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Dimension embedding for big data in radio interferometry

Publications associées (43)

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Design and Fabrication of a Prototype Actuator for Fourier Transform Interferometry

Yves Bellouard

The design, fabrication and characterisation of an uniaxial scanning mirror component for interferometry applications is presented. The device is fabricated in fused silica by means of femtosecond laser irradiation and a selective etching step. The fabrica ...

2014

Applications of Model Reduction Techniques in Aerospace Combustors

Jan Sickmann Hesthaven

In this paper we consider some practical applications of model reduction methods in unstable gas turbine and rocket combustion. We explore a set of promising methods for reducing computational burden in large scale LES calculations of unsteady turbulent co ...

2014

The varying w spread spectrum effect for radio interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

We study the impact of the spread spectrum effect in radio interferometry on the quality of image reconstruction. This spread spectrum effect will be induced by the wide ﬁeld-of-view of forthcoming radio interferometric telescopes. The resulting chirp modu ...

2013

Sparsity Averaging Reweighted Analysis (SARA): a novel algorithm for radio-interferometric imaging

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

We propose a novel algorithm for image reconstruction in radio interferometry. The ill-posed inverse problem associated with the incomplete Fourier sampling identified by the visibility measurements is regularized by the assumption of average signal sparsi ...

Wiley-Blackwell2012

Nonlinear data description with Principal Polynomial Analysis

Devis Tuia

Principal Component Analysis (PCA) has been widely used for manifold description and dimensionality reduction. Performance of PCA is however hampered when data exhibits nonlinear feature relations. In this work, we propose a new framework for manifold lear ...

2012

Low-rank Matrix Approximation Using Point-wise Operators

Arash Amini, Amin Karbasi

Extracting low dimensional structure from high dimensional data arises in many applications such as machine learning, statistical pattern recognition, wireless sensor networks, and data compression. If the data is restricted to a lower dimensional subspace ...

Institute of Electrical and Electronics Engineers2012

Coherence properties of exciton polariton OPO condensates in one and two dimensions

We give an overview of the coherence properties of exciton-polariton condensates generated by optical parametric scattering. Different aspects of the first-order coherence (g((1))) have been investigated. The spatial coherence extension of a two-dimensiona ...

Iop Publishing Ltd2012

Compressed sensing for radio interferometric imaging: review and future

Yves Wiaux, Jason Douglas McEwen

Radio interferometry is a powerful technique for astronomical imaging. The theory of compressed sensing (CS) has been applied recently to the ill-posed inverse problem of recovering images from the measurements taken by radio interferometric telescopes. We ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Learning Low-Dimensional Signal Models

Volkan Cevher

Sampling, coding, and streaming even the most essential data, e.g., in medical imaging and weather-monitoring applications, produce a data deluge that severely stresses the avail able analog-to-digital converter, communication bandwidth, and digital-storag ...

Institute of Electrical and Electronics Engineers2011

Compressed sensing for wide-field radio interferometric imaging

Yves Wiaux, Jason Douglas McEwen

For the next generation of radio interferometric telescopes it is of paramount importance to incorporate wide field-of-view (WFOV) considerations in interferometric imaging, otherwise the fidelity of reconstructed images will suffer greatly. We extend comp ...

Wiley-Blackwell2011