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Showing 1 to 3 of 3 for “"Smooth basis functions"”.

  1. Local Smoothing Methods for the Analysis of Multivariate Complex Data Structures

    Local smoothing methods are a widely used tool in the context of nonparametric regression. The essential idea is to perform a linear or polynomial regression locally in a neighborhood of the target point. This method is generalized in two ways. Firstly, the polynomials are substituted by arbitrary …

    lmu-germany Repository record for Local Smoothing Methods for the Analysis of Multivariate Complex Data Structures (opens in a new tab)

  2. Mollified piecewise polynomial approximants of arbitrary order and smoothness

    … or mollification regularises piecewise functions with improved differentiability based on the continuity of the mollifier. Therefore convolution is suitable to generating smooth basis functions that reproduce global polynomial and is easy to construct on polytopic cells. We propose the …

    cambridge Repository record for Mollified piecewise polynomial approximants of arbitrary order and smoothness (opens in a new tab)

  3. Finite elements for higher-order problems in isogeometric analysis and statistical inference

    … is essential. The construction of isogeometric smooth spline basis functions is crucial for solving higher-order partial differential equations on meshes with arbitrary topologies. We introduce a simple blending approach that produces smooth blended B-splines, referred to as SB-splines, on …

    cambridge Repository record for Finite elements for higher-order problems in isogeometric analysis and statistical inference (opens in a new tab)