Faculty of Science, School of Statistics & Actuarial Science, MSC DissertationThis thesis follows a direction of research that deals with the theoretical foundations of stochastic differential equations on manifolds and a geometric analysis of the fundamental equations in nonlinear filtering theory. We examine the importance of modern differential geometry in developing an invariant theory of stochastic processes on manifolds, which allow us to extend current filtering techniques to an important class of manifolds. Furthermore, these tools provide us with greater insight to the infinite-dimensional nonlinear filtering problem. In particular, we apply our geometric analysis to the so called unnormalized conditional density approach expo...
In this dissertation, we investigate various problems in the analysis of stochastic (partial) differ...
This monograph, now in a thoroughly revised second edition, develops the theory of stochastic calcul...
: We present a new and systematic method of approximating exact nonlinear filters with finite dimens...
AbstractA general procedure, inspired from that used for deterministic partial differential equation...
We are interested in a nonlinear filtering problem motivated by an information-based approach for mo...
International audienceA general procedure, inspired from that used for deterministic partial differe...
This thesis studies different aspects of the linear and the nonlinear stochastic filtering problem. ...
AbstractIn the present paper on high dimensional nonlinear filtering problems and stochastic partial...
In this paper we study a nonlinear filtering problem for a general Markovian partially observed syst...
Filtering and identification problems of partially observable stochastic dynamical systems has been ...
The geometry which is the topic of this book is that determined by a map of one space N onto another...
Some stochastic filtering problems are formulated and solved where the observations are described by...
In this paper, we investigate a nonlinear ¯ltering problem with correlated noises, bounded coe±cient...
This paper is concerned with numerical approximations for a class of nonlinear stochastic partial di...
AbstractThis paper develops the stochastic calculus of variations for Hilbert space-valued solutions...
In this dissertation, we investigate various problems in the analysis of stochastic (partial) differ...
This monograph, now in a thoroughly revised second edition, develops the theory of stochastic calcul...
: We present a new and systematic method of approximating exact nonlinear filters with finite dimens...
AbstractA general procedure, inspired from that used for deterministic partial differential equation...
We are interested in a nonlinear filtering problem motivated by an information-based approach for mo...
International audienceA general procedure, inspired from that used for deterministic partial differe...
This thesis studies different aspects of the linear and the nonlinear stochastic filtering problem. ...
AbstractIn the present paper on high dimensional nonlinear filtering problems and stochastic partial...
In this paper we study a nonlinear filtering problem for a general Markovian partially observed syst...
Filtering and identification problems of partially observable stochastic dynamical systems has been ...
The geometry which is the topic of this book is that determined by a map of one space N onto another...
Some stochastic filtering problems are formulated and solved where the observations are described by...
In this paper, we investigate a nonlinear ¯ltering problem with correlated noises, bounded coe±cient...
This paper is concerned with numerical approximations for a class of nonlinear stochastic partial di...
AbstractThis paper develops the stochastic calculus of variations for Hilbert space-valued solutions...
In this dissertation, we investigate various problems in the analysis of stochastic (partial) differ...
This monograph, now in a thoroughly revised second edition, develops the theory of stochastic calcul...
: We present a new and systematic method of approximating exact nonlinear filters with finite dimens...