Name
Abstract | ||
|---|---|---|
Blind separation of mixtures has been achieved by approximate joint diagonalization (AJD) approaches. This paper presents an approach for overdetermined blind source separation (BSS) using AJD. The approach is based on an alternative minimization of the indirect and direct least-squares criteria to the diagonal matrices in the first phase and to the mixing matrix in the second phase, respectively. Simulation result demonstrates that the proposed algorithm is capable for achieving better separation performance in overdetermined mixtures than in determined mixtures at reduced complexity. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/MWSCAS.2017.8052887 | 2017 IEEE 60th International Midwest Symposium on Circuits and Systems (MWSCAS) |
Keywords | Field | DocType |
overdetermined blind source separation,diagonal matrices,approximate joint diagonalization approaches,AJD approaches,BSS,minimization,direct least-squares criteria,indirect least-squares criteria,mixing matrix,reduced complexity | Overdetermined system,Mathematical optimization,Matrix (mathematics),Matrix decomposition,Signal-to-noise ratio,Algorithm,Electronic engineering,Minification,Diagonal matrix,Blind signal separation,Mathematics | Conference |
ISSN | ISBN | Citations |
1548-3746 | 978-1-5090-6390-1 | 0 |
PageRank | References | Authors |
0.34 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taiki Asamizu | 1 | 0 | 0.34 |
| Shinya Saito | 2 | 11 | 1.95 |
| kunio oishi | 3 | 8 | 1.54 |
| T. Furukawa | 4 | 2 | 1.77 |