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- W2036268274 abstract "We propose a stable reconstruction method for polynomial splines from compressive samples based on the maximum aposteriori (MAP) estimation. The polynomial splines are one of the most powerful tools for modeling signals in realapplications. Since such signals are not band-limited, the classical sampling theorem cannot be applied to them. However,splines can be regarded as signals with finite rate of innovation and therefore be perfectly reconstructed from noiselesssamples acquired at, approximately, the rate of innovation. In noisy case, the conventional approach exploits Cadzowdenoising. Our approach based on the MAP estimation reconstructs the signals more stably than not only the conventionalapproach but also a maximum likelihood estimation. We show the effectiveness of the proposed method by applying it tocompressive sampling of vehicular signals." @default.
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- W2036268274 date "2013-09-26" @default.
- W2036268274 modified "2023-09-25" @default.
- W2036268274 title "MAP recovery of polynomial splines from compressive samples and its application to vehicular signals" @default.
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- W2036268274 doi "https://doi.org/10.1117/12.2024039" @default.
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