articleProceedings of the Royal Society A Mathematical Physical and Engineering SciencesDec 23, 2009Closed access
Multivariate empirical mode decomposition
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Abstract
Despite empirical mode decomposition (EMD) becoming a de facto standard for time-frequency analysis of nonlinear and non-stationary signals, its multivariate extensions are only emerging; yet, they are a prerequisite for direct multichannel data analysis. An important step in this direction is the computation of the local mean, as the concept of local extrema is not well defined for multivariate signals. To this end, we propose to use real-valued projections along multiple directions on hyperspheres ( n -spheres) in order to calculate the envelopes and the local mean of multivariate signals, leading to multivariate extension of EMD. To generate a suitable set of direction vectors, unit hyperspheres ( n…
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Topics
Keywords
- Multivariate statistics
- Maxima and minima
- Computation
- Mathematics
- Monte Carlo method
- Nonlinear system
- Algorithm
- Hilbert–Huang transform
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