Sparse recovery in bounded Riesz systems with applications to numerical methods for PDEs

نویسندگان

چکیده

We study sparse recovery with structured random measurement matrices having independent, identically distributed, and uniformly bounded rows a nontrivial covariance structure. This class of arises from sampling Riesz systems generalizes partial Fourier matrices. Our main result improves the currently available results for null space restricted isometry properties such The novelty our analysis is new upper bound expectation supremum Bernoulli process associated constant. apply to prove performance guarantees CORSING method, recently introduced numerical approximation technique differential equations (PDEs) based on compressive sensing.

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ژورنال

عنوان ژورنال: Applied and Computational Harmonic Analysis

سال: 2021

ISSN: ['1096-603X', '1063-5203']

DOI: https://doi.org/10.1016/j.acha.2021.01.004