Efficient Sparsity Pattern Recovery
نویسندگان
چکیده
The theory of compressed sensing shows that sparsity pattern (or support) of a sparse signal can be recovered from a small number of appropriate linear projections (samples). Unfortunately, as soon as noise is added, the number of required samples exceeds the full signal dimension, rendering compressed sensing ineffective. In recent work, we have shown that this can be fixed if a small distortion is allowed in the signal recovery. The present paper extends our results to a simplified estimator.
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تاریخ انتشار 2009