Joint Decomposition of Multichannel Signals with Multimarginal Optimal Transport
The joint decomposition of a sequence of signals is addressed, where each signal is coded within a predefined dictionary. We propose a convex variational formulation involving a regularization term based on optimal transport. The latter is designed so as to promote proximity between neighboring channels. Two kinds of regularization criteria are designed, corresponding to distinct cross-channel information on the transport of dictionary atoms from one channel to another. The resulting optimization problems are reformulated as quadratic programs and solved using a proximal algorithm. The proposed approach is analyzed for a multichannel deconvolution problem.
Authors
- Charles Soussen (ORCID: https://orcid.org/0000-0002-6837-6755)
- Jérôme Idier (ORCID: https://orcid.org/0000-0003-4087-0302)
- Xiangyi Li (ORCID: https://orcid.org/0000-0003-3080-0108)
- Jean Malléjac
Institutions
- École Centrale de Nantes (FR)
- Centre National de la Recherche Scientifique (FR)
- CentraleSupélec (FR)
- Laboratoire des Sciences du Numérique de Nantes (FR)
- Institut Fresnel (FR)
- Centrale Méditerranée (FR)
- Nantes Université (FR)
Publication Details
- Published
- 2024-08-26
- DOI
- https://doi.org/10.23919/eusipco63174.2024.10715143
- Primary Topic
- Blind Source Separation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00