in the several past years, extended kalman filter (ekf) and unscented kalman filter (ukf) havebecame basic algorithm for state-variables and parameters estimation of discrete nonlinear systems.the ukf has consistently outperformed for estimation. sometimes least estimation error doesn't yieldwith ukf for the most nonlinear systems. in this paper, we use a new approach for a two variablesta...

Active filters are power electronics devices used to eliminate harmonics from the distribution network. This article presents an active disturbance rejection control scheme for active filters. The controller is based on a linear disturbance observer combined with a disturbance rejection scheme. The parameter tuning is based on a combined pole placement and an optimal estimation based on Kalman-...

This paper formulates and proposes solutions to the problem of estimating/reconstructing the absolute (not simply modulo-2pi) phase of a complex random field from noisy observations of its real and imaginary parts. This problem is representative of a class of important imaging techniques such as interferometric synthetic aperture radar, optical interferometry, magnetic resonance imaging, and di...

In practical situations, we observe the number of claims to an insurance portfolio but not the claim intensity. It is therefore of interest to try to solve the` ltering problem', that is to obtain the best estimate of the claim intensity on the basis of reported claims. In order to use the Kalman-Bucy lter, based on the Cox process incorporating a shot noise process as claim intensity, we need ...

Abstract In this article we consider the estimation of log-normalization constant associated to a class continuous-time filtering models. particular, ensemble Kalman–Bucy filter estimates based upon several nonlinear diffusions. Using new conditional bias results for mean aforementioned methods, analyze empirical log-scale normalization constants in terms their $\mathbb{L}_n$ -errors and -condi...

We provide a continuous time limit analysis for the class of Ensemble Square Root Filter algorithms with deterministic model perturbations. In particular linear case, we specify general conditions on perturbations implying convergence empirical mean and covariance matrix towards their respective counterparts Kalman-Bucy Filter. As second main result identify additional assumptions whole ensembl...

There are several functional forms for non-linear dynamical filters. Extended Kalman filters algorithms that used to estimate more accurate values of unknown quantities internal systems from a sequence noisy observation measured over period time. This filtering process becomes computationally expensive when subjected high dimensional data which consequently has negative impact on the filter per...