Cherni Afef

Cherni Afef
Aix-Marseille Université | AMU · Centre de Mathématiques et Informatique

PhD

About

12
Publications
434
Reads
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60
Citations
Additional affiliations
October 2018 - present
Aix-Marseille Université
Position
  • PhD
Education
October 2015 - October 2018
University of Strasbourg, Alsace, France
Field of study
  • Signal processing
September 2014 - June 2015
Paris Descartes University, Paris, France
Field of study
  • Mathematics and Computer science
September 2011 - June 2014
National Engineering School of Tunis, Tunisia
Field of study
  • Telecommunicatons

Publications

Publications (12)
Preprint
Full-text available
Nuclear Magnetic Resonance (NMR) spectroscopy is an efficient technique to analyze chemical mixtures in which one acquires spectra of the chemical mixtures along one ore more dimensions. One of the important issues is to efficiently analyze the composition of the mixture, this is a classical Blind Source Separation (BSS) problem. The poor resolutio...
Preprint
Full-text available
Underdetermined or ill-posed inverse problems require additional information for sound solutions with tractable optimization algorithms. Sparsity yields consequent heuristics to that matter, with numerous applications in signal restoration, image recovery, or machine learning. Since the $\ell_0$ count measure is barely tractable, many statistical o...
Article
Underdetermined or ill-posed inverse problems require additional information for sound solutions with tractable optimization algorithms. Sparsity yields consequent heuristics to that matter, with numerous applications in signal restoration, image recovery, or machine learning. Since the $\ell _0$ count measure is barely tractable, many statistica...
Conference Paper
In NMR spectroscopy, the analysis and the distinction of different chemical entities in a given mixture based on blind source separation techniques is an actual objective that is considered in this work. Precision and relevance are highly required in this area. Consequently,the developpement of new and modern blind source separation approaches is n...
Poster
In this work, we are interested in unmixing complex mix-tures based on Nuclear Magnetic Resonance spectroscopy spectra. Moreprecisely, we propose to solve a 2D blind source separation problemwhere signals (spectra) are highly sparse. The separation is formulatedas a nonnegative matrix factorization problem that is solved using ablock coordinate pro...
Preprint
Mass Spectrometry (MS) is a largely used analytical technique in biology with applications such as the determination of molecule masses or the elucidation of structural data. Fourier Transform Ion Cyclotron Resonance MS is one implementation of the technique allowing high resolution and mass accuracy and based on trapping ions in circular orbits th...
Article
Analytical methods for mixtures of small molecules requires specificity (is a certain molecule present in the mix?) and speciation capabilities. NMR has been a tool of choice for both of these issues since its early days, due to its quantitative (linear) response, sufficiently high resolving power and capabilities of inferring molecular structures...
Thesis
Cette thèse s’intéresse à la création de nouvelles approches algorithmiques pour la résolution du problème inverse en biophysiques. Dans un premier temps, on vise l’application RMN de type DOSY: une nouvelle approche de régularisation hybride a été proposée avec un nouvel algorithme PALMA (http://palma.labo.igbmc.fr/). Cet algorithme permet d’analy...
Conference Paper
Mass spectrometry (MS) is a fundamental technology of analytical chemistry for measuring the structure of molecules, with many application fields such as clinical biomarker analysis or pharmacokinetics. In the context of proteomic analysis with MS, the superposition of the isotopic patterns of different proteins, in various charge-states produces M...
Article
NMR is a tool of choice for the measure of diffusion coefficients of species in solution. The DOSY experiment, a 2D implementation of this measure, has proven to be particularly useful for the study of complex mixtures, molecular interactions, polymers, etc. However, DOSY data analysis requires to resort to inverse Laplace transform, in particular...
Conference Paper
Inverse problems arising from Laplace transform inversion are ill-posed, and require suitable regularization strategies. Although the maximum entropy regularization approach usually appears as an adequate strategy due to its ability to recover regular positive valued signals, it was observed to lead to poor reconstruction results when the sought si...

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