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

机译:通信不可靠条件下的T-S模糊随机跳跃神经网络的有限时间可靠滤波

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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.
机译:该研究涉及T-S模糊随机跳跃神经网络的有限时间状态估计问题,其中随机跳跃神经网络与其估计量之间的通信联系不完善。通过引入模糊技术,非线性和随机扰动都可以用T-S模型表示。服从伯努利白色序列的随机变量用于确定在不同扇区边界中发生的非线性。根据线性矩阵不等式,给出了状态估计器存在的一些充分条件,并借助仿真结果说明了其有效性。

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