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Sample Complexity of Total Variation Minimization
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DOI：10.1109/LSP.2018.2847051.png)
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摘要
En 中文
This letter considers the use of total variation (TV) minimization in the recovery of a given gradient sparse vector from Gaussian linear measurements. It has been shown in recent studies that there exists a sharp phase transition behavior in TV minimization for the number of measurements necessary to recover the signal in asymptotic regimes. The phase-transition curve specifies the boundary of success and failure of TV minimization for large number of measurements. It is a challenging task to obtain a theoretical bound that reflects this curve. In this letter, we present a novel upper bound that suitably approximates this curve and is asymptotically sharp. Numerical results show that our bound is closer to the empirical TV phase-transition curve than the previously known bound obtained by Kabanava.
Keyword:
Phase transition
sample complexity
total variation (TV) minimization
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9.6
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1.1W
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1.7W
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