Proportionate NSAF algorithms with sparseness-measured for acoustic echo cancellation
Authors:
- Yi YuYYYi Yu
- Haiquan ZhaoHZHaiquan Zhao
- 1 May 2017
- journal article
- Published by Elsevier in AEU - International Journal of Electronics and Communications
- Vol. 75, 53-62
Abstract
No abstract availableFunding Information
- National Science Foundation of P.R. China (61271340, 61571374, 61433011)
- China Scholarship Council
This publication has 33 references indexed in Scilit:
- Sparse normalized subband adaptive filter algorithm with l0-norm constraintJournal of the Franklin Institute, 2016
- Norm-adaption penalized least mean square/fourth algorithm for sparse channel estimationSignal Processing, 2016
- Zero‐attracting variable‐step‐size least mean square algorithms for adaptive sparse channel estimationInternational Journal of Adaptive Control and Signal Processing, 2015
- A fast convergence normalized least‐mean‐square type algorithm for adaptive filteringInternational Journal of Adaptive Control and Signal Processing, 2013
- An Enhanced IAF-PNLMS Adaptive Algorithm for Sparse Impulse Response IdentificationIEEE Transactions on Signal Processing, 2012
- A PNLMS Algorithm With Individual Activation FactorsIEEE Transactions on Signal Processing, 2009
- An Efficient Proportionate Affine Projection Algorithm for Echo CancellationIEEE Signal Processing Letters, 2009
- A Class of Sparseness-Controlled Algorithms for Echo CancellationIEEE Transactions on Audio, Speech, and Language Processing, 2009
- Improving convergence of the PNLMS algorithm for sparse impulse response identificationIEEE Signal Processing Letters, 2005
- Proportionate normalized least-mean-squares adaptation in echo cancelersIEEE Transactions on Speech and Audio Processing, 2000