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
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;
Conference_Titel :
Signal Processing (ICSP), 2012 IEEE 11th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-2196-9
DOI :
10.1109/ICoSP.2012.6491612
