Name
Abstract | ||
|---|---|---|
This work presents a generalization of classical factor analysis (FA). Each of M channels carries measurements that share factors with all other channels, but also contains factors that are unique to the channel. Furthermore, each channel carries an additive noise whose covariance is diagonal, as is usual in factor analysis, but is otherwise unknown. This leads to a problem of multi-channel factor... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TSP.2019.2955829 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
Covariance matrices,Brain modeling,Load modeling,Maximum likelihood estimation,Signal processing algorithms,Loading | Cognitive science,Psychology,Multi channel,Applied psychology | Journal |
Volume | ISSN | Citations |
68 | 1053-587X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Ramírez | 1 | 206 | 20.05 |
| Ignacio Santamaría | 2 | 941 | 81.56 |
| Louis L. Scharf | 3 | 2525 | 414.45 |
| Steven Van Vaerenbergh | 4 | 257 | 19.82 |