Sparse normalized subband adaptive filter algorithm with l0-norm constraint
Authors:
- Yi YuYYYi Yu
- Haiquan ZhaoHZHaiquan Zhao
- Badong ChenBCBadong Chen
- 1 December 2016
- journal article
- Published by Elsevier in Journal of the Franklin Institute
- Vol. 353 (18) , 5121-5136
Abstract
No abstract availableFunding Information
- National Science Foundation of PR China (61571374, 61433011)
- 973 Program (2015CB351703)
This publication has 31 references indexed in Scilit:
- Reweighted l1-norm penalized LMS for sparse channel estimation and its analysisSignal Processing, 2014
- Subband Adaptive Filtering with-Norm Constraint for Sparse System IdentificationMathematical Problems in Engineering, 2013
- Simplified p-norm-like constraint LMS algorithm for efficient estimation of underwater acoustic channelsJournal of Marine Science and Application, 2013
- Performance Analysis of $l_0$ Norm Constraint Least Mean Square AlgorithmIEEE Transactions on Signal Processing, 2012
- Sparsity regularised recursive least squares adaptive filteringIET Signal Processing, 2011
- A family of proportionate normalized subband adaptive filter algorithmsJournal of the Franklin Institute, 2011
- $l_{0}$ Norm Constraint LMS Algorithm for Sparse System IdentificationIEEE Signal Processing Letters, 2009
- Improving convergence of the NLMS algorithm using constrained subband updatesIEEE Signal Processing Letters, 2004
- Proportionate normalized least-mean-squares adaptation in echo cancelersIEEE Transactions on Speech and Audio Processing, 2000
- Advanced television systems for terrestrial broadcasting: Some problems and some proposed solutionsProceedings of the IEEE, 1995