Event-triggered Non-fragile State Estimation for Discrete Nonlinear Markov Jump Neural Networks with Sensor Failures

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 event-triggered 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.