Reducing noise in moving-grid codes with strongly-centroidal Lloyd mesh regularization

Convergence of the Lloyd Algorithm for Computing Centroidal Voronoi Tessellations

Centroidal Voronoi tessellations (CVTs) are Voronoi tessellations of a bounded geometric domain such that the generating points of the tessellations are also the centroids (mass centers) of the corresponding Voronoi regions with respect to a given density function. Centroidal Voronoi tessellations may also be defined in more abstract and more general settings. Due to the natural optimization pr...

Adaptive Polygonal Mesh Simplification With Discrete Centroidal Voronoi Diagrams

In this paper, we propose an adaptive polygonal mesh coarsening algorithm. This approach is based on the clustering of the input mesh triangles, driven by a discretized variationnal definition of centroidal tesselations. It is able to simplify meshes with high complexity i.e. meshes with a large number of vertices and high genus. We demonstrate the ability our scheme to simplify meshes accordin...

Weak Global Convergence of the Lloyd Method for Computing Centroidal Voronoi Tessellations in R

A Noise-Robust Method with Smoothed \ell_1/\ell_2 Regularization for Sparse Moving-Source Mapping

The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smooth l1/l2 regularization term. As the mean of the noise in the power spectrum domain is dependent on its variance in the time domain, the proposed method includes a variance estimation step, which allows more ...

A Noise-Robust Method with Smoothed ℓ1/ℓ2 Regularization for Sparse Moving-Source Mapping

The method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smoothed `1/`2 regularization term. As the mean of the noise in the power spectrum domain depends on its variance in the time domain, the proposed method includes a variance estimation step, which allows more rob...