AI Article Synopsis
- The study focuses on analyzing the complex behavior of glow discharge plasma using wavelet transform, which helps to effectively capture varying patterns over different time scales.
- The continuous Morlet wavelet is particularly useful for identifying periodic changes and features like turbulence, while the discrete Daubechies wavelet helps in removing trends to uncover multi-fractal characteristics.
- Various methods, including wavelet-based detrended fluctuation analysis, Fourier methods, and rescale range analysis, are employed to estimate important scaling factors that describe the plasma's dynamics.
Article Abstract
The multiscale dynamics of glow discharge plasma is analysed through wavelet transform, whose scale dependent variable window size aptly captures both transients and non-stationary periodic behavior. The optimal time-frequency localization ability of the continuous Morlet wavelet is found to identify the scale dependent periodic modulations efficiently, as also the emergence of neutral turbulence and dissipation, whereas the discrete Daubechies basis set has been used for detrending the temporal behavior to reveal the multi-fractality of the underlying dynamics. The scaling exponents and the Hurst exponent have been estimated through wavelet based detrended fluctuation analysis, and also Fourier methods and rescale range analysis.
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| http://dx.doi.org/10.1063/1.4903332 | DOI Listing |
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