Abstract
This article is devoted to coping with the state estimate problem for a class of Itô stochastic complex network. The target network under consideration is a hybrid system involving Markovian jumping parameters and mode-dependent distributed time-delays, and the system noise is characterized by the Brownian Motion. The problem addressed is to design a state estimator to track the states of target network under the assumption that the network outputs are from only a portion of network nodes. By utilizing the Lyapunov stability method and the Itô stochastic differential equation theory, sufficient conditions are educed so that the state estimation error of the estimator is mean-square exponentially ultimately bounded. In particular, in the case that the system is noise-free, the derived conditions can ensure the state estimation error is mean-square exponentially stable. Furthermore, the estimator design can be made by solving a set of matrix inequalities. Lastly, a numerical example is exploited to indicates the validity of the theoretical results.
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