We consider the task of recovering two real or complexm-vectors from phase less Fourier measurements of their circular convolution. Our method is a novel convex relaxation that is based on a lifted matrix recovery formulation that allows a non-trivial convex relaxation of the bilinear measurements from convolution. We prove that if the two signals belongto […]
We consider the bilinear inverse problem of recovering two vectors, and , from their entrywise product. We consider the case where and have known signs and are sparse with respect to known dictionaries of size and , respectively. Here, and may be larger than, smaller than, or equal to . We introduce -BranchHull, which is […]
We consider the bilinear inverse problem of recovering two vectors, and , in from their entrywise product. For the case where the vectors have known signs and belong to known subspaces, we introduce the convex program BranchHull, which is posed in the natural parameter space and does not require an approximate solution or initialization in […]
We consider the bilinear inverse problem of recovering two vectors, and , from their entrywise product. We consider the case where and have known signs and are sparse with respect to known dictionaries of size and , respectively. Here, and may be larger than, smaller than, or equal to . We introduce -BranchHull, which is […]
We consider the task of recovering two real or complex -vectors from phaseless Fourier measurements of their circular convolution. Our method is a novel convex relaxation that is based on a lifted matrix recovery formulation that allows a nontrivial convex relaxation of the bilinear measurements from convolution. We prove that if the two signals belong […]
