Iterative Thresholding for Demixing Structured Superpositions in High Dimensions

23 Jan 2017Mohammadreza SoltaniChinmay Hegde

We consider the demixing problem of two (or more) high-dimensional vectors from nonlinear observations when the number of such observations is far less than the ambient dimension of the underlying vectors. Specifically, we demonstrate an algorithm that stably estimate the underlying components under general \emph{structured sparsity} assumptions on these components... (read more)

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