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Compressive sensing using iterative hard thresholding with low precision data representation: Theory and applications

IEEE Transactions on Signal Processing, (2020): 4268-4282

Cited by: 1|Views12
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Abstract

Modern scientific instruments produce vast amounts of data, which can overwhelm the processing ability of computer systems. Lossy compression of data is an intriguing solution, but comes with its own drawbacks, such as potential signal loss, and the need for careful optimization of the compression ratio. In this work, we focus on a settin...More

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Author
Nezihe Merve Gürel
Nezihe Merve Gürel
Kaan Kara
Kaan Kara
Alen Stojanov
Alen Stojanov
Tyler Smith
Tyler Smith
Thomas Lemmin
Thomas Lemmin
Markus Püschel
Markus Püschel
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