Rohsa: regularized optimization for hyper-spectral analysis – application to phase separation of 21 cm data

HIGHLIGHTS

• who: Marchal Antoine and colleagues from the CEA, CNRS, Université Paris-Saclay, Université Paris Diderot, Sorbonne Paris Cité, Gif-sur-Yvette, France Laboratoire des Signaux et Systèmes (CNRS, CentraleSupélec, University of Paris-Sud), Université Paris-Saclay have published the paper: ROHSA: Regularized Optimization for Hyper-Spectral Analysis - Application to phase separation of 21 cm data, in the Journal: (JOURNAL)
• what: The aim of this work is to develop new algorithm to perform separation of diffuse sources in hyper-spectral data. The authors propose a new method to map out the contribution of each . . .
  

   

  

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