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Open AccessArticle

Regularization Factor Selection Method for l1-Regularized RLS and Its Modification against Uncertainty in the Regularization Factor

by Junseok Lim 1,* and Seokjin Lee 2
1
Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, Gwangjin-gu, Seoul 05006, Korea
2
School of Electronics Engineering, College of IT Engineering, Kyungpook National University, Daegu 41566, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(1), 202; https://doi.org/10.3390/app9010202
Received: 5 December 2018 / Revised: 31 December 2018 / Accepted: 4 January 2019 / Published: 8 January 2019
(This article belongs to the Special Issue Modelling, Simulation and Data Analysis in Acoustical Problems)
This paper presents a new l1-RLS method to estimate a sparse impulse response estimation. A new regularization factor calculation method is proposed for l1-RLS that requires no information of the true channel response in advance. In addition, we also derive a new model to compensate for uncertainty in the regularization factor. The results of the estimation for many different kinds of sparse impulse responses show that the proposed method without a priori channel information is comparable to the conventional method with a priori channel information. View Full-Text
Keywords: l1-regularized RLS; sparsity; room impulse response; total least squares; regularization factor l1-regularized RLS; sparsity; room impulse response; total least squares; regularization factor
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Lim, J.; Lee, S. Regularization Factor Selection Method for l1-Regularized RLS and Its Modification against Uncertainty in the Regularization Factor. Appl. Sci. 2019, 9, 202.

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