Particle methods for change detection, system identification, and control

C Andrieu; A Doucet; SS Singh; VB Tadic

doi:10.1109/JPROC.2003.823142

Particle methods for change detection, system identification, and control

C Andrieu, A Doucet, SS Singh, VB Tadic

Research output: Contribution to journal › Article (Academic Journal) › peer-review

255 Citations (Scopus)

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.

Translated title of the contribution	Particle methods for change detection, system identification, and control
Original language	English
Pages (from-to)	423 - 438
Number of pages	16
Journal	Proceedings of the IEEE
Volume	92 (3)
DOIs	https://doi.org/10.1109/JPROC.2003.823142
Publication status	Published - Mar 2004

Bibliographical note

Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Other identifier: IDS number 800CA

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10.1109/JPROC.2003.823142

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@article{9a9348ecca2b47aaa8c63d225f4ebd3d,

title = "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.",

author = "C Andrieu and A Doucet and SS Singh and VB Tadic",

note = "Publisher: IEEE-Inst Electrical Electronics Engineers Inc Other identifier: IDS number 800CA",

year = "2004",

month = mar,

doi = "10.1109/JPROC.2003.823142",

language = "English",

volume = "92 (3)",

pages = "423 -- 438",

journal = "Proceedings of the IEEE",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

}

TY - JOUR

T1 - Particle methods for change detection, system identification, and control

AU - Andrieu, C

AU - Doucet, A

AU - Singh, SS

AU - Tadic, VB

N1 - Publisher: IEEE-Inst Electrical Electronics Engineers Inc Other identifier: IDS number 800CA

PY - 2004/3

Y1 - 2004/3

N2 - 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.

AB - 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.

U2 - 10.1109/JPROC.2003.823142

DO - 10.1109/JPROC.2003.823142

M3 - Article (Academic Journal)

VL - 92 (3)

SP - 423

EP - 438

JO - Proceedings of the IEEE

JF - Proceedings of the IEEE

ER -

Particle methods for change detection, system identification, and control

Abstract

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