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• W2798433853 abstract "This work proposes a frequency and amplitude estimator tailored for noise corrupted signals that have been clipped. Formulated as a sparse reconstruction problem, the proposed algorithm estimates the signal parameters by solving an atomic norm minimization problem. The estimator also exploits the waveform information provided by the clipped samples, incorporated in the form of linear constraints that have been augmented by slack variables as to provide robustness to noise. Numerical examples indicate that the algorithm offers preferable performance as compared to methods not exploiting the saturated samples." @default.
• W2798433853 created "2018-05-07" @default.
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• W2798433853 date "2017-10-01" @default.
• W2798433853 modified "2023-09-27" @default.
• W2798433853 title "Grid-less estimation of saturated signals" @default.
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• W2798433853 doi "https://doi.org/10.1109/acssc.2017.8335204" @default.
• W2798433853 hasPublicationYear "2017" @default.
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