DocumentCode :
1551618
Title :
Recursive scheme for ARMA coefficient and order estimation with noisy input-output data
Author :
Tan, H.-Z. ; Chow, T.W.S.
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong
Volume :
146
Issue :
2
fYear :
1999
fDate :
8/1/1999 12:00:00 AM
Firstpage :
65
Lastpage :
71
Abstract :
A novel estimation scheme for determining ARMA orders and coefficients is presented. The system is assumed to be excited by a non-Gaussian random sequence. Third-order cumulants of the input-output data are introduced to eliminate additive Gaussian noise of unknown variances at the measurement site. The proposed algorithm is performed order-recursively until the estimated coefficients converge where the defined norm of error squares (NES) nearly stays at a constant value. The system orders thereby need not be known a priori. Theoretical analyses together with experimental results indicate that the system orders can be accurately determined with the same procedures while the corresponding system coefficients are being estimated
Keywords :
Gaussian noise; autoregressive moving average processes; convergence of numerical methods; error analysis; higher order statistics; random processes; recursive estimation; signal processing; ARMA coefficient; ARMA orders; additive Gaussian noise elimination; autoregressive moving average; convergence; experimental results; measurement site; noisy input-output data; nonGaussian random sequence; norm of error squares; order estimation; recursive estimation; signal processing; stochastic linear system modelled; system coefficients; system orders; third-order cumulants;
fLanguage :
English
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
Publisher :
iet
ISSN :
1350-245X
Type :
jour
DOI :
10.1049/ip-vis:19990237
Filename :
788762
Link To Document :
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