DSpace
 

EPrints@IIT Delhi >
Faculty Research Publicatons  >
Electrical Engineering >

Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1783

Full metadata record

DC FieldValueLanguage
dc.contributor.authorChakraborty, M-
dc.contributor.authorPrasad, S-
dc.date.accessioned2006-06-27T09:14:03Z-
dc.date.available2006-06-27T09:14:03Z-
dc.date.issued1993-
dc.identifier.citationSignal Processing, IEEE Transactions on, 41(4), 1692 - 1697p.en
dc.identifier.urihttp://eprint.iitd.ac.in/dspace/handle/2074/1783-
dc.description.abstractAn 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 processen
dc.format.extent78207 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.subjectmultichannel autoregressiveen
dc.subjectperiodic ARMA processen
dc.subjectscalar autoregressive (AR) parametersen
dc.subjectmoving average (MA) parametersen
dc.titleMultivariate ARMA modeling by scalar algorithmsen
dc.typeArticleen
Appears in Collections:Electrical Engineering

Files in This Item:

File Description SizeFormat
chakrabortymul1993.pdf76.37 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback