DocumentCode :
2676431
Title :
Nonlinear acoustic system identification using a combination of Volterra and power filters
Author :
Contan, Cristian ; Topa, Marina ; Kirei, Botond ; Homana, Ioana
Author_Institution :
Fac. of Electron., Tech. Univ. of Cluj-Napoca, Cluj-Napoca, Romania
fYear :
2011
fDate :
June 30 2011-July 1 2011
Firstpage :
1
Lastpage :
4
Abstract :
The paper proposes a nonlinear system identification method that uses a combination of adaptive linear, Volterra and power filters. Adaptation of the kernels is made using a Normalized Least Mean Square algorithm. The method is applied in echo cancellation, where several sources of nonlinearities exist: the overdriven amplifier, the small loudspeaker at high volume, the room with different absorbent walls. Functions with nonlinear characteristics are chosen to model these distortions. The evaluation is made in terms of Echo Return Loss Enhancement. Results show that the overall convex combination approach performs better or at least as well as the best single adaptive filter.
Keywords :
adaptive filters; echo suppression; least mean squares methods; nonlinear filters; nonlinear systems; power filters; Volterra filter; adaptive linear filter; convex combination approach; echo cancellation; echo return loss enhancement; nonlinear acoustic system identification; normalized least mean square algorithm; overdriven amplifier; power filter; Acoustics; Adaptation models; Adaptive filters; Maximum likelihood detection; Nonlinear filters; Nonlinear systems; Power filters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Circuits and Systems (ISSCS), 2011 10th International Symposium on
Conference_Location :
lasi
Print_ISBN :
978-1-61284-944-7
Type :
conf
DOI :
10.1109/ISSCS.2011.5978752
Filename :
5978752
Link To Document :
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