Unbiased FIR system identification in the presence of input and output interference

Author

So, H.C.

Author_Institution

Dept. of Electron. Eng., City Univ. of Hong Kong, Kowloon, China

Volume

2

fYear

1999

fDate

1999

Firstpage

696

Abstract

In the presence of input interference, the Wiener solution for impulse response estimation is biased. In this paper, it is proved that bias removal can be achieved by proper scaling of the optimal filter coefficients and a modified least mean squares algorithm is then developed for accurate system identification in noise. Simulation results are included to compare the impulse response estimation performances of the proposed method and two total least squares based adaptive algorithms under different interference conditions

Keywords

FIR filters; filtering theory; identification; interference (signal); least mean squares methods; noise; Wiener solution; filter coefficient scaling; impulse response estimation performance; input interference; interference conditions; modified LMS algorithm; modified least mean squares algorithm; noise; optimal filter coefficients; output interference; unbiased FIR system identification; Adaptive algorithm; Additive noise; Finite impulse response filter; Interference; Least mean square algorithms; Least squares approximation; Least squares methods; Noise measurement; System identification; Wiener filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1999. 42nd Midwest Symposium on

Conference_Location

Las Cruces, NM

Print_ISBN

0-7803-5491-5

Type

conf

DOI

10.1109/MWSCAS.1999.867733

Filename

867733