@article{article_406443, title={Stability Analysis of A Class of Takagı-Sugeno Fuzzy Cohen-Grossberg Neural Networks with Time Delays}, journal={Uludağ Üniversitesi Mühendislik Fakültesi Dergisi}, volume={23}, pages={45–54}, year={2018}, DOI={10.17482/uumfd.406443}, author={Özcan Semerci, Neyir and Barış, Samet}, keywords={T-S Fuzzy Neural Networks,Delayed Systems,Lyapunov Functionals}, abstract={<p> <span lang="en-us" style="line-height:115%;font-family:’Times New Roman’, serif;font-size:10pt;" xml:lang="en-us"> <font color="#000000">This paper deals with the problem of the global
asymptotic stability of the class of Takagi-Sugeno Fuzzy Cohen-Grossberg neural
networks with multiple time delays. By constructing a suitable fuzzy Lyapunov
functional, we present a new delay-independent sufficient condition for the
global asymptotic stability of the equilibrium point for delayed Takagi-Sugeno
Fuzzy Cohen-Grossberg neural networks with respect to the Lipschitz activation
functions. The obtained condition simply relies on the network parameters of the
neural system. Therefore, the equilibrium and stability properties of the
neural network model considered in this paper can be easily verified by
exploiting some basic properties of some certain classes of matrices. </font> </span> <br /> </p>}, number={2}, publisher={Bursa Uludağ University}