β-NMF AND SPARSITY PROMOTING REGULARIZATIONS FOR COMPLEX MIXTURE UNMIXING. APPLICATION TO 2D HSQC NMR
| Autor: | Afef Cherni, Sandrine Anthoine, Caroline Chaux |
|---|---|
| Přispěvatelé: | Institut de Mathématiques de Marseille (I2M), Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Cherni, Afef |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
[SPI] Engineering Sciences [physics]
Computer science sparsity 020206 networking & telecommunications majorization- minimization (MM) 02 engineering and technology Blind signal separation Nmr data Non-negative matrix factorization NMR spectra database [SPI]Engineering Sciences [physics] multiplicative algorithm Index Terms-BSS 0202 electrical engineering electronic engineering information engineering β-divergence 020201 artificial intelligence & image processing 2D NMR Biological system Terms-BSS Two-dimensional nuclear magnetic resonance spectroscopy [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing Heteronuclear single quantum coherence spectroscopy [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing |
| Zdroj: | 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020) 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2020), May 2020, Barcelone, Spain ICASSP |
| Popis: | International audience; In Nuclear Magnetic Resonance (NMR) spectroscopy, an efficient analysis and a relevant extraction of different molecule properties from a given chemical mixture are important tasks, especially when processing bidimensional NMR data. To that end, using a blind source separation approach based on a variational formulation seems to be a good strategy. However, the poor resolution of NMR spectra and their large dimension require a new and modern blind source separation method. In this work, we propose a new variational formulation for blind source separation (BSS) based on a β-divergence data fidelity term combined with sparsity promoting regularization functions. An application to 2D HSQC NMR experiments illustrates the interest and the effectiveness of the proposed method whether in simulated or real cases. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|