Dimension embedding for big data in radio interferometry

Vijay Kartik, Rafael E Carrillo, Yves Wiaux

Research output: Contribution to conferencePaperpeer-review

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As radio telescope data is now increasingly high- dimensional, data reduction has become essential. This abstract describes dimension embedding techniques that are being explored as a way to reduce data size and, consequently, computational load while preserving accurate signal reconstruction (in terms of SNR and dynamic range) in the context of radio interferometric imaging. In this work, dimension embeddings are being designed and evaluated for their ability to preserve information after embedding. Preliminary results suggest that random Gaussian embeddings may provide significant improvement with respect to standard gridding.
Original languageEnglish
Number of pages1
Publication statusPublished - 2015
EventBASP Frontiers 2015 - Villars-sur-Ollon, Lausanne, Switzerland
Duration: 25 Jan 201530 Jan 2015


WorkshopBASP Frontiers 2015


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