Rongda Zhu

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In this paper, we propose a novel algorithm based on nonconvex sparsity-inducing penalty for one-bit compressed sensing. We prove that our algorithm has a sample complexity of O(s// 2) for strong signals, and O(s log d// 2) for weak signals , where s is the number of nonzero entries in the signal vector, d is the signal dimension and is the recovery error.(More)
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