Equilibrium and Stability Analysis of Takagi-Sugeno Fuzzy Delayed Cohen-Grossberg Neural Networks

Authors : Neyir OZCAN

Pages : 1411-1426

Doi:10.31801/cfsuasmas.455799

View : 13 | Download : 11

Publication Date : 2019-08-01

Article Type : Research Paper

Abstract :This paper carries out an investigation into the problem of the global asymptotic   stability of the class of Takagi-Sugeno insert ignore into journalissuearticles values(T-S); fuzzy delayed Cohen-Grossberg neural  networks with discrete time delays. A new sufficient criterion for the uniqueness and  global asymptotic stability of the equilibrium point for this class of fuzzy neural networks  is proposed. The uniqueness of the equilibrium point is proved by using the contradiction  method. The stability of the equilibrium point is established by employing a new fuzzy  type Lyapunov functional. The obtained stability result is obtained with respect to the  nondecreasing and slope-bounded activation functions it can be shown to be independent  of time delays. The proposed result can be easily verified by using some commonly used  norm properties of matrices.
Keywords : Stability Theory, Equilibrium Analysis, Cohen Grossberg Neural Networks, Delayed T S Fuzzy Systems