Stability analysis of fuzzy Markovian jumping Cohen-Grossberg BAM neural networks with mixed time-varying delays.

*(English)*Zbl 1221.34201Summary: We investigate the robust stability of uncertain fuzzy Markovian jumping Cohen–Grossberg BAM neural networks with discrete and distributed time-varying delays. A new delay-dependent stability condition is derived under uncertain switching probabilities by Takagi–Sugeno fuzzy model. Based on the Linear Matrix Inequality (LMI) technique, upper bounds for the discrete and distributed delays are calculated using the LMI toolbox in MATLAB. Numerical examples are provided to illustrate the effectiveness of the proposed method.

##### MSC:

34K20 | Stability theory of functional-differential equations |

34K36 | Fuzzy functional-differential equations |

60J28 | Applications of continuous-time Markov processes on discrete state spaces |

92B20 | Neural networks for/in biological studies, artificial life and related topics |

##### Keywords:

stability; fuzzy; Markovian jumping; Cohen–Grossberg neural networks; bi-directional associative memory; mixed time-varying delays
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\textit{R. Sathy} and \textit{P. Balasubramaniam}, Commun. Nonlinear Sci. Numer. Simul. 16, No. 4, 2054--2064 (2011; Zbl 1221.34201)

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