Regularization factor selection method for l1-regularized RLS and its modification against uncertainty in the regularization factor

Junseok Lim; Seokjin Lee

doi:10.3390/app9010202

Regularization factor selection method for l₁-regularized RLS and its modification against uncertainty in the regularization factor

Junseok Lim, Seokjin Lee

School of Electronics Engineering

Sejong University

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

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.

Original language	English
Article number	202
Journal	Applied Sciences (Switzerland)
Volume	9
Issue number	1
DOIs	https://doi.org/10.3390/app9010202
State	Published - 8 Jan 2019

Keywords

L-regularized RLS
Regularization factor
Room impulse response
Sparsity
Total least squares

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10.3390/app9010202

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title = "Regularization factor selection method for l1-regularized RLS and its modification against uncertainty in the regularization factor",

abstract = "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.",

keywords = "L-regularized RLS, Regularization factor, Room impulse response, Sparsity, Total least squares",

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AU - Lee, Seokjin

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N2 - 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.

AB - 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.

KW - L-regularized RLS

KW - Regularization factor

KW - Room impulse response

KW - Sparsity

KW - Total least squares

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ER -

Regularization factor selection method for l₁-regularized RLS and its modification against uncertainty in the regularization factor

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Keywords

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