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Jianning Li,Zhujian Li,Yufei Xu,Kaiyang Gu,Wendong Bao,Xiaobin Xu 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.5
This paper investigates the non-fragile state estimation problem for discrete nonlinear Markov jump neural networks(MJNNs) with sensor failures. Due to the limit communication resource, we adopt a kind of eventtriggered mechanism to determine whether the sensor sampling information is sent or not. By selecting suitable Lyapunov functions, a sufficient condition is obtained to guarantee the mean-square exponential stability of the augmented system. Finally, a numerical example is given to show the effectiveness of the proposed method.