DocumentCode
2185758
Title
Low-rank matrix recovery from non-linear observations
Author
Bhattacharjee, Protim ; Khurana, Prerna ; Majumdar, Angshul
Author_Institution
IIIT-Delhi, India
fYear
2015
fDate
21-24 July 2015
Firstpage
623
Lastpage
627
Abstract
Algorithms for sparse recovery problems from non-linear measurements have attracted some attention lately. Closely related to the problem of sparse is recovery is the problem of low-rank matrix recovery. There is no work on the topic of low-rank matrix recovery from non-linear measurements. This is the first study that proposes two algorithms for the said problem. The first one is based on nuclear norm minimization while the second one is based on Ky-Fan norm minimization.
Keywords
Inverse problems; Magnetic resonance imaging; Matrix decomposition; Minimization; Protons; Signal processing algorithms; Sparse matrices; Ky-Fan norm; matrix completion; non-linear inverse problem; nuclear norm;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Signal Processing (DSP), 2015 IEEE International Conference on
Conference_Location
Singapore, Singapore
Type
conf
DOI
10.1109/ICDSP.2015.7251949
Filename
7251949
Link To Document