DocumentCode
2385809
Title
Least mean-squared error polynomial estimation in systems with uncertain observations
Author
Caballero-Aguila, R. ; Hermoso-Carazo, A. ; Linares-Perez, J.
Author_Institution
Dept. Estadistica e I.O., Univ. de Jaen
fYear
2000
fDate
2000
Firstpage
110
Abstract
We consider a kind of discrete-time linear systems with uncertain observations, in which the additive noise of the state and observation equations are correlated with each other. By using the orthogonal projection theorem, a recursive algorithm to obtain the least mean-squared error polynomial estimator for the state of these systems is proposed
Keywords
discrete time systems; least mean squares methods; linear systems; noise; observers; parameter estimation; polynomials; recursive estimation; signal processing; additive noise; discrete-time linear systems; least mean-squared error polynomial estimation; observation equations; orthogonal projection theorem; recursive algorithm; state estimation; Additive noise; Communication systems; Equations; Estimation error; Estimation theory; Kalman filters; Linear systems; Polynomials; State estimation; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2000. Proceedings. IEEE International Symposium on
Conference_Location
Sorrento
Print_ISBN
0-7803-5857-0
Type
conf
DOI
10.1109/ISIT.2000.866400
Filename
866400
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