DocumentCode :
2171273
Title :
Proportionate affine projection sign algorithms for sparse system identification in impulsive interference
Author :
Yang, Zengli ; Zheng, Yahong Rosa ; Grant, Steven L.
Author_Institution :
Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO, USA
fYear :
2011
fDate :
22-27 May 2011
Firstpage :
4068
Lastpage :
4071
Abstract :
Two proportionate affine projection sign algorithms (APSAs) are proposed for system identification applications, such as network echo cancellation (NEC), where the impulse response is often real-valued with sparse coefficients and long filter length. The proposed proportionate-type algorithms can achieve fast convergence and low steady-state misalignment by adopting a proportionate regularization matrix to the APSA. Benefiting from the characteristic of Zi-norm algorithms, affine projection, and proportionate matrix, the new algorithms are robust to impulsive interferences and colored input, and achieve much faster convergence rate in sparse impulse responses than the original APSA, the normalized sign algorithm (NSA), and the proportionate least mean square (PNLMS) algorithm. The computational complexity of the new algorithms is lower than the affine projection algorithm (APA) family due to elimination of matrix inversion.
Keywords :
adaptive filters; interference suppression; least mean squares methods; matrix inversion; minimisation; transient response; APSA; affine projection sign algorithms; impulsive interference; matrix inversion; minimisation; normalized sign algorithm; proportionate least mean square algorithm; proportionate regularization matrix; proportionate-type algorithms; sparse impulse responses; sparse system identification; Convergence; Echo cancellers; Interference; Robustness; Signal processing algorithms; Sparse matrices; Speech; Adaptive filter; affine projection algorithm; network echo cancellation (NEC); proportionate adaptive algorithm; sign algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague
ISSN :
1520-6149
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2011.5947246
Filename :
5947246
Link To Document :
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