RIPless Theory for Compressed Sensing
نویسندگان
چکیده
This paper discusses the theory for RIPless in compressed sensing (CS). In the literature, E.J. Candès has proved that δ2s < √ 2 − 1 is a sufficient condition via l1 optimization having s-sparse vector solution. Later, many researchers have improved the sufficient conditions on δ2s or δs. Such researches have supposed that a matrix A obeys RIP and a signal to recover is sparse. In this paper, we do not suppose that a matrix A obeys RIP and a signal is sparse. We propose the RIPless theory and the method of any signal recovery for noiseless and noisy cases in CS.
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