On the Phase Coupling of Two Components Mixing in Empirical Mode Decomposition

Journal article


Laszuk, D, Cadenas, O. and Nasuto, Slawomir J. (2016). On the Phase Coupling of Two Components Mixing in Empirical Mode Decomposition. Advances in Data Science and Adaptive Analysis. 8 (1). https://doi.org/10.1142/S2424922X16500042
AuthorsLaszuk, D, Cadenas, O. and Nasuto, Slawomir J.
Abstract

This paper investigates frequency mixing effect of empirical mode decomposition (EMD) and explores whether it can be explained by simple phase coupling between components of the input signal. The input is assumed to be a linear combination of harmonic oscillators. The hypothesis was tested assuming that phases of input signals’ components would couple according to Kuramoto’s model. Using a Kuramoto’s model with as many oscillators as the number of intrinsic mode functions (result of EMD), the model’s parameters were adjusted by a particle swarm optimization (PSO) method. The results show that our hypothesis is plausible, however, a different coupling mechanism than the simple sine-coupling Kuramoto’s model are likely to give better results.

KeywordsEmpirical mode decomposition; instanteneous frequency; Kuramoto model; Particle swarm optimization
Year2016
JournalAdvances in Data Science and Adaptive Analysis
Journal citation8 (1)
PublisherWorld Scientific Publishing
ISSN2424-922X, 2424-9238
Digital Object Identifier (DOI)https://doi.org/10.1142/S2424922X16500042
Publication dates
Print03 Aug 2016
Publication process dates
Deposited08 May 2017
Accepted21 Apr 2016
Accepted author manuscript
License
File Access Level
Open
Permalink -

https://openresearch.lsbu.ac.uk/item/872y2

Download files


Accepted author manuscript
ws-aada.pdf
License: CC BY 4.0
File access level: Open

  • 84
    total views
  • 184
    total downloads
  • 0
    views this month
  • 0
    downloads this month

Export as

Related outputs

Preprocessing 2D data for fast convex hull computations
Cadenas, O and Megson, GM (2019). Preprocessing 2D data for fast convex hull computations. PLoS ONE. 14 (2), p. e0212189. https://doi.org/10.1371/journal.pone.0212189
KurSL: Model of anharmonic coupled oscillations based on Kuramoto coupling and Sturm-Liouville problem
Cadenas, O, Laszuk, D and Slawomir, N (2018). KurSL: Model of anharmonic coupled oscillations based on Kuramoto coupling and Sturm-Liouville problem. Advances in Data Science and Adaptive Analysis. 10 (02). https://doi.org/10.1142/S2424922X18400028
Running Median Algorithm and Implementation for Integer Streaming Applications
Cadenas, O and Megson, GM (2018). Running Median Algorithm and Implementation for Integer Streaming Applications. IEEE Embedded Systems Letters. 11 (2), pp. 58-61. https://doi.org/10.1109/LES.2018.2868409
Rapid preconditioning of data for accelerating convex hull algorithms
Cadenas, O and Megson, G (2014). Rapid preconditioning of data for accelerating convex hull algorithms. Electronics Letters. 50 (4), pp. 270-272. https://doi.org/10.1049/el.2013.3507
Virtualization for cost-effective teaching of assembly language
Cadenas, O, Sherratt, S, Howlett, D, Guy, C and Lundqvist, K (2015). Virtualization for cost-effective teaching of assembly language. IEEE Transactions on Education. 58 (4), pp. 282-288. https://doi.org/10.1109/TE.2015.2405895
Median architecture by accumulative parallel counters
Cadenas, O, Megson, G and Sherratt, S (2015). Median architecture by accumulative parallel counters. IEEE Transactions on Circuits and Systems II: Express Briefs. 62 (7), pp. 661-665. https://doi.org/10.1109/TCSII.2015.2415655
Pipelined median architecture
Cadenas, O (2015). Pipelined median architecture. Electronics Letters. 51 (24), pp. 1999-2001. https://doi.org/10.1049/el.2015.1898
Preconditioning 2D integer data for fast convex hull computations
Cadenas, O, Megson, G.M. and Luengo Hendriks, C.L. (2016). Preconditioning 2D integer data for fast convex hull computations. PLoS ONE. 11 (3). https://doi.org/10.1371/journal.pone.0149860
EMD performance comparison: single vs double floating points
Laszuk, D, Cadenas, O. and Nasuto, J (2016). EMD performance comparison: single vs double floating points. International journal of signal processing systems. 4 (4), pp. 349-353. https://doi.org/10.18178/ijsps.4.4.349-353