Interval-Passing Algorithm for Chemical Mixture Estimation

Ludovic Danjean (1, 2) , Bane Vasic (2) , Michael Marcellin (2) , David Declercq (3)

1 ETIS - UMR 8051 - Equipes Traitement de l'Information et Systèmes
2 ECE - Department of Electrical and Computer Engineering [Tucson]
3 ICI

In this letter we propose a compressive sensing scheme for the mixture estimation problem in spectroscopy. We show that by applying an appropriate measurement matrix on the chemical mixture spectrum, we obtain an overall measurement matrix which is sparse. This enables the use of a low-complexity iterative reconstruction algorithm, called the interval-passing algorithm, to estimate the concentration of each chemical present in the mixture. Simulation results for the proportion of correct reconstructions show that chemical mixtures with a large number of chemicals present can be recovered.

Domaines: Théorie de l'information [cs.IT]; Théorie de l'information et codage [math.IT]

Ludovic Danjean, Bane Vasic, Michael Marcellin, David Declercq. Interval-Passing Algorithm for Chemical Mixture Estimation. IEEE Signal Processing Letters, 2013, 20 (9), pp.849--852. ⟨10.1109/LSP.2013.2267656⟩. ⟨hal-00865690⟩