Skip to main navigation Skip to search Skip to main content

Comparison of baseline estimation algorithms for chromatographic signals

  • Silesian University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Citations (Scopus)

Abstract

Baseline in signals is a relatively complicated problem in analysis of signals obtained in various analytical techniques such as chromatography and spectroscopy. In this article there are presented results of tests on four algorithms for a baseline estimation in chromatographic signals. Two of them are based on a polynomial fitting in a region of detected peaks. Another two algorithms, i.e. assymetric least squares method and iterative polynomial fitting with the automatic treshold, estimate the baseline under the whole signal and generally does not require peak detection. The tests of the algorithms are performed on both simulated and experimental signals.

Original languageEnglish
Title of host publication2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages925-930
Number of pages6
ISBN (Electronic)9781479987016
DOIs
Publication statusPublished - 29 Sept 2015
Event20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015 - Miedzyzdroje, Poland
Duration: 24 Aug 2015 → 27 Aug 2015

Publication series

Name2015 20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015

Conference

Conference20th International Conference on Methods and Models in Automation and Robotics, MMAR 2015
Country/TerritoryPoland
CityMiedzyzdroje
Period24/08/15 → 27/08/15

Keywords

  • baseline removal
  • chromatographic signal

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Comparison of baseline estimation algorithms for chromatographic signals'. Together they form a unique fingerprint.

Cite this