Atomic norm algorithms for blind spectral super-resolution problems
This thesis focuses on the development of atomic norm based algorithms for particular instances of blind super-resolution problems appearing in wireless communications, modal analysis in sensor networks, and target localization in radar signal processing. Blind super- resolution problems are a harder version of canonical super-resolution problems in that they include more degrees of freedom that must be resolved due to additional sources of blurring via unknown linear transformations. Our atomic norm algorithms focus on leveraging special sparsity structure with respect to certain dictionaries ...
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