The Open Applied Mathematics Journal

2007, 1 : 21-23
Published online 2007 December 31. DOI: 10.2174/1874114200701010021
Publisher ID: TOAMJ-1-21

Note on Sparsity in Signal Recovery and in Matrix Identification

Götz E. Pfander
School of Engineering and Science, Jacobs University Bremen, 28759 Bremen, Germany.

ABSTRACT

We describe a connection between the identification problem for matrices with sparse representations in given matrix dictionaries and the problem of sparse signal recovery. This allows the application of novel compressed sensing techniques to operator identification problems such as the channel measurement problem in communications engineering.

Keywords:

Sparse signal recovery, compressed sensing, Basis Pursuit, time–frequency shifts.