Study of nonlinear oscillations in a glow discharge plasma using empirical mode decomposition and Hilbert Huang transform

Abstract

Hilbert Huang transform (HHT) based time series analysis was carried out on nonlinear floating potential fluctuations obtained from hollow cathode glow discharge plasma in the presence of anode glow. HHT was used to obtain contour plots and the presence of nonlinearity was studied. Frequency shift with time, which is a typical nonlinear behaviour, was detected from the contour plots. Various plasma parameters were measured and the concepts of correlation coefficients and the physical contribution of each intrinsic mode function have been discussed. Physically important quantities such as instantaneous energy and their uses in studying physical phenomena such as intermittency and non-stationary data have also been discussed. V C 2013 American Institute of Physics. [http://dx.

Hurst Exponent-Based Nonlinear Analysis for the Identification of Arrhythmia-Affected Cardiac Systems

“…The correlation coefficient between the IMFs and the original signal were calculated to identify the IMFs with the real components of the original signal [22,23]. The correlation coefficients ( 𝐶 𝑥𝑐 𝑁 ) were calculated using the following equations [24,25]:…”

Chaotic behavior and fractals discovered in the time evolution of discharge current at atmospheric pressure

“…For several decades, nonlinear phenomena such as chaos and fractals have attracted significant attention globally in all fields of science, and their concepts are considered common and beneficial according to the investigation of the structures caused by discharge phenomena. Many different varieties of experimental studies on nonlinear behaviors have been accomplished in plasmas produced by discharges, [1][2][3][4][5][6] observations of chaos, [7][8][9][10][11][12][13][14][15][16][17][18][19] control of chaos, [20][21][22] synchronization of coupled oscillators, [23][24][25][26][27][28] and calculations of fractal dimensions. [29][30][31][32][33][34][35] The properties concerning chaos and fractals can be characterized quantitatively, for example, from experimental data using the calculation of the Lyapunov exponent 36 and the correlation dimension, 37 respectively.…”