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An algorithm for multichannel autoregressive moving average (ARMA) modeling which uses scalar computations only and is well suited for parallel implementation is proposed. The given ARMA process is converted to an equivalent scalar, periodic ARMA process. The scalar autoregressive (AR) parameters are estimated by first deriving a set of modified Yule-Walker-type equations and then solving them by a parallel, order recursive algorithm. The moving average (MA) parameters are estimated by a least squares method from the estimates of the input samples obtained via a high-order, periodic AR approximation of the scalar process
Published in:
Signal Processing, IEEE Transactions on
(Volume:41
,
Issue:
4
)
Date of Publication: Apr 1993
- Page(s):
- 1692 - 1697
- ISSN :
- 1053-587X
- INSPEC Accession Number:
- 4449599
- Digital Object Identifier :
- 10.1109/78.212746
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Apr 1993
- Sponsored by :
- IEEE Signal Processing Society
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