Variational splines and Paley-Wiener spaces on Combinatorial graphs
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Publication:734052
DOI10.1007/s00365-007-9004-9zbMath1180.42026arXiv1111.5897OpenAlexW2014368295MaRDI QIDQ734052
Publication date: 19 October 2009
Published in: Constructive Approximation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1111.5897
compressed sensinggeneralized Fourier transformdiscrete Laplace transformvariational splinecombinatorial graph
Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Spline approximation (41A15) Graph theory (05C99) Nontrigonometric harmonic analysis (42C99) Sampling theory in information and communication theory (94A20)
Related Items (18)
Approximation theorems on graphs ⋮ Harmonic analysis invariants for infinite graphs via operators and algorithms ⋮ Sobolev orthogonal polynomials on the Sierpinski gasket ⋮ Graph signal sampling and interpolation based on clusters and averages ⋮ Half sampling on bipartite graphs ⋮ Analysis vs synthesis with structure -- an investigation of union of subspace models on graphs ⋮ Graph signal interpolation with positive definite graph basis functions ⋮ Gabor-type frames for signal processing on graphs ⋮ Overview of the topical collection: harmonic analysis on combinatorial graphs ⋮ Sampling, filtering and sparse approximations on combinatorial graphs ⋮ Geometric space-frequency analysis on manifolds ⋮ Eigenmaps and minimal and bandlimited immersions of graphs into Euclidean spaces ⋮ Removable sets and approximation of eigenvalues and eigenfunctions on combinatorial graphs ⋮ Partition of unity methods for signal processing on graphs ⋮ Interpolating splines on graphs for data science applications ⋮ Splines and wavelets on circulant graphs ⋮ Sampling by Averages and Average Splines on Dirichlet Spaces and on Combinatorial Graphs ⋮ Kernel-based models for influence maximization on graphs based on Gaussian process variance minimization
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