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Stable and robust -constrained compressive sensing recovery via robust width property
We study the recovery results of -constrained compressive sensing
(CS) with via robust width property and determine conditions on the
number of measurements for standard Gaussian matrices under which the property
holds with high probability. Our paper extends the existing results in Cahill
and Mixon (2014) from -constrained CS to -constrained case with
and complements the recovery analysis for robust CS with
loss function