| | |
| | |
Stat |
Members: 3667 Articles: 2'599'751 Articles rated: 2609
18 February 2025 |
|
| | | |
|
Article overview
| |
|
PENDANTSS: PEnalized Norm-ratios Disentangling Additive Noise, Trend and Sparse Spikes | Paul Zheng
; Emilie Chouzenoux
; Laurent Duval
; | Date: |
4 Jan 2023 | Abstract: | Denoising, detrending, deconvolution: usual restoration tasks, traditionally
decoupled. Coupled formulations entail complex ill-posed inverse problems. We
propose PENDANTSS for joint trend removal and blind deconvolution of sparse
peak-like signals. It blends a parsimonious prior with the hypothesis that
smooth trend and noise can somewhat be separated by low-pass filtering. We
combine the generalized quasi-norm ratio SOOT/SPOQ sparse penalties
$ell_p/ell_q$ with the BEADS ternary assisted source separation algorithm.
This results in a both convergent and efficient tool, with a novel Trust-Region
block alternating variable metric forward-backward approach. It outperforms
comparable methods, when applied to typically peaked analytical chemistry
signals. Reproducible code is provided. | Source: | arXiv, 2301.01514 | Services: | Forum | Review | PDF | Favorites |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
|
| |
|
|
|