Investigation of coherent modes in the chaotic time series using empirical mode decomposition and discrete wavelet transform analysis

Pankaj Kumar Shaw, Debajyoti Saha, Sabuj Ghosh, M. S. Janaki, A. N.Sekar Iyengar

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

This paper presents a comparative study on the investigation of coherent modes in chaotic time series data based on two techniques: the empirical mode decomposition and the discrete wavelet transform. We have applied these techniques to the different types of chaotic time series data obtained from a glow discharge plasma. The discrete wavelet transform and empirical mode decomposition analysis of the chaotic time series, combined with some simple statistical estimations like variance and correlation coefficient, helps in identifying the presence of coherent modes. We carried out a bicoherency analysis on the coherent modes extracted using empirical mode decomposition to detect the interactions amongst them. It is quite likely that the interactions between the different plasma modes are responsible for such turbulent nonlinear oscillations.

Original languageEnglish
Pages (from-to)285-296
Number of pages12
JournalChaos, Solitons and Fractals
Volume78
DOIs
StatePublished - 2 Sep 2015
Externally publishedYes

Keywords

  • Bicoherency
  • Chaotic time series
  • Coherent mode
  • Empirical mode decomposition
  • Wavelet analysis

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematics (all)
  • Physics and Astronomy (all)
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Investigation of coherent modes in the chaotic time series using empirical mode decomposition and discrete wavelet transform analysis'. Together they form a unique fingerprint.

Cite this