Date(s) : 24/01/2014 iCal
14 h 00 min - 15 h 00 min
Compressed sensing with unknown sensor permutation\nBy Valentin Emiya\, LIF.\n\nCompressed sensing is the ability to retrieve a sparse vector from a set of linear measurements. The task gets more difficult when the sensing process is not perfectly known. We address such a problem in the case where the sensors have been permuted\, i.e.\, the order of the measurements is unknown. We propose a branch-and-bound algorithm that converges to the solution. The experimental study shows that our approach always retrieves the unknown permutation\, while a simple convex relaxation strategy almost always fails. In terms of its time complexity\, we show that the proposed algorithm converges quickly with respect to the combinatorial nature of the problem.
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