dc.contributor.author | Raffo, Andrea | |
dc.contributor.author | Biasotti, Silvia | |
dc.date.accessioned | 2022-03-18T12:54:49Z | |
dc.date.available | 2022-03-18T12:54:49Z | |
dc.date.created | 2020-08-25T12:36:49Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Numerical Algorithms. 2020, 1-29. | en_US |
dc.identifier.issn | 1017-1398 | |
dc.identifier.uri | https://hdl.handle.net/11250/2986215 | |
dc.description.abstract | Continuous representations are fundamental for modeling sampled data and perform ing computations and numerical simulations directly on the model or its elements.To effectively and efficiently address the approximation of point clouds, we propose the weighted quasi-interpolant spline approximation method (wQISA). We provide global and local bounds of the method and discuss how it still preserves the shape properties of the classical quasi-interpolation scheme. This approach is particularly useful when the data noise can be represented as a probabilistic distribution: from the point of view of non-parametric regression, the wQISA estimator is robust to ran dom perturbations, such as noise and outliers. Finally, we show the effectiveness of the method with several numerical simulations on real data, including curve fitting on images, surface approximation, and simulation of rainfall precipitations. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer | en_US |
dc.rights | An error occurred on the license name. | * |
dc.subject | Spline methods | en_US |
dc.subject | Quasi-interpolation | en_US |
dc.subject | Non-parametric regression | en_US |
dc.subject | Point clouds | en_US |
dc.subject | Raw data | en_US |
dc.subject | Noise | en_US |
dc.title | Weighted quasi-interpolant spline approximations: Properties and applications | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | acceptedVersion | en_US |
dc.rights.holder | This is a post-peer-review, pre-copyedit version of an article published in Numerical Algorithms. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11075-020-00989-4. | en_US |
dc.source.pagenumber | 819–847 | en_US |
dc.source.volume | 87 | en_US |
dc.source.journal | Numerical Algorithms | en_US |
dc.identifier.doi | 10.1007/s11075-020-00989-4 | |
dc.identifier.cristin | 1825015 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |