Name
Abstract | ||
|---|---|---|
In this paper, we propose an embedding technique for univariate single-channel biomedical signals to apply projective subspace techniques. Biomedical signals are often recorded as 1-D time series; hence, they need to be transformed to multidimensional signal vectors for subspace techniques to be applicable. The transformation can be achieved by embedding an observed signal in its delayed coordinat... |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TIM.2009.2016385 | IEEE Transactions on Instrumentation and Measurement |
Keywords | Field | DocType |
Multidimensional systems,Principal component analysis,Kernel,Signal processing,Covariance matrix,Electroencephalography,Electrooculography,Additive noise,Signal analysis,Geophysics computing | Kernel (linear algebra),Signal processing,Embedding,Pattern recognition,Subspace topology,Kernel principal component analysis,Singular spectrum analysis,Artificial intelligence,Mathematics,Principal component analysis,Multidimensional systems | Journal |
Volume | Issue | ISSN |
58 | 8 | 0018-9456 |
Citations | PageRank | References |
13 | 1.51 | 14 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ana R. Teixeira | 1 | 34 | 3.77 |
| Ana Maria Tomé | 2 | 163 | 30.42 |
| Matthias Böhm | 3 | 84 | 12.17 |
| Carlos García Puntonet | 4 | 107 | 25.86 |
| Elmar Wolfgang Lang | 5 | 260 | 36.10 |