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Found 8 papers, 6 papers with code
Semi-Blind Source Separation with Learned Constraints
BSS problems being ill-posed, the resolution requires efficient regularization schemes to better distinguish between the sources and yield interpretable solutions.
Unrolling PALM for sparse semi-blind source separation
Sparse Blind Source Separation (BSS) has become a well established tool for a wide range of applications - for instance, in astrophysics and remote sensing.
Joint deconvolution and unsupervised source separation for data on the sphere
This becomes highly challenging when applied to large data sampled on the sphere such as those provided by wide-field observations in astrophysics, whose analysis requires the design of dedicated robust and yet effective algorithms.
Recovery of 21 cm intensity maps with sparse component separation
21 cm intensity mapping has emerged as a promising technique to map the large-scale structure of the Universe.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics
A novel method for component separation of extended sources in X-ray astronomy
In high-energy astronomy, spectro-imaging instruments such as X-ray detectors allow investigation of the spatial and spectral properties of extended sources including galaxy clusters, galaxies, diffuse interstellar medium, supernova remnants and pulsar wind nebulae.
High Energy Astrophysical Phenomena Astrophysics of Galaxies Instrumentation and Methods for Astrophysics
Two-pixel polarimetric camera by compressive sensing
We propose an original concept of compressive sensing (CS) polarimetric imaging based on a digital micro-mirror (DMD) array and two single-pixel detectors.
NMF with Sparse Regularizations in Transformed Domains
In this article, we show how a sparse NMF algorithm coined non-negative generalized morphological component analysis (nGMCA) can be extended to impose non-negativity in the direct domain along with sparsity in a transformed domain, with both analysis and synthesis formulations.
Sparse and Non-Negative BSS for Noisy Data
In this context, it is fundamental that the sources to be estimated present some diversity in order to be efficiently retrieved.
