Finite-Time Fault-Tolerant State Estimation for Markovian Jumping Neural Networks With Two Delay Components

This paper focuses on the finite time fault tolerant state estimation of Markovian jumping neural networks with two delay components. Firstly, mathematical expression estimator is defined when system components have faults and output has external disturbances. Then, an augmented Lyapunov-Krasovslii functional including additive information, information activation function used to derive stochastic stability conditions for error systems. In addition, some advanced reciprocally convex inequalities are obtain linear matrix inequality (LMI) that easy solve. Finally, numerical simulation carried out verify effectiveness proposed method. Numerical results show can still guarantee performance in framework even if there component faults.