"Sparse super resolution is Lipschitz continuous"Hockmann, MathiasMotivated by the application of neural networks in super resolution microscopy, this talk considers super resolution as the mapping of trigonometric moments of a discrete measure on $[0,1)^d$ to its support and weights. We prove that this map satisfies a local Lipschitz property where we give explicit estimates for the Lipschitz constant depending on the dimension $d$ and the sampling effort. Moreover, this local Lipschitz estimate allows to conclude that super resolution with the Wasserstein distance as the metric on the parameter space is even globally Lipschitz continuous. As a byproduct, we present an improved estimate for the smallest singular value of multivariate Vandermonde matrices having pairwise clustering nodes. |
| http://univie.ac.at/projektservice-mathematik/e/talks/Hockmann_2021-06_ICCHA_2021_Hockmann_and_Kunis.pdf |
« back