An intelligence background-correction algorithm for highly fluorescent sample in Raman spectroscopy has been developed with peak detection and width estimation by CWT wavelet and background fitting by penalized least squares. The programming language is R(http://www.r-project.org/).
library(devtools);
httr::set_config( httr::config( ssl_verifypeer = 0L ) )
install_github("zmzhang/baselineWavelet")
Install the downloaded packages from local zip or tar.gz file.
To start running this algorithm, load the baselineWavelet package through "library(baselineWavelet)" in the R commandline windows, try "?baselineWavelet" in the R commandline windows to open the documents.
This is a correction example:
For any questions, please contact: Yi-Zeng Liang: yizeng_liang@263.net or: Zhi-Min Zhang: zhangzhimin.csu@gmail.com
Z.M. Zhang, S. Chen, Y.Z. Liang, et al., An intelligent background-correction algorithm for highly fluorescent samples in Raman spectroscopy. Journal of Raman Spectroscopy 41 (6), 659 (2010).
Download pdf and endnote citation here
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