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Convex Blind Deconvolution with Random Masks

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Abstract

We solve blind deconvolution problems where one signal is modulated by multiple random masks using nuclear norm minimization. Theoretical analysis shows the number of masks for successful recovery scales as poly-logarithm of the problem dimension.

© 2014 Optical Society of America

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