Identification of multivariate FIR systems using higher-order statistics

Author

Tong, Lung

Author_Institution

Dept. of Electr. & Syst. Eng., Connecticut Univ., Storrs, CT, USA

Volume

5

fYear

1996

fDate

7-10 May 1996

Firstpage

3037

Abstract

The identification of multichannel moving average (MA) parameter matrices {H(k)} using fourth-order output cumulants is considered. By analysing the eigenstructures of the cumulant matrices, it is shown that the MA parameter matrices can be identified uniquely up to a post multiplication of monomial matrices if H(0) does not have columns that are pairwise colinear and H=[H^t(0),...,H^t(L)]^t has full column rank. The constructive proof of this condition leads to a closed-form identification algorithm

Keywords

FIR filters; MIMO systems; eigenvalues and eigenfunctions; filtering theory; higher order statistics; matrix algebra; moving average processes; parameter estimation; telecommunication channels; MA parameter matrices; MIMO MA process; blind system identification; cumulant matrices; eigenstructures; fourth-order output cumulants; full column rank matrix; higher-order statistics; monomial matrices; multichannel moving average parameter matrices; multivariate FIR system identification; pairwise colinear columns; post multiplication; Contracts; Equations; Erbium; Finite impulse response filter; Higher order statistics; Lungs; MIMO; Parameter estimation; Symmetric matrices; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1520-6149

Print_ISBN

0-7803-3192-3

Type

conf

DOI

10.1109/ICASSP.1996.550195

Filename

550195