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arXiv · 1007.4396

Restricted $p$-isometry property and its application for nonconvex compressive sensing

Yi Shen·Song Li
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Abstract

Compressed sensing is a new scheme which shows the ability to recover sparse signal from fewer measurements, using $l_1$ minimization. Recently, Chartrand and Staneva shown in \cite{CS1} that the $l_p$ minimization with $0 1 - 1 / {N\choose S}$ for $p$ smaller. The second purpose of the paper is to show that under certain weaker conditions, decoders $\triangle_p$ are stable in the sense that they are $(2,p)$ instance optimal for a large class of encoder for $0<p<1.$

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Yi Shen, Song Li. 2011-03-01. Restricted $p$-isometry property and its application for nonconvex compressive sensing. https://arxiv.org/abs/1007.4396

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