Parameter Estimation of Multivariate ARMA Processes Using Cumulants

Yujiro INOUYE  Toyohiro UMEDA  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E77-A   No.5   pp.748-759
Publication Date: 1994/05/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: INVITED PAPER (Special Section on Signal Processing and System Theory)
Category: 
Keyword: 
parameter estimation,  non-Gaussian processes,  higher-order statistics,  cumulants,  identification,  

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Summary: 
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.