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MAP recovery of polynomial splines from compressive samples and its application to vehicular signals
2013
Wavelets and Sparsity XV
We propose a stable reconstruction method for polynomial splines from compressive samples based on the maximum a posteriori (MAP) estimation. The polynomial splines are one of the most powerful tools for modeling signals in real applications. 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 noiseless samples acquired at,
doi:10.1117/12.2024039
fatcat:6lhhkas7hjckje4gs7lblqbegi