Inh.: Dr. Renate Gorre
Fon: +49 (0)7533 97227
Fax: +49 (0)7533 97228
Series in Communication Theory
Edited by Helmut Bölcskei
Uncertainty relations and sparse signal recovery are
of significant interest in the signal processing and applied mathematics
community. A large number of signal processing problems and scenarios can be
cast as sparse signal recovery problems and solved using the corresponding
tools. Prominent examples include signal separation, image inpainting,
super-resolution, and the recovery of signals that are impaired by narrowband
interference or clipped. This work presents a novel uncertainty relation for
pairs of general signal sets and improved sparsity thresholds for the recovery
of signals that are sparse in an arbitrary dictionary. Furthermore, guarantees
for the restoration of sparse signals that are corrupted by sparse noise are
provided. Finally, the recovery of signals lying in unions of subspaces is
investigated and recovery algorithms with corresponding analytical performance
guarantees are presented.
Patrick Kuppinger was born in Freiburg, Germany, in 1983. He received the BSc degree in Electrical Engineering and Information Technology in 2005 from ETH Zurich, Switzerland, and the MSc degree with distinction in Communications and Signal Processing in 2006 from Imperial College London, UK. After graduating from Imperial College, he joined the Communication Technology Laboratory at ETH Zurich, where he graduated with the Dr. sc. degree in 2011.
Keywords: uncertainty relations; sparse signal recovery; signal separation; image inpainting; block-sparse signals.
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