Abstract
Acoustic echo cancellation represents one of the most challenging system identification problems. The most used adaptive filter in this application is the popular normalized least mean square (NLMS) algorithm, which has to address the classical compromise between fast convergence/tracking and low misadjustment. In order to meet these conflicting requirements, the step-size of this algorithm needs to be controlled. Inspired by the pioneering work of Prof. E. Hänsler and his collaborators on this fundamental topic, we present in this paper several solutions to control the adaptation of the NLMS adaptive filter. The developed algorithms are “non-parametric” in nature, i.e., they do not require any additional features to control their behavior. Simulation results indicate the good performance of the proposed solutions and support the practical applicability of these algorithms.
Original language | English |
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Article number | 97 |
Journal | Eurasip Journal on Advances in Signal Processing |
Volume | 2015 |
Issue number | 1 |
Pages (from-to) | 1-19 |
Number of pages | 19 |
ISSN | 1687-6172 |
DOIs | |
Publication status | Published - 1 Dec 2015 |
Externally published | Yes |
Keywords
- Acoustic echo cancellation
- Adaptive filters
- Normalized least mean square (NLMS) algorithm
- Step-size control
- Variable regularized NLMS
- Variable step-size NLMS