TY - GEN
T1 - Blind deconvolution and compressed sensing
AU - Stoger, Dominik
AU - Jung, Peter
AU - Krahmer, Felix
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/15
Y1 - 2016/11/15
N2 - In this paper we consider the classical problem of blind deconvolution of multiple signals from its superposition, also called blind demixing and deconvolution. One is given a signal ∑ri=1 wi - xi = y RL which is the superposition of r unknown source signals {xi}ri=1 and convolution kernels {wi}ri=1 The goal is to reconstruct the vectors w; and x;, which are elements of known but random subspaces. The problem can be lifted into a low rank matrix recovery problem. We will discuss uniform as well as non-uniform recovery guarantees.
AB - In this paper we consider the classical problem of blind deconvolution of multiple signals from its superposition, also called blind demixing and deconvolution. One is given a signal ∑ri=1 wi - xi = y RL which is the superposition of r unknown source signals {xi}ri=1 and convolution kernels {wi}ri=1 The goal is to reconstruct the vectors w; and x;, which are elements of known but random subspaces. The problem can be lifted into a low rank matrix recovery problem. We will discuss uniform as well as non-uniform recovery guarantees.
UR - https://www.scopus.com/pages/publications/85002934559
U2 - 10.1109/CoSeRa.2016.7745692
DO - 10.1109/CoSeRa.2016.7745692
M3 - Conference contribution
AN - SCOPUS:85002934559
T3 - 2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016
SP - 24
EP - 27
BT - 2016 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing, CoSeRa 2016
Y2 - 19 September 2016 through 23 September 2016
ER -