Onose, A;
Carrillo, R;
McEwen, J;
Wiaux, Y;
(2016)
A randomised primal-dual algorithm for distributed radio-interferometric imaging.
In:
2016 24th European Signal Processing Conference (EUSIPCO).
(pp. pp. 1448-1452).
IEEE
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Abstract
Next generation radio telescopes, like the Square Kilometre Array, will acquire an unprecedented amount of data for radio astronomy. The development of fast, parallelisable or distributed algorithms for handling such large-scale data sets is of prime importance. Motivated by this, we investigate herein a convex optimisation algorithmic structure, based on primal-dual forward-backward iterations, for solving the radio interferometric imaging problem. It can encompass any convex prior of interest. It allows for the distributed processing of the measured data and introduces further flexibility by employing a probabilistic approach for the selection of the data blocks used at a given iteration. We study the reconstruction performance with respect to the data distribution and we propose the use of nonuniform probabilities for the randomised updates. Our simulations show the feasibility of the randomisation given a limited computing infrastructure as well as important computational advantages when compared to state-of-the-art algorithmic structures.
Type: | Proceedings paper |
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Title: | A randomised primal-dual algorithm for distributed radio-interferometric imaging |
Event: | 24th European Signal Processing Conference (EUSIPCO) |
Location: | Budapest, Hungary |
Dates: | 29 August 2016 - 02 September 23016 |
ISBN-13: | 978-0-9928-6265-7 |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp... |
Language: | English |
Additional information: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
Keywords: | Signal processing algorithms, Image reconstruction, Imaging, Minimization, Distributed databases, Signal processing, Optimization |
UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Space and Climate Physics |
URI: | https://discovery.ucl.ac.uk/id/eprint/1523148 |
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