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  Finding dependencies between frequencies with the kernel cross-spectral density

Besserve, M., Janzing, D., Logothetis, N., & Schölkopf, B. (2011). Finding dependencies between frequencies with the kernel cross-spectral density. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011) (pp. 2080-2083). Piscataway, NJ, USA: IEEE.

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Besserve, M1, 2, 3, Author           
Janzing, D1, 3, Author           
Logothetis, NK2, 3, Author           
Schölkopf, B1, 3, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: 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.

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 Dates: 2011-07
 Publication Status: Issued
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 Identifiers: DOI: 10.1109/ICASSP.2011.5946735
BibTex Citekey: 7047
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Title: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)
Place of Event: Praha, Czech Republic
Start-/End Date: 2011-05-22 - 2011-05-27

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Title: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 2080 - 2083 Identifier: ISBN: 978-1-4577-0538-0