title: Stability analysis of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays.
abstract: This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov-Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov-Krasovskii functional, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results.
authors.forename: Yi-You
authors.initials: YY
authors.lastname: Hou
authors.forename: Teh-Lu
authors.initials: TL
authors.lastname: Liao
authors.forename: Jun-Juh
authors.initials: JJ
authors.lastname: Yan
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008390:Markov Chains; D015233:Models, Statistical; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods*; D013269:Stochastic Processes