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4S Peak Filling - baseline estimation by iterative mean suppression.

Liland KH - MethodsX (2015)

Bottom Line: A novel baseline estimation procedure building on previously published works is presented. •The core of the estimation is an iterative spectrum suppression consisting of a moving window minimum replacement (adapted from Friedrichs [1]).•Four, easily understandable, parameters control placement of the baseline relative to the noise band around the signal (adapted from Eilers [2]) and the flexibility in different situations.•The method is especially suited for non-linear baselines with local variations and for resolving peak clusters in qualitative analyses.

View Article: PubMed Central - PubMed

Affiliation: Norwegian University of Life Sciences, 1430 Ås, Norway ; Nofima - Norwegian Institute of Food, Fisheries and Aquaculture Research, 1432 Ås, Norway.

ABSTRACT
A novel baseline estimation procedure building on previously published works is presented. •The core of the estimation is an iterative spectrum suppression consisting of a moving window minimum replacement (adapted from Friedrichs [1]).•Four, easily understandable, parameters control placement of the baseline relative to the noise band around the signal (adapted from Eilers [2]) and the flexibility in different situations.•The method is especially suited for non-linear baselines with local variations and for resolving peak clusters in qualitative analyses.

No MeSH data available.


Related in: MedlinePlus

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4S Peak Filling - baseline estimation by iterative mean suppression.

Liland KH - MethodsX (2015)

© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4487348&req=5

Bottom Line: A novel baseline estimation procedure building on previously published works is presented. •The core of the estimation is an iterative spectrum suppression consisting of a moving window minimum replacement (adapted from Friedrichs [1]).•Four, easily understandable, parameters control placement of the baseline relative to the noise band around the signal (adapted from Eilers [2]) and the flexibility in different situations.•The method is especially suited for non-linear baselines with local variations and for resolving peak clusters in qualitative analyses.

View Article: PubMed Central - PubMed

Affiliation: Norwegian University of Life Sciences, 1430 Ås, Norway ; Nofima - Norwegian Institute of Food, Fisheries and Aquaculture Research, 1432 Ås, Norway.

ABSTRACT
A novel baseline estimation procedure building on previously published works is presented. •The core of the estimation is an iterative spectrum suppression consisting of a moving window minimum replacement (adapted from Friedrichs [1]).•Four, easily understandable, parameters control placement of the baseline relative to the noise band around the signal (adapted from Eilers [2]) and the flexibility in different situations.•The method is especially suited for non-linear baselines with local variations and for resolving peak clusters in qualitative analyses.

No MeSH data available.


Related in: MedlinePlus