AbstractThe Wiener-Hopf equations of the Kalman-Bucy estimate can be solved, owing to the assumption that the covariance matrix of the observation noise is invertible. It will be shown that this property is already needed from the very outset, where the estimate is represented as a stochastic integral. This representation will be characterized by means of a generalization of a theorem of Karhunen. Then it can be shown that the usual formal derivations, leading to the filter equations, are legitimate
AbstractThe problem of optimal linear estimation for continuous time processes is investigated. The ...
AbstractA stochastic integral with respect to a generalized, i.e., not necessarily time-homogeneous,...
This thesis is on filtering in state space models. First, we examine approximate Kalman filters for ...
AbstractThe Wiener-Hopf equations of the Kalman-Bucy estimate can be solved, owing to the assumption...
AbstractIt is noteworthy that the possibility of computing Kalman-Bucy estimates depends entirely on...
AbstractIt is noteworthy that the possibility of computing Kalman-Bucy estimates depends entirely on...
In the Thesis we study the problem of linear filtration of Gaussian signals in finite-dimensional sp...
In the Thesis we study the problem of linear filtration of Gaussian signals in finite-dimensional sp...
AbstractA filtering of Kalman–Bucy type is derived for a signal governed by a linear retarded stocha...
Representing the solutions of partial differential equations by integrals over function space has be...
The purpose of this work is to analyse the effect of various perturbations and projections of Kalman...
In standard treatments of stochastic filtering one first has to estimate the parameters of the model...
The purpose of this work is to analyse the effect of various perturbations and projections of Kalman...
In this paper we will set up the Hida theory of generalized Wiener functionals using *(d), the space...
For Q the variance of some centred Gaussian random vector in a separable Banach space it is shown th...
AbstractThe problem of optimal linear estimation for continuous time processes is investigated. The ...
AbstractA stochastic integral with respect to a generalized, i.e., not necessarily time-homogeneous,...
This thesis is on filtering in state space models. First, we examine approximate Kalman filters for ...
AbstractThe Wiener-Hopf equations of the Kalman-Bucy estimate can be solved, owing to the assumption...
AbstractIt is noteworthy that the possibility of computing Kalman-Bucy estimates depends entirely on...
AbstractIt is noteworthy that the possibility of computing Kalman-Bucy estimates depends entirely on...
In the Thesis we study the problem of linear filtration of Gaussian signals in finite-dimensional sp...
In the Thesis we study the problem of linear filtration of Gaussian signals in finite-dimensional sp...
AbstractA filtering of Kalman–Bucy type is derived for a signal governed by a linear retarded stocha...
Representing the solutions of partial differential equations by integrals over function space has be...
The purpose of this work is to analyse the effect of various perturbations and projections of Kalman...
In standard treatments of stochastic filtering one first has to estimate the parameters of the model...
The purpose of this work is to analyse the effect of various perturbations and projections of Kalman...
In this paper we will set up the Hida theory of generalized Wiener functionals using *(d), the space...
For Q the variance of some centred Gaussian random vector in a separable Banach space it is shown th...
AbstractThe problem of optimal linear estimation for continuous time processes is investigated. The ...
AbstractA stochastic integral with respect to a generalized, i.e., not necessarily time-homogeneous,...
This thesis is on filtering in state space models. First, we examine approximate Kalman filters for ...