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Parameter Estimation of Multivariate ARMA Processes Using Cumulants
Yujiro INOUYE Toyohiro UMEDA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1994/05/25
Print ISSN: 0916-8508
Type of Manuscript: INVITED PAPER (Special Section on Signal Processing and System Theory)
parameter estimation, non-Gaussian processes, higher-order statistics, cumulants, identification,
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This paper addresses the problem of estimating the parameters of multivariate ARMA processes by using higher-order statistics called cumulants. The main objective in this paper is to extend the idea of the q-slice algorithm in univariate ARMA processes to multivariate ARMA processes. It is shown for a multivariate ARMA process that the MA coefficient matrices can be estimated up to postmultiplication of a permutation matrix by using the third-order cumulants and of an extended permutation matrix by using the fourth-order cumulants. Simulation examples are included to demonstrate the effectiveness of the proposed method.