<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The application of the Partition of Unity Method (PUM) to signal approximation on graphs represents a recent advancement of this versatile and efficient interpolation technique. Given the novelty of this approach, little is yet known regarding the role of kernel parameters employed in constructing the associated Graph Basis Functions (GBFs). In order to shed light on this aspect, this study proposes several numerical tests obtained using GBFs generated by heat kernels and variational spline kernels.</p>
</abstract>

The application of the Partition of Unity Method (PUM) to signal approximation on graphs represents a recent advancement of this versatile and efficient interpolation technique. Given the novelty of this approach, little is yet known regarding the role of kernel parameters employed in constructing the associated Graph Basis Functions (GBFs). In order to shed light on this aspect, this study proposes several numerical tests obtained using GBFs generated by heat kernels and variational spline kernels.

Exploration of Kernel Parameters in Signal GBF-PUM Approximation on Graphs

Department of Mathematics “Giuseppe Peano”

Communications in Applied and Industrial Mathematics

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Exploration of Kernel Parameters in Signal GBF-PUM Approximation on Graphs"}

The application of the Partition of Unity Method (PUM) to signal approximation on graphs represents a recent advancement of this versatile and efficient...

Exploration of Kernel Parameters in Signal GBF-PUM Approximation on Graphs

Publié en ligne: 17 juil. 2024

Pages: 66 - 85

Reçu: 31 mai 2024

Accepté: 11 juin 2024

DOI: https://doi.org/10.2478/caim-2024-0004

Mots clés
Graph Interpolation, Kernel Methods, Graph Basis Functions, Partition of Unity Methods, Approximation Algorithms

© 2024 R. Cavoretto et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Exploration of Kernel Parameters in Signal GBF-PUM Approximation on Graphs

Publié en ligne: 17 juil. 2024

Pages: 66 - 85

Reçu: 31 mai 2024

Accepté: 11 juin 2024

DOI: https://doi.org/10.2478/caim-2024-0004

Mots clésGraph Interpolation, Kernel Methods, Graph Basis Functions, Partition of Unity Methods, Approximation Algorithms

© 2024 R. Cavoretto et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Graph Interpolation, Kernel Methods, Graph Basis Functions, Partition of Unity Methods, Approximation Algorithms