Robust stability of fuzzy Markov type Cohen-Grossberg neural networks by delay decomposition approach
R. Sathy, Pagavathigounder Balasubramaniam, R. Chandran · Iranian journal of fuzzy systems · 2014
In this paper, we investigate the delay-dependent robust stabil- ity of fuzzy Cohen-Grossberg neural networks with Markovian jumping pa- rameter and mixed time varying delays by delay decomposition method. A new Lyapunov-Krasovskii functional (LKF) is constructed by nonuniformly dividing discrete delay interval into multiple subinterval, and choosing proper functionals with different weighting matrices corresponding to different subin- tervals in the LKFs. A new delay-dependent stability condition is derived with Markovian jumping parameters by T-S fuzzy model. Based on the linear ma- trix inequality (LMI) technique, maximum admissible upper bound (MAUB) for the discrete and distributed delays are calculated by the LMI Toolbox in MATLAB. Numerical examples are given to illustrate the effectiveness of the proposed method.