Abstract
In this paper, based on asymmetric least squares smoothing, a new algorithm for multiple spectra baseline correction is proposed. By means of the similarity among the multiple spectra, the algorithm estimates the baselines by penalizing the differences in the baseline corrected signals, which makes the algorithm possible to eliminate scatter effects on the spectra. In addition, a relaxation factor which measures the similarity of the baseline corrected spectra is incorporated into the optimization model and an alternate iteration strategy is used to solve the optimization problem. The proposed algorithm is fast and can output multiple baselines simultaneously. Experimental results on both simulated data and real data demonstrate the effectiveness and efficiency of the algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
