Self-Configuring System Identification via Evolutionary Frequency-Domain Adaptive Filters

Conference contribution


Publication Details

Author(s): Zeller M, Kellermann W
Publication year: 2010
Conference Proceedings Title: Int. Workshop on Acoustic Echo and Noise Control (IWAENC)
Language: English


Abstract

This paper proposes a novel strategy for adaptive frequencydomain filtering in arbitrary system identification tasks. Employing
a convex combination of two competing filters with different size,
the lengths of the components are dynamically adjusted, following a
performance-based soft decision. Thus, a doubly-adaptive, evolutionary
filter structure is realized that can find and track the optimum filter
length so as to automatically match the adaptive model size to that of
the unknown system. Regarding the proposed DFT-domain algorithm, a
focus is put on the various implications on coefficient updates and memory
organization for different choices of the length increment. Results for the
effectiveness of the estimation and identification are shown for noise and
speech signals and several systems in an AEC scenario.


FAU Authors / FAU Editors

Kellermann, Walter Prof. Dr.-Ing.
Professur für Nachrichtentechnik
Zeller, Marcus
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


How to cite

APA:
Zeller, M., & Kellermann, W. (2010). Self-Configuring System Identification via Evolutionary Frequency-Domain Adaptive Filters. In Int. Workshop on Acoustic Echo and Noise Control (IWAENC). Tel Aviv, IL.

MLA:
Zeller, Marcus, and Walter Kellermann. "Self-Configuring System Identification via Evolutionary Frequency-Domain Adaptive Filters." Proceedings of the Int. Workshop on Acoustic Echo and Noise Control (IWAENC), Tel Aviv 2010.

BibTeX: 

Last updated on 2019-08-05 at 16:08