DocumentCode
1845335
Title
The prediction of observed samples under unknown rank in matrix completion
Author
Zhao Yu-Juan ; Zheng Bao-yu ; Chen Shou-ning
Author_Institution
Inst. of Signal Process. & Transm., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Volume
1
fYear
2012
fDate
21-25 Oct. 2012
Firstpage
111
Lastpage
114
Abstract
Matrix completion is the extension of compressed sensing, which uses the prior of low rank to recover original matrix. This paper introduces several reconstruction algorithms (SVT, ADMiRA and SVP) firstly, put forward their shortcomings to know the rank of original matrix, and propose our method to predict the observed samples under unknown rank of original matrix.
Keywords
compressed sensing; matrix algebra; ADMiRA; SVP; SVT; compressed sensing extension; matrix completion; observed samples; original matrix; reconstruction algorithms; unknown rank; compressed sensing; matrix completion; reconstruction algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing (ICSP), 2012 IEEE 11th International Conference on
Conference_Location
Beijing
ISSN
2164-5221
Print_ISBN
978-1-4673-2196-9
Type
conf
DOI
10.1109/ICoSP.2012.6491612
Filename
6491612
Link To Document