Non-fragile exponential state estimation for continuous-time fuzzy stochastic neural networks with time-varying delays

作者：Hua, Mingang^*; Cai, Yixi; Fei, Juntao

来源：Journal of Intelligent and Fuzzy Systems, 2016, 30(5): 2915-2926.

DOI：10.3233/IFS-151789

• Non-fragile
• state estimation
• Takagi-Sugeno
• stochastic neural networks
• exponential stability

This paper investigates non-fragile exponential state estimation problems for continuous-time fuzzy stochastic neural networks with time-varying delays. The Takagi-Sugeno (T-S) fuzzy model representation is extended to the exponential state estimator design for fuzzy stochastic neural networks with time-varying delays. The neuron activation function and the nonlinear measurement equation are assumed to be satisfy sector-bounded conditions and standard Lipschitz conditions. For these two conditions, delay-dependent sufficient conditions are presented to guarantee the existence of the desired state estimators for fuzzy stochastic neural networks. Finally, two numerical examples are given to demonstrate that the proposed approaches are effective and that the sector-bounded conditions are weaker than the standard Lipschitz conditions.

• 出版日期2016
• 单位河海大学