State Estimation for Discrete Time-Delay Complex Networks with Switching Topologies and Binary Encoding Schemes

In this paper, the state estimation is investigated for a class of discrete-time delayed complex network with switching topologies and stochastic noises subject to binary encoding scheme (BES). The Markov chain is utilized to describe the random changes of network topologies. By using the BES, the original measurement signal is first encoded into a bit string, then transmitted via binary symmetric channels, and lastly restored by a decoder before entering the estimator. In the transmission process, random bit errors may occur in the bit string due to the channel noises. A set of Bernoulli distributed random variables is used to characterize such errors. The aim of this paper is to design a mode-dependent state estimator such that the estimation error dynamics is exponentially ultimately bounded in the mean square. A sufficient condition of the expected estimator is given by utilizing Lyapunov functional approach, and subsequently the estimator gain matrix is obtained by solving a certain matrix inequality. Finally, a simulation example is shown to certify the effectiveness of the state estimation scheme.