Hybrid hyperinterpolation over general regions

We present an ℓ 2 2 + ℓ 1 -regularized discrete least squares approximation over general regions under assumptions of hyperinterpolation, named hybrid hyperinterpolation. Hybrid hyperinterpolation, using a soft thresholding operator and a filter function to shrink the Fourier coefficients approximat...

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Bibliographic Details
Published in:Calcolo 2025-03, Vol.62 (1), Article 3
Main Authors: An, Congpei, Ran, Jiashu, Sommariva, Alvise
Format: Article
Language:English
Subjects:
Approximation
Continuity (mathematics)
Mathematics
Mathematics and Statistics
Numerical Analysis
Operators (mathematics)
Parameters
Quadratures
Regularization
Theory of Computation
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Summary:We present an ℓ 2 2 + ℓ 1 -regularized discrete least squares approximation over general regions under assumptions of hyperinterpolation, named hybrid hyperinterpolation. Hybrid hyperinterpolation, using a soft thresholding operator and a filter function to shrink the Fourier coefficients approximated by a high-order quadrature rule of a given continuous function with respect to some orthonormal basis, is a combination of Lasso and filtered hyperinterpolations. Hybrid hyperinterpolation inherits features of them to deal with noisy data once the regularization parameter and the filter function are well chosen. We derive L 2 errors in theoretical analysis for hybrid hyperinterpolation to approximate continuous functions with noise data on sampling points. Numerical examples illustrate the theoretical results and show that well chosen regularization parameters can enhance the approximation quality over the unit-sphere and the union of disks.
ISSN:0008-0624
1126-5434
DOI:10.1007/s10092-024-00625-w