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Reduced order Kalman filtering without model reduction

Author
SIMON, D1
[1] Department of Electrical Engineering, Cleveland State University, 2121 Euclid Avenue, SH 332, Cleveland, OH 44115-2214, United States
Source

Control and intelligent systems. 2007, Vol 35, Num 2, pp 169-174, 6 p ; ref : 24 ref

ISSN
1480-1752
Scientific domain
Control theory, operational research; Computer science
Publisher
Acta Press, Anaheim, CA / Acta Press, Calgary, AB / Acta Press, Zürich
Publication country
United States
Document type
Article
Language
English
Author keyword
Kalman filter order reduction state estimation
Keyword (fr)
Combinaison linéaire Covariance Erreur estimation Estimation erreur Estimation état Filtre Kalman Identification système Modélisation Système ordre réduit Temps discret Temps minimal
Keyword (en)
Linear combination Covariance Estimation error Error estimation State estimation Kalman filter System identification Modeling Reduced order systems Discrete time Minimum time
Keyword (es)
Combinación lineal Covariancia Error estimación Estimación error Estimación estado Filtro Kalman Identificación sistema Modelización Tiempo discreto Tiempo mínimo
Classification
Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C02 Learning and adaptive systems

Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02D Control theory. Systems / 001D02D05 Modelling and identification

Discipline
Computer science : theoretical automation and systems
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
18819527

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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