Low-rank matrix recovery: blind deconvolution and efficient sampling of correlated signals

Low-dimensional signal structures naturally arise in a large set of applications in various fields such as medical imaging, machine learning, signal, and array processing. A ubiquitous low-dimensional structure in signals and images is sparsity, and a new sampling theory; namely, compressive sensing...

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Bibliographic Details
Main Author: Ahmed, Ali
Other Authors: Romberg, Justin K.
Format: Others
Language:en_US
Published: Georgia Institute of Technology 2014
Subjects:
Online Access:http://hdl.handle.net/1853/50226