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- W4200462502 abstract "Abstract Positive definite kernels are powerful tools for multivariate approximation from scattered data. This contribution discusses kernel‐based image approximation from scattered Radon data. To this end, we use weighted kernels for the reconstruction. Moreover, we propose greedy algorithms, which are used to adaptively select suitable approximation spaces. This reduces the complexity of the resulting image reconstruction method and, moreover, it improves the numerical stability quite significantly." @default.
- W4200462502 created "2021-12-31" @default.
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- W4200462502 date "2021-12-01" @default.
- W4200462502 modified "2023-10-16" @default.
- W4200462502 title "Greedy algorithms for image approximation from scattered Radon data" @default.
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- W4200462502 doi "https://doi.org/10.1002/pamm.202100223" @default.
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