Sources of uncertainty in gas chromatography and high-performance liquid chromatography, Journal of Chromatography A, vol.849, issue.1, pp.13-33, 1999. ,
DOI : 10.1016/S0021-9673(99)00537-3
An iterative algorithm for linear inverse problems with compound regularizers, 2008 15th IEEE International Conference on Image Processing, pp.685-688, 2008. ,
DOI : 10.1109/ICIP.2008.4711847
New background correction method for liquid chromatography with diode array detection, infrared spectroscopic detection and Raman spectroscopic detection, Journal of Chromatography A, vol.1057, issue.1-2, pp.21-30, 2004. ,
DOI : 10.1016/j.chroma.2004.09.035
Proximal Algorithms for Multicomponent Image Recovery Problems, Journal of Mathematical Imaging and Vision, vol.30, issue.1-2, pp.3-22, 2011. ,
DOI : 10.1007/s10851-010-0243-1
Derivative Preprocessing and Optimal Corrections for Baseline Drift in Multivariate Calibration, Applied Spectroscopy, vol.54, issue.7, pp.1055-1068, 2000. ,
DOI : 10.1366/0003702001950571
Comprehensive Chemometrics: Chemical and Biochemical Data Analysis, 2009. ,
Wavelet-Based Method for Noise Characterization and Rejection in High-Performance Liquid Chromatography Coupled to Mass Spectrometry, Analytical Chemistry, vol.80, issue.13, pp.4960-4968, 2008. ,
DOI : 10.1021/ac800166w
The digital TV filter and nonlinear denoising, IEEE Transactions on Image Processing, vol.10, issue.2, pp.231-241, 2001. ,
DOI : 10.1109/83.902288
Application of Wavelet Transform in Processing Chromatographic Data, Wavelets in Chemistry, pp.205-223, 2000. ,
DOI : 10.1016/S0922-3487(00)80034-9
Atomic Decomposition by Basis Pursuit, SIAM Journal on Scientific Computing, vol.20, issue.1, pp.33-61, 1998. ,
DOI : 10.1137/S1064827596304010
Matched filtering with background suppression for improved quality of base peak chromatograms and mass spectra in liquid chromatography???mass spectrometry, Analytica Chimica Acta, vol.454, issue.2, pp.167-184, 2002. ,
DOI : 10.1016/S0003-2670(01)01574-4
Mixture models for baseline estimation, Chemometrics and Intelligent Laboratory Systems, vol.117, pp.56-60, 2012. ,
DOI : 10.1016/j.chemolab.2011.11.001
A Perfect Smoother, Analytical Chemistry, vol.75, issue.14, pp.3631-3836, 2003. ,
DOI : 10.1021/ac034173t
Unimodal smoothing, Journal of Chemometrics, vol.13, issue.5-7, pp.317-328, 2005. ,
DOI : 10.1002/cem.935
Simultaneous cartoon and texture image inpainting using morphological component analysis (MCA), Applied and Computational Harmonic Analysis, vol.19, issue.3, pp.340-358, 2005. ,
DOI : 10.1016/j.acha.2005.03.005
Image Decomposition and Separation Using Sparse Representations: An Overview, Proc. IEEE, pp.98983-994, 2010. ,
DOI : 10.1109/JPROC.2009.2024776
URL : https://hal.archives-ouvertes.fr/hal-00808047
Majorization–Minimization Algorithms for Wavelet-Based Image Restoration, IEEE Transactions on Image Processing, vol.16, issue.12, pp.2980-2991, 2007. ,
DOI : 10.1109/TIP.2007.909318
Background estimation in experimental spectra, Physical Review E, vol.61, issue.2, pp.1152-1160, 2000. ,
DOI : 10.1103/PhysRevE.61.1152
An objective comparison of pre-processing methods for enhancement of liquid chromatography???mass spectrometry data, Journal of Chromatography A, vol.1172, issue.2, pp.1172135-150, 2007. ,
DOI : 10.1016/j.chroma.2007.09.077
Baseline correction by improved iterative polynomial fitting with automatic threshold, Chemometrics and Intelligent Laboratory Systems, vol.82, issue.1-2, pp.59-65, 2006. ,
DOI : 10.1016/j.chemolab.2005.08.009
Sparse decomposition over multi-component redundant dictionaries, IEEE 6th Workshop on Multimedia Signal Processing, 2004., pp.494-497, 2004. ,
DOI : 10.1109/MMSP.2004.1436603
Bayesian model selection and parameter estimation of nuclear emission spectra using RJMCMC, Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol.497, issue.2-3, pp.492-510, 2003. ,
DOI : 10.1016/S0168-9002(02)01807-7
A background elimination method based on wavelet transform for Raman spectra, Chemometrics and Intelligent Laboratory Systems, vol.85, issue.1, pp.94-101, 2007. ,
DOI : 10.1016/j.chemolab.2006.05.004
A Tutorial on MM Algorithms, The American Statistician, vol.58, issue.1, pp.30-37, 2004. ,
DOI : 10.1198/0003130042836
Algorithm for fitting XRF, SEM and PIXE X-ray spectra backgrounds [27] L. Komsta. Comparison of several methods of chromatographic baseline removal with a new approach based on quantile regression, Nucl. Instrum. Methods Phys. Res. Sect. B Chromatographia, vol.109, issue.73, pp.201-213721, 1996. ,
Geometric separation by single-pass alternating thresholding, Applied and Computational Harmonic Analysis, vol.36, issue.1, pp.23-50, 2014. ,
DOI : 10.1016/j.acha.2013.02.001
Optimal peak area determination in the presence of noise, Analytica Chimica Acta, vol.176, pp.77-104, 1985. ,
DOI : 10.1016/S0003-2670(00)81636-0
Optimization Transfer Using Surrogate Objective Functions, Journal of Computational and Graphical Statistics, vol.68, issue.1, pp.1-20, 2000. ,
DOI : 10.1080/10618600.2000.10474858
Intelligent background correction using an adaptive lifting wavelet, Chemometrics and Intelligent Laboratory Systems, vol.125, pp.11-17, 2013. ,
DOI : 10.1016/j.chemolab.2013.03.010
Baseline spectrum estimation using half-quadratic minimization, Proc. Eur. Sig. Image Proc. Conf, pp.305-308, 2004. ,
Background removal from spectra by designing and minimising a non-quadratic cost function, Chemometrics and Intelligent Laboratory Systems, vol.76, issue.2, pp.121-133, 2005. ,
DOI : 10.1016/j.chemolab.2004.10.003
Compendium of Chemical Terminology, 2009. ,
The effect of different baseline estimators on the limit of quantification in chromatography, Journal of Chemometrics, vol.11, issue.1, pp.1-11, 1997. ,
DOI : 10.1002/(SICI)1099-128X(199701)11:1<1::AID-CEM429>3.0.CO;2-V
Median filtering for removal of low-frequency background drift, Analytical Chemistry, vol.65, issue.2, pp.188-191, 1993. ,
DOI : 10.1021/ac00050a018
ECG Enhancement and QRS Detection Based on Sparse Derivatives, Biomedical Signal Processing and Control, vol.8, issue.6, pp.713-723, 2013. ,
DOI : 10.1016/j.bspc.2013.06.005
A general baseline-recognition and baseline-flattening algorithm, Journal of Magnetic Resonance (1969), vol.27, issue.2, pp.265-272, 1977. ,
DOI : 10.1016/0022-2364(77)90076-2
Numerical recipes: The Art of Scientific Computing, 2007. ,
A tutorial on the Lasso approach to sparse modeling, Chemometrics and Intelligent Laboratory Systems, vol.119, pp.21-31, 2012. ,
DOI : 10.1016/j.chemolab.2012.10.003
Baseline subtraction using robust local regression estimation, Journal of Quantitative Spectroscopy and Radiative Transfer, vol.68, issue.2, pp.179-193, 2001. ,
DOI : 10.1016/S0022-4073(00)00021-2
Investigation of Selected Baseline Removal Techniques as Candidates for Automated Implementation, Applied Spectroscopy, vol.59, issue.5, pp.545-574, 2005. ,
DOI : 10.1366/0003702053945985
Resonance-based signal decomposition: A new sparsity-enabled signal analysis method, Signal Processing, vol.91, issue.12, pp.2793-2809, 2011. ,
DOI : 10.1016/j.sigpro.2010.10.018
URL : http://taco.poly.edu/selesi/pubs/Resonance_Decomposition.pdf
Polynomial Smoothing of Time Series With Additive Step Discontinuities, IEEE Transactions on Signal Processing, vol.60, issue.12, pp.6305-6318, 2012. ,
DOI : 10.1109/TSP.2012.2214219
Simultaneous Low-Pass Filtering and Total Variation Denoising, IEEE Transactions on Signal Processing, vol.62, issue.5, pp.1109-1124, 2014. ,
DOI : 10.1109/TSP.2014.2298836
URL : http://otg.downstate.edu/Publication/SelesnickTSP14.pdf
Specification and estimation of noisy analytical signals, Chemometrics and Intelligent Laboratory Systems, vol.8, issue.1, pp.15-27, 1990. ,
DOI : 10.1016/0169-7439(90)80037-7
Specification and estimation of noisy analytical signals, Chemometrics and Intelligent Laboratory Systems, vol.8, issue.1, pp.29-41, 1990. ,
DOI : 10.1016/0169-7439(90)80038-8
Noise and Detection Limits in Signal-Integrating Analytical Methods ,
DOI : 10.1021/bk-1988-0361.ch007
Image decomposition via the combination of sparse representations and a variational approach, IEEE Transactions on Image Processing, vol.14, issue.10, pp.1570-1582, 2005. ,
DOI : 10.1109/TIP.2005.852206
Regression shrinkage and selection via the Lasso, J. Roy. Statist. Soc. Ser. B, vol.58, issue.1, pp.267-288, 1996. ,
DOI : 10.1111/j.1467-9868.2011.00771.x
Comparison of conventional gas chromatography and comprehensive two-dimensional gas chromatography for the detailed analysis of petrochemical samples, Journal of Chromatography A, vol.1056, issue.1-2, pp.155-162, 2004. ,
DOI : 10.1016/j.chroma.2004.05.071
URL : https://hal.archives-ouvertes.fr/hal-01330592
Comprehensive Two-Dimensional Gas Chromatography for Detailed Characterisation of Petroleum Products, Oil & Gas Science and Technology - Revue de l'IFP, vol.62, issue.1, pp.43-55, 2007. ,
DOI : 10.2516/ogst:2007004
URL : https://hal.archives-ouvertes.fr/hal-00617264
The Study of Discontinuous Phenomena, Ann. Phys, vol.362, pp.541-567, 1918. ,
Characterisation of middle-distillates by comprehensive two-dimensional gas chromatography (GC??GC): A powerful alternative for performing various standard analysis of middle-distillates, Journal of Chromatography A, vol.1086, issue.1-2, pp.21-28, 2005. ,
DOI : 10.1016/j.chroma.2005.05.106
URL : https://hal.archives-ouvertes.fr/hal-01330596
Signal Processing in Analytical Chemistry, Encyclopedia of Analytical Chemistry, 2000. ,
DOI : 10.1002/9780470027318.a5207
The elimination of errors due to baseline drift in the measurement of peak areas in gas chromatography, Journal of Chromatography A, vol.19, pp.486-494, 1965. ,
DOI : 10.1016/S0021-9673(01)99489-0
Baseline correction using adaptive iteratively reweighted penalized least squares, The Analyst, vol.10, issue.5, pp.1138-1146, 2010. ,
DOI : 10.1002/jrs.2500