baselineWavelet: Intelligent background-correction algorithm for highly...

Description Details Author(s) References

Description

an intelligent background-correction algorithm is developed, which simulates manual background-correction procedure of an expert intelligently. It basically consists of works of three aspects: 1) the accurate peak position detection of Raman spectrum by continuous wavelet transform (CWT) with the Mexican Hat wavelet as the mother wavelet; 2) peak widths estimation by enhanced signal-to-noise ratio (SNR) derivative calculation based on CWT but with the Haar wavelet as the mother wavelet; and 3) background fitting using penalized least squares with binary masks.

What's new in newer version:
1: from version 2.0 to 3.0: Rewirte the WhittakerSmooth function, don't use the cholskey decomposition any more.
2: from version 1.0 - 2.0: Two functions, say baselineCorrectionCWT() and WhittakerSmoother(), in the baselineWavelet package were modified (add a parameter) so that one could easily perform first, second or even higher differences penalties by adjusting the parameter for the purpose.

Details

Package: baselineWavelet
Type: Package
Version: 3.0.0
Date: 2009-09-03
License: GPL (>= 2)

The package can be used to not only an intelligent and valid tool for background correction in Raman spectroscopy, but also a useful tool in other spectral signals and chromatogram.

Author(s)

yizeng liang<yizeng_liang@263.net>, zhimin zhang <zhangzhimin.csu@gmail.com>

References

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zmzhang/baselineWavelet documentation built on Dec. 26, 2019, 8:49 a.m.