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Proceedings Paper

Deterministic compressed sensing and quantization
Author(s): Arman Ahmadieh; Özgur Yilmaz
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Paper Abstract

Compressed Sensing (CS) is a sampling paradigm used for acquiring sparse or compressible signals from a seemingly incomplete set of measurements. In any practical application with our digitally driven technology, these "compressive measurements" are quantized and thus they do not have infinite precision. So far, the theory of quantization in CS has mainly focused on compressive sampling systems designed with random measurement matrices. In this note, we turn our attention to "deterministic compressed sensing". Specifically, we focus on quantization in CS with chirp sensing matrices and present quantization approaches and numerical experiments.

Paper Details

Date Published: 11 September 2015
PDF: 10 pages
Proc. SPIE 9597, Wavelets and Sparsity XVI, 95970P (11 September 2015); doi: 10.1117/12.2189211
Show Author Affiliations
Arman Ahmadieh, Univ. of British Columbia (Canada)
Özgur Yilmaz, Univ. of British Columbia (Canada)

Published in SPIE Proceedings Vol. 9597:
Wavelets and Sparsity XVI
Manos Papadakis; Vivek K. Goyal; Dimitri Van De Ville, Editor(s)

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