Stochastic generalized sampling uses leverage-score sampling and a new matrix Bernstein inequality to guarantee stable recovery at m ≳ n log n samples with high probability, even for redundant frames, and demonstrates near-exponential convergence on analytic function recovery from Fourier data.
Stable reconstructions in hilbert spaces and the resolution of the gibbs phenomenon.Applied and Computational Harmonic Analysis, 32(3):357–388, 2012
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Stochastic Generalized Sampling
Stochastic generalized sampling uses leverage-score sampling and a new matrix Bernstein inequality to guarantee stable recovery at m ≳ n log n samples with high probability, even for redundant frames, and demonstrates near-exponential convergence on analytic function recovery from Fourier data.