Abstract
In order to improve the overall performance of the normalized least-mean-square (NLMS) algorithm, there is the need to control its main parameters, i.e., the normalized step-size and regularization terms. In this context, the variable step-size and variable regularized versions of the NLMS algorithm are designed to address the conflicting requirement of fast convergence and low mis adjustment. In this paper, we propose an optimized NLMS algorithm for acoustic echo cancellation (AEC). This algorithm is based on a joint-optimization on both the normalized step-size and regularization parameters, in the context of a state variable model (similar to Kalman filtering). The simulation results indicate that the proposed algorithm can be a reliable choice for AEC applications, since it achieves fast convergence and tracking, low mis adjustment, and double-talk robustness.
Recommended Citation
S. Ciochina et al., "An Optimized NLMS Algorithm for Acoustic Echo Cancellation," ISSCS 2015 - International Symposium on Signals, Circuits and Systems, article no. 7203971, Institute of Electrical and Electronics Engineers, Aug 2015.
The definitive version is available at https://doi.org/10.1109/ISSCS.2015.7203971
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-146737487-3
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
14 Aug 2015
