Referenced Items are not available for this document.
Singular-value-decomposition (SVD)-based moving-average (MA) order determination of non-Gaussian processes using higher-order statistics is addressed. It is shown that the MA order determination of autoregressive moving-average (ARMA) models is equivalent to the rank determination of a certain error matrix, and a SVD approach is proposed. Its simplified form is applied to pure MA models. To improve the robustness of the order selection, a combination of the SVD and the product of diagonal entries (PODE) test is proposed. Some interesting applications of the two SVD approaches are presented, and simulations verify their performance
Published in:
Signal Processing, IEEE Transactions on
(Volume:41
,
Issue:
8
)
Date of Publication: Aug 1993
- Page(s):
- 2657 - 2664
- ISSN :
- 1053-587X
- INSPEC Accession Number:
- 4532820
- Digital Object Identifier :
- 10.1109/78.229896
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Aug 1993
- Sponsored by :
- IEEE Signal Processing Society
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