Title :
Minimum subspace approximation property for sparse approximations in finite dimension
Author :
Aldroubi, Akram ; Tessera, Romian
Author_Institution :
Dept. of Math., Vanderbilt Univ., Nashville, TN, USA
Abstract :
We find necessary and sufficient conditions that a class of subspaces C must satisfy so that a solution exits to the problem of finding the subspace V ¿ C that best approximate a set of data F ¿ ¿d.
Keywords :
approximation theory; sparse matrices; finite dimension; minimum subspace approximation property; sparse approximation; Application software; Computer science; Computer vision; Cost function; Face recognition; Hilbert space; Mathematics; Singular value decomposition; Subspace constraints; Sufficient conditions;
Conference_Titel :
Information Sciences and Systems (CISS), 2010 44th Annual Conference on
Conference_Location :
Princeton, NJ
Print_ISBN :
978-1-4244-7416-5
Electronic_ISBN :
978-1-4244-7417-2
DOI :
10.1109/CISS.2010.5464979
