Add to ORKGWe consider a generalization of the Gauss-Hermite filter (GHF), where the filter density is represented by a Hermite expansion with leading Gaussian term. Thus the usual GHF is included as a special case. The moment equations for the time update are solved stepwise by Gauss-Hermite integration, and the measurement update is com-puted by the Bayes formula, again using numerical integration. Key Words: Stochastic differential equations; Nonlinear systems; Discrete measurements; Continuous-discrete state space model; Gaus
A finite-dimensional approximation to general discrete-time nonlinear filtering problems is provided...
We consider the filtering problem for a partially observable stochastic process , solution to a nonl...
In order to improve estimation accuracy of nonliear system with linear measurement model, simplifed ...
We consider a generalization of the Gauss-Hermite filter (GHF), where the filter density is represen...
The generalized Gauss-Hermite-filter (GGHF) is implemented in the multivariate case. We utilize a He...
Stochastic differential equations, Nonlinear systems, Discrete measurements, Maximum likelihood esti...
In this paper, a new version of the quadrature Kalman filter (QKF) is developed theoretically and te...
A finite-dimensional approximation to general discrete-time non linear filtering problems is provide...
In this paper, we propose a progressive Bayesian procedure, where the measurement information is con...
We propose an analytic moment-based filter for nonlinear stochastic dynamic systems modeled by Gauss...
This dissertation considers the state estimation problems with symmetric Gaussian/asymmetric skew-Ga...
We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochasti...
© 2003 Society for Industrial and Applied MathematicsIn this paper we present two methods for comput...
The stochastic filtering problem deals with the estimation of the posterior distribution of the curr...
In this paper we develop and analyze real-time and accurate filters for nonlinear filtering problems...
A finite-dimensional approximation to general discrete-time nonlinear filtering problems is provided...
We consider the filtering problem for a partially observable stochastic process , solution to a nonl...
In order to improve estimation accuracy of nonliear system with linear measurement model, simplifed ...
We consider a generalization of the Gauss-Hermite filter (GHF), where the filter density is represen...
The generalized Gauss-Hermite-filter (GGHF) is implemented in the multivariate case. We utilize a He...
Stochastic differential equations, Nonlinear systems, Discrete measurements, Maximum likelihood esti...
In this paper, a new version of the quadrature Kalman filter (QKF) is developed theoretically and te...
A finite-dimensional approximation to general discrete-time non linear filtering problems is provide...
In this paper, we propose a progressive Bayesian procedure, where the measurement information is con...
We propose an analytic moment-based filter for nonlinear stochastic dynamic systems modeled by Gauss...
This dissertation considers the state estimation problems with symmetric Gaussian/asymmetric skew-Ga...
We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochasti...
© 2003 Society for Industrial and Applied MathematicsIn this paper we present two methods for comput...
The stochastic filtering problem deals with the estimation of the posterior distribution of the curr...
In this paper we develop and analyze real-time and accurate filters for nonlinear filtering problems...
A finite-dimensional approximation to general discrete-time nonlinear filtering problems is provided...
We consider the filtering problem for a partially observable stochastic process , solution to a nonl...
In order to improve estimation accuracy of nonliear system with linear measurement model, simplifed ...