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Tree-structured compressive sensing (CS) shows that it is possible to recover tree-sparse signals using fewer measurements compared with conventional CS. However, performance guarantees rely heavily on the premise that an exact tree projection (ETP) algorithm is employed. Nevertheless, for a given sparsity, the condensing sort and select algorithm in the model-based compressive sampling matching pursuit...
Multi-coset sampling is a compressed sampling strategy for the acquisition of spectrally sparse signal. In previous discrete blind recovery methods, either the sensing matrix is really huge, or the sampled sequences are interpolated to the Nyquist rate at the first step, both leading to a high computational complexity. A new discrete blind reconstruction method is proposed in this study to reconstruct...
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