DocumentCode
581852
Title
Decomposition based iterative estimation algorithm for autoregressive moving average models
Author
Hu, Huiyi ; Ding, Ruifeng
Author_Institution
Key Lab. of Adv. Process Control for Light Ind. (Minist. of Educ.), Jiangnan Univ., Wuxi, China
fYear
2012
fDate
25-27 July 2012
Firstpage
1932
Lastpage
1937
Abstract
This paper discusses an iterative least squares algorithm for identifying the parameters of autoregressive moving average models using the matrix decomposition technique. The basic idea is to use the block matrix inversion lemma to avoid repeatedly computing the inverse of the involved data matrix at each iteration. The simulation results show that the proposed algorithm works well.
Keywords
data handling; estimation theory; iterative methods; least squares approximations; matrix algebra; autoregressive moving average models; block matrix inversion lemma; data matrix; decomposition based iterative estimation algorithm; iterative least squares algorithm; matrix decomposition technique; ARMA model; Iterative method; Least squares; Parameter estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2012 31st Chinese
Conference_Location
Hefei
ISSN
1934-1768
Print_ISBN
978-1-4673-2581-3
Type
conf
Filename
6390241
Link To Document