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

Title: Multivariate ARMA modeling by scalar algorithms
Authors: Chakraborty, M
Prasad, S
Keywords: multichannel autoregressive
periodic ARMA process
scalar autoregressive (AR) parameters
moving average (MA) parameters
Issue Date: 1993
Citation: Signal Processing, IEEE Transactions on, 41(4), 1692 - 1697p.
Abstract: 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
URI: http://eprint.iitd.ac.in/dspace/handle/2074/1783
Appears in Collections:Electrical Engineering

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