TY - GEN
T1 - The RIP for random matrices with complex Gaussian entries
AU - Xu, Kuo
AU - Wang, Jian
AU - Shim, Byonghyo
PY - 2014
Y1 - 2014
N2 - In this paper, we show that complex Gaussian random matrix satisfies the restricted isometric property (RIP) with overwhelming probability. We also show that for compressive sensing (CS) applications, complex Gaussian random matrix outperforms its real number equivalent in the sense that it requires fewer measurements for exact recovery of sparse signals. Numerical results confirm our analysis.
AB - In this paper, we show that complex Gaussian random matrix satisfies the restricted isometric property (RIP) with overwhelming probability. We also show that for compressive sensing (CS) applications, complex Gaussian random matrix outperforms its real number equivalent in the sense that it requires fewer measurements for exact recovery of sparse signals. Numerical results confirm our analysis.
KW - Sparse recovery
KW - complex Gaussian entries
KW - restricted isometric property
UR - http://www.scopus.com/inward/record.url?scp=84899799516&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84899799516&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40861-8_3
DO - 10.1007/978-3-642-40861-8_3
M3 - Conference contribution
AN - SCOPUS:84899799516
SN - 9783642408601
T3 - Lecture Notes in Electrical Engineering
SP - 13
EP - 19
BT - Future Information Technology, FutureTech 2013
PB - Springer Verlag
T2 - 8th FTRA International Conference on Future Information Technology, FutureTech 2013
Y2 - 4 September 2013 through 6 September 2013
ER -