DocumentCode :
1493214
Title :
Empirical Mode Decomposition for Trivariate Signals
Author :
Rehman, Naveed Ur ; Mandic, Danilo P.
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
Volume :
58
Issue :
3
fYear :
2010
fDate :
3/1/2010 12:00:00 AM
Firstpage :
1059
Lastpage :
1068
Abstract :
An extension of empirical mode decomposition (EMD) is proposed in order to make it suitable for operation on trivariate signals. Estimation of local mean envelope of the input signal, a critical step in EMD, is performed by taking projections along multiple directions in three-dimensional spaces using the rotation property of quaternions. The proposed algorithm thus extracts rotating components embedded within the signal and performs accurate time-frequency analysis, via the Hilbert-Huang transform. Simulations on synthetic trivariate point processes and real-world three-dimensional signals support the analysis.
Keywords :
Hilbert transforms; signal processing; time-frequency analysis; Hilbert-Huang transform; empirical mode decomposition; rotating component extraction; synthetic trivariate point processes; three-dimensional spaces; time-frequency analysis; trivariate signals; Empirical mode decomposition (EMD); Hilbert–Huang spectrum; motion analysis; quaternion algebra; rotation property of quaternions; spiking neurons; time-frequency analysis; trivariate signals; wind modeling;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2009.2033730
Filename :
5280229
Link To Document :
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