Abstract
In this paper, we present an iterative algorithm for computing sparse solutions (or sparse approximate solutions) to linear inverse problems. The algorithm is intended to supplement the existing arsenal of techniques. It is shown to converge to the local minima of a function of the form used for picking out sparse solutions, and its connection with existing techniques explained. Finally, it is demonstrated on subset selection and deconvolution examples. The fact that the proposed algorithm is sometimes successful when existing greedy algorithms fail is also demonstrated.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1331-1334 |
| Number of pages | 4 |
| Journal | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
| Volume | 3 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 6) - Atlanta, GA, USA Duration: May 7 1996 → May 10 1996 |
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering