John M. Boyer, Charles F. Wiecha
DocEng 2009
Compressed sensing is a technique for finding sparse solutions to underdetermined linear systems. This technique relies on properties of the sensing matrix such as the restricted isometry property. Sensing matrices that satisfy this property with optimal parameters are mainly obtained via probabilistic arguments. Deciding whether a given matrix satisfies the restricted isometry property is a nontrivial computational problem. Indeed, it is shown in this paper that restricted isometry parameters cannot be approximated in polynomial time within any constant factor under the assumption that the hidden clique problem is hard. In addition, on the positive side, an improvement on the brute-force enumeration algorithm for checking the restricted isometry property is proposed. © 2014 IEEE.
John M. Boyer, Charles F. Wiecha
DocEng 2009
Raghu Krishnapuram, Krishna Kummamuru
IFSA 2003
Donald Samuels, Ian Stobert
SPIE Photomask Technology + EUV Lithography 2007
Khaled A.S. Abdel-Ghaffar
IEEE Trans. Inf. Theory