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Data for "Quadrature-Based Compressive Sensing Guarantees for Bounded Orthonormal Systems", to be submitted to IEEE Signal Processing Letters

Published by National Institute of Standards and Technology | National Institute of Standards and Technology | Metadata Last Checked: June 27, 2025 | Last Modified: 2023-09-06 00:00:00
This dataset contains CSV files for the figures in the paper titled "Quadrature-Based Compressive Sensing Guarantees for Bounded Orthonormal Systems", to be submitted to the journal IEEE Signal Processing Letters. In this paper, we derive an approach to apply compressive sensing guarantees to linear inverse problems where measurements are samples of a function that can be expanded in a series of bounded orthonormal functions and require implementations using fast transform algorithms. In particular, we develop extensions of compressive sensing guarantees that can be used in the case described but where samples are taken on quadrature sample points instead of continuous sampling domains. This work has applications in antenna metrology, acoustic field measurements, astronomy, and more. The figures that this dataset is for are examples comparing transform algorithm times in continuous sample domains versus quadrature sample positions as well as comparisons of the performance of compressive sensing using continuous sampling versus quadrature-node-based sampling.

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