DocumentCode :
3116048
Title :
Subspace-Based Blind Identification of IIR Systems
Author :
Gómez, Juan C. ; Baeyens, Enrique
Author_Institution :
Lab. for Syst. Dynamics & Signal Process., Univ. Nac. de Rosario, Rosario
fYear :
2006
fDate :
6-8 Sept. 2006
Firstpage :
97
Lastpage :
102
Abstract :
A new subspace method for the blind identification of infinite impulse response (IIR), single input-multiple output (SIMO) systems represented using orthonormal bases with fixed poles, is presented in this paper. Basis coefficients are estimated in closed form, up to a scalar factor, by first computing the column space of the output Hankel matrix using singular value decomposition (SVD), and then solving a least squares problem also resorting to an SVD. The performance of the proposed algorithm is illustrated through a simulation example.
Keywords :
Hankel matrices; IIR filters; least mean squares methods; singular value decomposition; infinite impulse response; least squares problem; output Hankel matrix; single input-multiple output systems; singular value decomposition; subspace-based blind identification; Computational modeling; Digital communication; Finite impulse response filter; Least squares approximation; Matrix decomposition; Sensor arrays; Signal processing; Signal processing algorithms; Singular value decomposition; Stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on
Conference_Location :
Arlington, VA
ISSN :
1551-2541
Print_ISBN :
1-4244-0656-0
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2006.275529
Filename :
4053628
Link To Document :
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