Name
Abstract | ||
|---|---|---|
This paper presents a novel independent component analysis algorithm that separates mixtures using serially updating geodesic method. The geodesic method is derived from the Stiefel manifold, and an on-line version of this method that can directly treat with the unwhitened observations is obtained. Simulation of artificial data as well as real biological data reveals that our proposed method has fast convergence. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11759966_162 | ISNN (1) |
Keywords | Field | DocType |
stiefel manifold,artificial data,geodesic method,unwhitened observation,real biological data,separates mixture,algorithm utilizing geodesic approach,on-line version,novel independent component analysis,biological data,independent component analysis | Convergence (routing),Biological data,Pattern recognition,Computer science,Algorithm,Stiefel manifold,Artificial intelligence,Method of lines,Independent component analysis,Artificial neural network,Blind signal separation,Geodesic | Conference |
Volume | ISSN | ISBN |
3971 | 0302-9743 | 3-540-34439-X |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tao Yu | 1 | 0 | 0.34 |
| Huai-Zong Shao | 2 | 50 | 13.46 |
| Qicong Peng | 3 | 43 | 7.07 |