AbstractEver since the technique of the Kalman–Bucy filter was popularized, there has been an intense interest in finding new classes of finite-dimensional recursive filters. In the late 1970s the concept of the estimation algebra of a filtering system was introduced. Brockett, Clark, and Mitter proposed to use the Wei–Norman approach to solve the nonlinear filtering problem. In 1990, Tam, Wong, and Yau presented a rigorous proof of the Brocket–Mitter program which allows one to construct finite-dimensional recursive filters from finite–dimensional estimation algebras. Later Yau wrote down explicitly a system of ordinary differential equations and generalized Kolmogorov equation to which the robust Duncan–Mortenser– Zakai equation can be re...
In this paper we prove that, under suitable regularity assumptions, a necessary condition for the ex...
In this note we present a computationally simple algorithm for non-linear filtering. The algorithm i...
The discrete-time filtering problem can be seen as a dynamic generalization of the classical Bayesia...
AbstractEver since the technique of the Kalman–Bucy filter was popularized, there has been an intens...
In this paper, the filtering problem for the general time-invariant nonlinear state-observation syst...
Abstract — In the paper, we introduce a kind of method to solve the nonlinear filtering problem. Fir...
In this paper we consider the continuous--time nonlinear filtering problem, which has an infinite--d...
Abstract—It is well known that the nonlinear filtering problem has important applications in both mi...
The linear generalized Kalman Bucy filter problem is studied. An observed process is a sum of a us...
http://deepblue.lib.umich.edu/bitstream/2027.42/6973/5/bbl3526.0001.001.pdfhttp://deepblue.lib.umich...
In principle, general approaches to optimal nonlinear filtering can be described in a unified way fr...
AbstractIn the early 1990s, Yau developed a new class of nonlinear filters, called the Yau Filterswh...
A new architecture to model and design nonlinear transfer functions is presented using a new formula...
Bibliography: p. 19-20.Caption title. "October 2, 1978."Supported in part by the DoD Joint Services ...
In this paper, we first introduce a novel sub-class of recursive linear-in-the-parameters nonlinear ...
In this paper we prove that, under suitable regularity assumptions, a necessary condition for the ex...
In this note we present a computationally simple algorithm for non-linear filtering. The algorithm i...
The discrete-time filtering problem can be seen as a dynamic generalization of the classical Bayesia...
AbstractEver since the technique of the Kalman–Bucy filter was popularized, there has been an intens...
In this paper, the filtering problem for the general time-invariant nonlinear state-observation syst...
Abstract — In the paper, we introduce a kind of method to solve the nonlinear filtering problem. Fir...
In this paper we consider the continuous--time nonlinear filtering problem, which has an infinite--d...
Abstract—It is well known that the nonlinear filtering problem has important applications in both mi...
The linear generalized Kalman Bucy filter problem is studied. An observed process is a sum of a us...
http://deepblue.lib.umich.edu/bitstream/2027.42/6973/5/bbl3526.0001.001.pdfhttp://deepblue.lib.umich...
In principle, general approaches to optimal nonlinear filtering can be described in a unified way fr...
AbstractIn the early 1990s, Yau developed a new class of nonlinear filters, called the Yau Filterswh...
A new architecture to model and design nonlinear transfer functions is presented using a new formula...
Bibliography: p. 19-20.Caption title. "October 2, 1978."Supported in part by the DoD Joint Services ...
In this paper, we first introduce a novel sub-class of recursive linear-in-the-parameters nonlinear ...
In this paper we prove that, under suitable regularity assumptions, a necessary condition for the ex...
In this note we present a computationally simple algorithm for non-linear filtering. The algorithm i...
The discrete-time filtering problem can be seen as a dynamic generalization of the classical Bayesia...