Mixture models for two-dimensional baseline correction, applied to artifact elimination in time-resolved spectroscopy
type: Dataset
description: Baseline correction and artifact removal are important pre-processing steps in analytical chemistry. We propose a correction algorithm using a mixture model in combination with penalized regression. The model is an extension of a method recently introduced for baseline estimation in the case of one-dimensional data. The data are modeled as a smooth surface using tensor product P-splines. The weights of the P-splines regression model are computed from a mixture model where a datapoint is either allocated to the noise around the baseline, or to the artifact component. The method is broadly applicable for anisotropic smoothing of two-way data such as two-dimensional gel electrophoresis and two-dimensional chromatography data. We focus here on the application of the approach in femtosecond time-resolved spectroscopy, to eliminate strong artifact signals from the solvent.
issued: 2026-05-11T17:20:27.911074
language: en
modified: 2026-05-11T17:20:27.911078
contact point: Organization
  fn: CCSD
keyword: baseline-estimation
keyword: chimtheochemical-sciencestheoretical-andor-physical-chemistry
keyword: infoeu-reposemanticsarticle
keyword: journal-articles
keyword: mixture-model
keyword: p-splines
keyword: tensor-product
keyword: time-resolved-spectroscopy
keyword: two-dimensional-data
landing page: 0003-2670

Mixture models for two-dimensional baseline correction, applied to artifact elimination in time-resolved spectroscopy
type: Distribution
format: HTML
issued: 2026-05-11T17:20:27.926484
modified: 2026-05-11T17:20:27.896002
access URL: https://hal.science/hal-00807353

test_moissonnage_selune
type: Agent