Related papers: Blind Signal Separation Methods for the Identifica…
It is a recurrent issue in astronomical data analysis that observations are unevenly sampled or incomplete maps with missing patches or intentionaly masked parts. In addition, many astrophysical emissions are non stationary processes over…
This paper presents and discusses the application of blind source separation to astrophysical data obtained with the WMAP satellite. Blind separation permits to identify and isolate a component compatible with CMB emission, and to measure…
NMR spectral datasets, especially in systems with limited samples, can be difficult to interpret if they contain multiple chemical components (phases, polymorphs, molecules, crystals, glasses, etc...) and the possibility of overlapping…
In the interstellar medium, the cosmic elemental carbon abundance includes the total carbon in both gas and solid phases. The aim of the study was to trial a new method for measuring the amount and distribution of aliphatic carbon within…
Fast Independent Component Analysis (FastICA) is a component separation algorithm based on the levels of non-Gaussianity. Here we apply the FastICA to the component separation problem of the microwave background including carbon monoxide…
The mid-infrared is an optimal window to trace stellar mass in nearby galaxies and the 3.6$\mu m$ IRAC band has been exploited to this effect, but such mass estimates can be biased by dust emission. We present our pipeline to reveal the old…
The mid-infrared emission from 18 nearby galaxies imaged with the IRAC instrument on Spitzer Space Telescope samples the spatial distributions of the reddening-free stellar photospheric emission and the warm dust in the ISM. These two…
Independent Component Analysis (ICA) has recently been shown to be a promising new path in data analysis and de-trending of exoplanetary time series signals. Such approaches do not require or assume any prior or auxiliary knowledge on the…
AIMS: One of the most challenging and important problem of digital signal processing in Cosmology is the separation of foreground contamination from cosmic microwave background (CMB). This problem becomes even more difficult in situations,…
We review issues and methods for diffuse component separation in the context of Cosmic Microwave Background observations. The revised version contains a paragraph on FastICA and its application to CMB component separation, which was missing…
The study of the interstellar medium (ISM) in the X-rays has entered a golden age with the advent of the X-ray observatories XMM-Newton and Chandra. High-energy resolution allowed to study dust spectroscopic features with unprecedented…
We present a new, fast, algorithm for the separation of astrophysical components superposed in maps of the sky, based on the fast Independent Component Analysis technique (FastICA). It allows to recover both the spatial pattern and the…
[Abridged] An increasing number of astronomical instruments (on Earth and space-based) provide hyperspectral images, that is three-dimensional data cubes with two spatial dimensions and one spectral dimension. The intrinsic limitation in…
In this work we study the relevance of the component separation technique based on the Independent Component Analysis (ICA) and investigate its performance in the context of a limited sky coverage observation and from the viewpoint of our…
A blind source separation method is described to extract sources from data mixtures where the underlying sources are assumed to be sparse and uncorrelated. The approach used is to detect and analyse segments of time where one source exists…
We generalize the technique of Lada et al. (1994) to map dust column density through a molecular cloud (NICE) to an optimized multi-band technique (NICER) that can be applied to any multi-band survey of molecular clouds. We present a first…
To date, the search for radio technosignatures has focused on sky location as a primary discriminant between technosignature candidates and anthropogenic radio frequency interference (RFI). In this work, we investigate the possibility of…
The spectral region around 10 micrometer, showing prominent dust emission bands, is commonly used to derive the chemical composition of protoplanetary dust. Different analysis methods have been proposed for this purpose, but so far, no…
Independent component analysis (ICA) is a blind source separation method to recover source signals of interest from their mixtures. Most existing ICA procedures assume independent sampling. Second-order-statistics-based source separation…
Independent Component Analysis (ICA) is a statistical method often used to decompose a complex dataset in its independent sub-parts. It is a powerful technique to solve a typical Blind Source Separation problem. A fast calculation of the…