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- W2168665985 abstract "In this paper, we reconstruct signals from underdetermined linear measurements where the componentwise gains of the measurement system are unknown a priori. The reconstruction is performed through an adaptation of the messagepassing algorithm called adaptive GAMP that enables joint gain calibration and signal estimation. To evaluate our approach, we apply it to the problem of sparse recovery and compare it against an ℓ <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>1</sub> -based approach. We numerically show that adaptive GAMP yields excellent results even for a moderate amount of data. It approaches the performance of oracle GAMP where the gains are perfectly known asymptotically." @default.
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- W2168665985 date "2013-05-01" @default.
- W2168665985 modified "2023-10-01" @default.
- W2168665985 title "Autocalibrated signal reconstruction from linear measurements using adaptive GAMP" @default.
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- W2168665985 doi "https://doi.org/10.1109/icassp.2013.6638801" @default.
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