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Iterative Soft/Hard Thresholding with Homotopy Continuation for Sparse Recovery
In this note, we analyze an iterative soft / hard thresholding algorithm with
homotopy continuation for recovering a sparse signal from noisy data
of a noise level . Under suitable regularity and sparsity conditions,
we design a path along which the algorithm can find a solution which
admits a sharp reconstruction error with an iteration complexity , where and are problem dimensionality and
controls the length of the path. Numerical examples are given to illustrate its
performance.Comment: 5 pages, 4 figure
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