Particle methods for change detection, system identification, and control

C Andrieu, A Doucet, SS Singh, VB Tadic

Research output: Contribution to journalArticle (Academic Journal)peer-review

223 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 contributionParticle methods for change detection, system identification, and control
Original languageEnglish
Pages (from-to)423 - 438
Number of pages16
JournalProceedings of the IEEE
Volume92 (3)
DOIs
Publication statusPublished - Mar 2004

Bibliographical note

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

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