Related papers: A Modified ICA Approach for Signal Separation in C…
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…
The detection of primordial polarization $B$ modes of the Cosmic Microwave Background (CMB) requires exquisite control of Galactic foreground contamination. The Needlet Internal Linear Combination (NILC) method has proven effective in…
Independent component analysis (ICA) is a method for recovering statistically independent signals from observations of unknown linear combinations of the sources. Some of the most accurate ICA decomposition methods require searching for the…
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…
Independent component analysis (ICA) is a fundamental data processing technique to decompose the captured signals into as independent as possible components. Computing the contrast function, which serves as a measure of independence of…
In recent years, there has been growing interest in jointly analyzing a foreground dataset, representing an experimental group, and a background dataset, representing a control group. The goal of such contrastive investigations is to…
Primordial B-mode detection is one of the main goals of current and future cosmic microwave background (CMB) experiments. However, the weak B-mode signal is overshadowed by several Galactic polarized emissions, such as thermal dust emission…
In this article we present a formalism to incorporate the partial-sky maps to the Gibbs ILC algorithm to estimate the joint posterior density of the Cosmic Microwave Background (CMB) signal and the theoretical CMB angular power spectrum…
Independent Component Analysis (ICA) is a technique for unsupervised exploration of multi-channel data that is widely used in observational sciences. In its classic form, ICA relies on modeling the data as linear mixtures of non-Gaussian…
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…
Independent component analysis (ICA) is a computational method for separating a multivariate signal into subcomponents assuming the mutual statistical independence of the non-Gaussian source signals. The classical Independent Components…
As Cosmic Microwave Background (CMB) measurements are becoming more ambitious, the issue of foreground contamination is becoming more pressing. This is especially true at the level of sensitivity, angular resolution and for the sky coverage…
The polarization modes of the cosmological microwave background are an invaluable source of information for cosmology, and a unique window to probe the energy scale of inflation. Extracting such information from microwave surveys requires…
Commercial cellular networks, like the systems based on DS-CDMA, face many types of interferences such as multi-user interference inside each sector in a cell to interoperate interference. Independent Component Analysis (ICA) has been used…
The detection of primordial gravitational waves in Cosmic Microwave Background B-mode polarization observations requires accurate and robust subtraction of astrophysical contamination. We show, using a blind Spectral Matching Independent…
Application of independent component analysis (ICA) as an unmixing and image clustering technique for high spatial resolution Raman maps is reported. A hyperspectral map of a fixed human cell was collected by a Raman micro spectrometer in a…
Cosmic birefringence, arising from a potential parity-violating interaction between cosmic microwave background (CMB) photons and evolving pseudo-scalar fields such as axion-like particles, can rotate the CMB polarization plane and induce…
We present a Bayesian parametric component separation method for polarised microwave sky maps. We solve jointly for the primary cosmic microwave background (CMB) signal and the main Galactic polarised foreground components. For the latter,…
Estimating the cosmological microwave background is of utmost importance for cosmology. However, its estimation from full-sky surveys such as WMAP or more recently Planck is challenging: CMB maps are generally estimated via the application…
Astrophysical foreground substraction is crucial to retrieve the cosmic microwave background (CMB) polarization out of the observed data. Recent efforts have been carried out towards the development of a minimally informed component…