DocumentCode :
2469459
Title :
Blind system identification using model based matching method
Author :
Kaufhold, B. ; Kirlin, R.L. ; Dizaji, R.M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada
fYear :
1998
fDate :
14-16 Sep 1998
Firstpage :
300
Lastpage :
303
Abstract :
A method for the blind identification of a set of spatially varying transfer functions is described. The techniques proposed herein are based on model matching of Fourier coefficient sensitivity vectors of the channel transfer function, which can be nonlinear in the unknown parameters, with a set of eigenvectors obtained from data deviation covariance matrices. The salient difference between this technique and the usual channel subspace methods is that no FIR structure for the individual transfer functions is assumed. Instead we assume that the frequency response as a function of the parameters is known which is often the case in wave transmission problems
Keywords :
Fourier analysis; covariance matrices; eigenvalues and eigenfunctions; frequency response; parameter estimation; signal processing; transfer function matrices; Fourier coefficient sensitivity vectors; blind system identification; channel transfer function; data deviation covariance matrices; eigenvectors; frequency response; model based matching method; signal processing; spatially varying transfer functions; wave transmission problems; Covariance matrix; Finite impulse response filter; Frequency response; Parameter estimation; Signal processing; Statistics; System identification; Time frequency analysis; Transfer functions; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Statistical Signal and Array Processing, 1998. Proceedings., Ninth IEEE SP Workshop on
Conference_Location :
Portland, OR
Print_ISBN :
0-7803-5010-3
Type :
conf
DOI :
10.1109/SSAP.1998.739394
Filename :
739394
Link To Document :
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