This paper considers the fixed-interval smoothing for jump Markov systems. An optimal backward-time recursive equation for computing the joint posterior of the state vector and model index is established first. A suboptimal algorithm is then developed to approximate the new Bayesian smoother under nonlinear state-space models with additive Gaussian noise. The proposed method utilizes the well-known assumed density filtering with Gaussian assumption and the expression for the quotient of two Gaussian densities to compute the smoothing posterior. It eliminates the need for finding the inverse of the state dynamics and can handle singular process noise covariance, compared with several existing multiple model smoothers. Promising results are o...
© Copyright 2005 IEEEIn this article we compute the exact smoothing algorithm for discrete-time Gaus...
International audienceWe address the statistical filtering problem in dynamical models with jumps. W...
International audienceWe address the statistical filtering problem in dynamical models with jumps. W...
International audienceA suboptimal algorithm to fixed-interval smoothing for nonlinear Markovian swi...
This paper considers the problem of fixed-interval smoothing for Markovian switching systems with m...
Pré-print, dernière versionInternational audienceA suboptimal algorithm to fixed-interval and fixed-...
In this article we compute new state and mode estimation algorithms for discrete-time Gauss--Markov ...
International audienceFixed-interval Bayesian smoothing in state-space systems has been addressed fo...
International audienceFixed-interval Bayesian smoothing in state-space systems has been addressed fo...
International audienceFixed-interval Bayesian smoothing in state-space systems has been addressed fo...
International audienceFixed-interval Bayesian smoothing in state-space systems has been addressed fo...
International audienceIn this note we revisit fixed-interval Kalman like smoothing algorithms. We ha...
We consider the smoothing problem of estimating a sequence of state vectors given a nonlinear state ...
We consider the smoothing problem of estimating a sequence of state vectors given a nonlinear state ...
Abstract Two-filter smoothing is a principled approach for performing optimal smoothing in non-linea...
© Copyright 2005 IEEEIn this article we compute the exact smoothing algorithm for discrete-time Gaus...
International audienceWe address the statistical filtering problem in dynamical models with jumps. W...
International audienceWe address the statistical filtering problem in dynamical models with jumps. W...
International audienceA suboptimal algorithm to fixed-interval smoothing for nonlinear Markovian swi...
This paper considers the problem of fixed-interval smoothing for Markovian switching systems with m...
Pré-print, dernière versionInternational audienceA suboptimal algorithm to fixed-interval and fixed-...
In this article we compute new state and mode estimation algorithms for discrete-time Gauss--Markov ...
International audienceFixed-interval Bayesian smoothing in state-space systems has been addressed fo...
International audienceFixed-interval Bayesian smoothing in state-space systems has been addressed fo...
International audienceFixed-interval Bayesian smoothing in state-space systems has been addressed fo...
International audienceFixed-interval Bayesian smoothing in state-space systems has been addressed fo...
International audienceIn this note we revisit fixed-interval Kalman like smoothing algorithms. We ha...
We consider the smoothing problem of estimating a sequence of state vectors given a nonlinear state ...
We consider the smoothing problem of estimating a sequence of state vectors given a nonlinear state ...
Abstract Two-filter smoothing is a principled approach for performing optimal smoothing in non-linea...
© Copyright 2005 IEEEIn this article we compute the exact smoothing algorithm for discrete-time Gaus...
International audienceWe address the statistical filtering problem in dynamical models with jumps. W...
International audienceWe address the statistical filtering problem in dynamical models with jumps. W...