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A compressive sampling algorithm recovers approximately a nearly sparse vector x from a much smaller “sketch” given by the matrix vector product Φx. Different settings in the literature make different assumptions to meet strong requirements on the accuracy of the recovered signal. Some are robust to noise (that is, the signal may be far from sparse), but the matrix ¦ is only guaranteed to work on...
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