| ID:
596849.0,
MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung) / Abt. Schölkopf (Empirical Inference) |
| Finding dependencies between frequencies with the kernel cross-spectral density |
| Authors: | Besserve, M.; Janzing, D.; Logothetis, N. K.; Schölkopf, B. |
| Place of Publication: | Praha, Czech Republic |
| Date of Publication (YYYY-MM-DD): | 2011-05-01 |
| Title of Proceedings: | IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011) |
| Start Page: | 2080 |
| End Page: | 2083 |
| Physical Description: | 3 |
| Review Status: | not specified |
| Audience: | Not Specified |
| Intended Educational Use: | No |
| Abstract / Description: | Cross-spectral density (CSD), is widely used to find linear dependency between two real or complex valued time series. We define a non-linear extension of this measure by mapping the time series into two Reproducing Kernel Hilbert Spaces. The dependency is quantified by the Hilbert Schmidt norm of a cross-spectral density operator between these two spaces. We prove that, by choosing a characteristic kernel for the mapping, this quantity detects any pairwise dependency between the time series. Then we provide a fast estimator for the Hilbert-Schmidt norm based on the Fast Fourier Trans form. We demonstrate the interest of this approach to quantify non-linear dependencies between frequency bands of simulated signals and intra-cortical neural recordings. |
| External Publication Status: | published |
| Document Type: | Conference-Paper |
| Communicated by: | Heide Klooz |
| Affiliations: | MPI für Intelligente Systeme/Abt. Schölkopf
|
| Identifiers: | URL:http://www.kyb.tuebingen.mpg.de/
LOCALID:7047
DOI:http://dx.doi.org/10.1016/j.irbm.2011.01.001 |
|
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