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This technical note studies the state estimation problem for stochastic complex networks with switching topology. A set of Bernoulli random variables are used to describe the switching behavior of the network. By using the structure of the extended Kalman filter (EKF), a recursive estimator is developed for each node to guarantee an optimized upper bound on the state estimation error covariance despite...
This paper studies the state estimation problem for a class of discrete-time nonlinear complex networks. A recursive state estimator is developed by employing the structure of the extended Kalman filter (EKF) with coupling terms. By using the stochastic analysis technique, an upper bound is derived for the coupling strength to guarantee the boundedness of the estimation errors in the mean square sense...
In this paper, we generalize the classical risk model and get a Cox risk model with multiple risk. Then we get exponential upper bounds for the ruin probability by using martingale theory in this new model. And we give some main results of Lundberg exponent, when claim occurs with the same cumulative intensity process. Finally, the value of Lundberg exponent is calculated through an example.
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