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SUMMARY:Phaseless super-resolution using masks - James Saunderson\, Monash
  University
DTSTART:20161128T140000Z
DTEND:20161128T150000Z
UID:TALK69011@talks.cam.ac.uk
CONTACT:Rachel Furner
DESCRIPTION:Phaseless super-resolution is the problem of reconstructing a 
 signal from low-frequency (super-resolution) Fourier magnitude (phaseless)
  measurements\, and is the combination of two classical signal processing 
 problems.  We consider the setting in which the signal to be recovered is 
 sparse\, and the measurements consist of the magnitudes of the low-frequen
 cy Fourier coefficients of certain masked versions of the signal. We devel
 op a single convex optimisation problem for phaseless super-resolution tha
 t\, in the noise-free setting\, recovers sparse signals (satisfying a mini
 mum separation condition) from a near-optimal number of phaseless masked m
 easurements. We also establish stability guarantees for approximate recove
 ry in the presence of measurement noise.\n\nJoint work with: Kishore Jagan
 athan (Illumina)\, Maryam Fazel (University of Washington)\, Yonina Eldar 
 (Technion)\, Babak Hassibi (Caltech) 
LOCATION:MR5 Centre for Mathematical Sciences
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