Analysis of hard-thresholding for distributed compressed sensing with one-bit measurements

Author:

Maly Johannes1,Palzer Lars2

Affiliation:

1. Department of Mathematics, Technical University of Munich, Germany

2. Department of Electrical and Computer Engineering, Technical University of Munich, Germany

Abstract

Abstract A simple hard-thresholding operation is shown to be able to uniformly recover $L$ signals $\textbf{x}_1,...,\textbf{x}_L \in{\mathbb{R}}^n$ that share a common support of size $s$ from $m = \mathscr{O}(s)$ one-bit measurements per signal if $L \geqslant \ln (en/s)$. This result improves the single signal recovery bounds with $m = \mathscr{O}(s\ln (en/s))$ measurements in the sense that asymptotically fewer measurements per non-zero entry are needed. Numerical evidence supports the theoretical considerations.

Funder

German Research Foundation

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Computational Theory and Mathematics,Numerical Analysis,Statistics and Probability,Analysis

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Distributed Decoding From Heterogeneous 1-Bit Compressive Measurements;Journal of Computational and Graphical Statistics;2022-10-14

2. Exploring Fundamental Limits of Spatiotemporal Sensing for Non-Linear Inverse problems;2021 55th Asilomar Conference on Signals, Systems, and Computers;2021-10-31

3. A fast algorithm for joint sparse signal recovery in 1-bit compressed sensing;AEU - International Journal of Electronics and Communications;2021-08

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