time delays. A new sufficient criterion for the uniqueness and  </span> <span style="font-size:12px;">global asymptotic stability of the equilibrium point for this class of fuzzy neural networks  </span> <span style="font-size:12px;">is proposed. The uniqueness of the equilibrium point is proved by using the contradiction  </span> <span style="font-size:12px;">method. The stability of the equilibrium point is established by employing a new fuzzy  </span> <span style="font-size:12px;">type Lyapunov functional. The obtained stability result is obtained with respect to the  </span> <span style="font-size:12px;">nondecreasing and slope-bounded activation functions it can be shown to be independent  </span> <span style="font-size:12px;">of time delays. The proposed result can be easily verified by using some commonly used  </span> <span style="font-size:12px;">norm properties of matrices. </span> <br />}, number={2}, publisher={Ankara University}