Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors

2021 IEEE Information Theory Workshop (ITW)(2021)

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摘要
In 1-bit compressive sensing, each measurement is quantized to a single bit, namely the sign of a linear function of an unknown vector, and the goal is to accurately recover the vector. While it is most popular to assume a standard Gaussian sensing matrix for 1-bit compressive sensing, using structured sensing matrices such as partial Gaussian circulant matrices is of significant practical importa...
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关键词
Conferences,Computational modeling,Sensors,Compressed sensing,Standards,Optimization,Information theory
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