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- W2012023453 abstract "We study recovering sparse and compressible signals using l <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>p</inf> minimization with p < 1 when some part of the support of the signal is known a priori. Sparse reconstruction method based on l <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>p</inf> minimization with partially known set is proposed. Recovery conditions of l <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>p</inf> minimization with partially known support is given. Theoretical results show that l <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>p</inf> minimization with partially known set is stable and robust. Furthermore, numerical results show that l <inf xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>p</inf> minimization with partially known support needs fewer measurements than the standard compressed sensing with partially known support" @default.
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- W2012023453 date "2012-04-01" @default.
- W2012023453 modified "2023-10-18" @default.
- W2012023453 title "Nonconvex compressed sensing with partially known support" @default.
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- W2012023453 doi "https://doi.org/10.1109/siu.2012.6204650" @default.
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