Stability analysis of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays

IEEE Trans Syst Man Cybern B Cybern. 2007 Jun;37(3):720-6. doi: 10.1109/tsmcb.2006.889628.

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.

Publication types

  • Letter

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Markov Chains
  • Models, Statistical*
  • Neural Networks, Computer*
  • Nonlinear Dynamics*
  • Pattern Recognition, Automated / methods*
  • Stochastic Processes