ICASSP 2017accepted0 citations
Sparsity-assisted signal smoothing (revisited)
Abstract
This paper proposes an improved formulation of sparsity-assisted signal smoothing (SASS). The purpose of SASS is to filter/denoise a signal that has jump discontinuities in its derivative (of some designated order) but is otherwise smooth. SASS unifies conventional low-pass filtering and total variation denoising. The SASS algorithm depends on the formulation, in terms of banded Toeplitz matrices, of a zero-phase recursive discrete-time filter as applied to finite-length data. The improved formulation presented in this paper avoids the unwanted end-point transient artifacts which sometimes occur in the original version. For illustration, SASS is applied to ECG signal denoising.
BibTeX
@inproceedings{icassp2017_sparsityassisted,
title = {Sparsity-assisted signal smoothing (revisited)},
author = {Ivan W. Selesnick},
booktitle = {ICASSP 2017},
year = {2017}
}