Title :
Real time algorithm for nonlinear filtering problem
Author :
Yau, Stephen S T ; Shing-Tung Yau
Author_Institution :
MSCS, Univ. of Illinois, Chicago, IL, USA
Abstract :
The fundamental problem of nonlinear filtering theory is how to solve robust D-M-Z equation in real time and in memoryless manner. This paper describes a new real time algorithm which reduces the nonlinear filtering problem to off-line computations. Our algorithm gives convergent solutions in both pointwise sense and L2 in case that the drift term and observation dynamic term have linear growths. The algorithm presented is slightly better than that given in our previous paper (2000)
Keywords :
convergence; filtering theory; nonlinear filters; probability; real-time systems; D-M-Z equation; drift term; nonlinear filtering; observation dynamic term; pointwise convergence; probability density; real time algorithm; signal observation model; Algebra; Differential equations; Filtering algorithms; Filtering theory; Maximum likelihood detection; Military computing; Nonlinear equations; Nonlinear filters; Real time systems; Robustness;
Conference_Titel :
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-7061-9
DOI :
10.1109/.2001.980569
