Journal article icon

Journal article

Particle methods for change detection, system identification, and control

Abstract:
Particle methods are a set of powerful and versatile simulation-based methods to perform optimal state estimation in nonlinear non-Gaussian state-space models. The ability to compute the optimal filter is central to solving important problems in areas such as change detection, parameter estimation, and control. Much recent work has been done in these areas. The objective of this paper is to provide a detailed overview of them. © 2004 IEEE.
Publication status:
Published

Actions


Access Document


Publisher copy:
10.1109/JPROC.2003.823142

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Journal:
PROCEEDINGS OF THE IEEE
Volume:
92
Issue:
3
Pages:
423-438
Publication date:
2004-03-01
DOI:
ISSN:
0018-9219
Source identifiers:
190596
Language:
English
Keywords:
Pubs id:
pubs:190596
UUID:
uuid:3ad3d43e-dd97-4d8d-a66f-7b493e3d2466
Local pid:
pubs:190596
Deposit date:
2012-12-19

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP