Name
Abstract | ||
|---|---|---|
This paper proposes blind source extraction methods based on several time-delay autocorrelations of primary sources, called MACBSE. The MACBSE approaches are batch fixed-point learning algorithms for extraction of source signals with linear autocorrelations. The fixed-point algorithms are very simple and do not need to choose any learning step sizes. Furthermore, the convergence properties of the algorithms are analyzed. Their efficiencies are demonstrated by extensive computer simulations. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.neucom.2007.09.004 | Neurocomputing |
Keywords | Field | DocType |
Blind source separation (BSS),Independent component analysis (ICA),Blind source extraction (BSE),Temporally correlated source | Convergence (routing),Pattern recognition,Computer science,Blind source extraction,Speech recognition,Artificial intelligence,Blind signal separation,Machine learning | Journal |
Volume | Issue | ISSN |
71 | 4 | 0925-2312 |
Citations | PageRank | References |
1 | 0.37 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhenwei Shi | 1 | 559 | 63.11 |
| Dan Zhang | 2 | 461 | 22.17 |
| Changshui Zhang | 3 | 5506 | 323.40 |