Finite-time reliable filtering for T-S fuzzy stochastic jumping neural networks under unreliable communication links

Advances in Difference Equations

Huiling Duan¹  Tao Peng¹ 

[1] College of Mathematics and Statistics, Chongqing Three Gorges University, Wanzhou, P.R. China

关键词: finite-time boundedness;    discrete-time;    T-S fuzzy model;    Lyapunov-Krasovskii functional;    stochastic jumping neural networks;   

DOI  :  10.1186/s13662-017-1108-3

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

This study is concerned with the problem of finite-time state estimation for T-S fuzzy stochastic jumping neural networks, where the communication links between the stochastic jumping neural networks and its estimator are imperfect. By introducing the fuzzy technique, both the nonlinearities and the stochastic disturbances are represented by T-S model. Stochastic variables subject to the Bernoulli white sequences are employed to determine the nonlinearities occurring in different sector bounds. Some sufficient conditions for the existence of the state estimator are given in terms of linear matrix inequalities, whose effectiveness are illustrated with the aid of simulation results.

【 授权许可】

CC BY