Title :
On the role of sparsity in Compressed Sensing and random matrix theory
Author :
Vershynin, Roman
Author_Institution :
Dept. of Math., Univ. of Michigan, Ann Arbor, MI, USA
Abstract :
We discuss applications of some concepts of compressed sensing in the recent work on invertibility of random matrices due to Rudelson and the author. We sketch an argument leading to the optimal bound ¿(N-1/2) on the median of the smallest singular value of an N × N matrix with random independent entries. We highlight the parts of the argument where sparsity ideas played a key role.
Keywords :
matrix algebra; signal processing; compressed sensing sparsity; optimal bound; random matrix theory; Bibliographies; Collaboration; Compressed sensing; Conferences; Entropy; Extraterrestrial measurements; Functional analysis; History; Mathematics; Sparse matrices;
Conference_Titel :
Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009 3rd IEEE International Workshop on
Conference_Location :
Aruba, Dutch Antilles
Print_ISBN :
978-1-4244-5179-1
Electronic_ISBN :
978-1-4244-5180-7
DOI :
10.1109/CAMSAP.2009.5413304
