Delay decomposition approach to state estimation of neural networks with mixed time-varying delays and Markovian jumping parameters

This paper investigates the state estimation of neural networks with mixed time-varying delays and Markovian jumping parameters. By developing a delay decomposition approach, the information of the delayed plant states can be taken into full consideration. On the basis of the new Lyapunov-Krasovskii functional, some inequality techniques, stochastic stability theory and delay-dependent stability criteria are obtained in terms of linear matrix inequalities. Finally, three numerical examples are given to illustrate the less conservative and effectiveness of our theoretical results.