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          Institute: MPI für Intelligente Systeme (ehemals Max-Planck-Institut für Metallforschung)     Collection: Abt. Schölkopf (Empirical Inference)     Display Documents



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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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