Kalman filtering has been widely considered for dynamic state estimation in smart grids. Despite its unique merits, the Kalman Filter (KF)-based dynamic state estimation can be undesirably influenced by cyber adversarial attacks that can potentially be launched against the communication links in the Cyber-Physical System (CPS). To enhance the security of KF-based state estimation, in this paper...

in this article, the discrete time state space model with first-order autoregressive dependent process noise is considered and the recursive method for filtering, prediction and smoothing of the hidden state from the noisy observation is designed. the explicit solution is obtained for the hidden state estimation problem. finally, in a simulation study, the performance of the designed method ...

The standard description of two-step extremum estimation amounts to plugging in a first step estimator of nuisance parameters in order to simplify the optimization problem and then to deduce a user friendly estimator for the parameters of interest. This two-step procedure often induces an e ciency loss with respect to estimation of the parameters of interest. In this paper, we consider a more g...

We introduce a new two-step kernel density estimation method, based on the EM algorithm and the generalized kernel density estimator. The accuracy obtained is better in particular, in the case of multimodal or skewed densities.