Journal
PHYSICAL REVIEW E
Volume 85, Issue 4, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.85.046205
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Funding
- Wellcome Trust (UK)
- EPSRC
- EU NEST
- Economic and Social Research Council [ES/G03690X/1] Funding Source: researchfish
- Engineering and Physical Sciences Research Council [EP/I00999X/1] Funding Source: researchfish
- Natural Environment Research Council [NE/I011889/1] Funding Source: researchfish
- EPSRC [EP/I00999X/1] Funding Source: UKRI
- ESRC [ES/G03690X/1] Funding Source: UKRI
- NERC [NE/I011889/1] Funding Source: UKRI
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We present a method for the testing of significance when evaluating the coherence of two oscillatory time series that may have variable amplitude and frequency. It is based on evaluating the self-correlations of the time series. We demonstrate our approach by the application of wavelet-based coherence measures to artificial and physiological examples. Because coherence measures of this kind are strongly biased by the spectral characteristics of the time series, we evaluate significance by estimation of the characteristics of the distribution of values that may occur due to chance associations in the data. The expectation value and standard deviation of this distribution are shown to depend on the autocorrelations and higher order statistics of the data. Where the coherence value falls outside this distribution, we may conclude that there is a causal relationship between the signals regardless of their spectral similarities or differences.
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