DocumentCode
567442
Title
Particle flow and Monge-Kantorovich transport
Author
Daum, Fred ; Huang, Jim
Author_Institution
Raytheon, Woburn, MA, USA
fYear
2012
fDate
9-12 July 2012
Firstpage
135
Lastpage
142
Abstract
We compare our new particle flow nonlinear filter algorithms with Monge-Kantorovich optimal transport (MKT) algorithms. These two classes of algorithms are the same in several ways, but they differ in computational complexity and the overall intended purpose, as well as differing in several crucial details of the computation and the problem. Moreover, the deep mathematical theory of incompressible particle flow that was developed recently by Shnirelman can be used to provide insight into why our particle flow algorithms work so well.
Keywords
computational complexity; nonlinear filters; particle filtering (numerical methods); MKT algorithms; Monge-Kantorovich transport algorithm; computational complexity; deep mathematical theory; incompressible particle flow; particle flow nonlinear filter algorithms; Approximation algorithms; Approximation methods; Computational complexity; Equations; Nonlinear filters; Particle filters; Standards; Monge-Kantorovich optimal transport; extended Kalman filter; nonlinear filter; particle filter; particle flow; transport problem;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion (FUSION), 2012 15th International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4673-0417-7
Electronic_ISBN
978-0-9824438-4-2
Type
conf
Filename
6289797
Link To Document