A robust baseline elimination method based on community information
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @Article{Wu:2015:DSP,
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author = "Yanling Wu and Qingwei Gao and Yuanyuan Zhang2",
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title = "A robust baseline elimination method based on
community information",
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journal = "Digital Signal Processing",
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year = "2015",
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ISSN = "1051-2004",
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DOI = "doi:10.1016/j.dsp.2015.02.015",
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URL = "http://www.sciencedirect.com/science/article/pii/S105120041500072X",
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abstract = "Baseline correction is an important pre-processing
technique used to separate true spectra from
interference effects or remove baseline effects. In
this paper, an adaptive iteratively reweighted genetic
programming based on excellent community information
(GPEXI) is proposed to model baselines from spectra.
Excellent community information which is abstracted
from the present excellent community includes an
automatic common threshold, normal global and local
slope information. Significant peaks can be firstly
detected by an automatic common threshold. Then based
on the characteristic that a baseline varies slowly
with respect to wavelength, normal global and local
slope information are used to further confirm whether a
point is in peak regions. Moreover the slope
information is also used to determine the range of
baseline curve fluctuation in peak regions. The
proposed algorithm is more robust for different kinds
of baselines and its curvature and slope can be
automatically adjusted without prior knowledge.
Experimental results in both simulated data and real
data demonstrate the effectiveness of the algorithm.",
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keywords = "genetic algorithms, genetic programming, Baseline
correction, Robust estimation, Community information",
- }
Genetic Programming entries for
Yanling Wu
Qingwei Gao
Yuanyuan Zhang2
Citations