Bounds on Discrete Fourier Transform of Random Mask
Nematollah Zarmehi, Farokh Marvasti
TL;DR
This paper establishes bounds on the maximum magnitude of a random mask in the Fourier domain, aiding iterative recovery methods in random sampling schemes.
Contribution
It introduces new bounds on the Fourier transform of random masks and compares them with empirical data.
Findings
Proposed bounds are tighter than existing estimates.
Bounds are validated through empirical examples.
Results improve understanding of random mask behavior in Fourier domain.
Abstract
This paper proposes some bounds on the maximum of magnitude of a random mask in Fourier domain. The random mask is used in random sampling scheme. Having a bound on the maximum value of a random mask in Fourier domain is very useful for some iterative recovery methods that use thresholding operator. In this paper, we propose some different bounds and compare them with the empirical examples.
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