Deterministic compressed sensing and quantization

Arman Ahmadieh; Özgur Yilmaz

doi:10.1117/12.2189211

11 September 2015 Deterministic compressed sensing and quantization

Arman Ahmadieh, Özgur Yilmaz

Proceedings Volume 9597, Wavelets and Sparsity XVI; 95970P (2015) https://doi.org/10.1117/12.2189211
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

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.

Citation Download Citation

Arman Ahmadieh and Özgur Yilmaz "Deterministic compressed sensing and quantization", Proc. SPIE 9597, Wavelets and Sparsity XVI, 95970P (11 September 2015); https://doi.org/10.1117/12.2189211

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