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arXiv · 2512.17377

Sobolev Algorithm for Local Smoothness Analysis (SALSA) via Sharp Direct and Inverse Statements

Sara Avesani·Leevan Ling·Francesco Marchetti·Tizian Wenzel
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Abstract

We extend sharp direct and inverse approximation statements for kernel-based methods for finitely smooth kernels, i.e. those whose native spaces are norm-equivalent to Sobolev spaces. In particular, our inverse results are now formulated for a broad class of approximation schemes beyond interpolation, extending existing theory. Building on these results, we propose a novel Sobolev Algorithm for Local Smoothness Analysis (SALSA) for detecting local smoothness properties of target data, including their degree of smoothness and non-smoothness. The method is rigorously grounded based on the sharp direct and inverse statements. Numerical experiments in various settings highlight the effectiveness of the proposed algorithm.

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Sara Avesani, Leevan Ling, Francesco Marchetti, Tizian Wenzel. 2025-12-19. Sobolev Algorithm for Local Smoothness Analysis (SALSA) via Sharp Direct and Inverse Statements. https://arxiv.org/abs/2512.17377

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