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Using the Markovian method, we study the stochastic nature of electrical discharge current ﬂuctuations in the Helium plasma. Sinusoidal trends are extracted from the
data set by the Fourier-Detrended Fluctuation analysis and consequently cleaned data is
retrieved. We determine the Markov time scale of the detrended data set by using likelihood analysis. We also estimate the Kramers-Moyals coefﬁcients of the discharge current
ﬂuctuations and derive the corresponding Fokker-Planck equation. In addition, the obtained
Langevin equation enables us to reconstruct discharge time series with similar statistical
properties compared with the observed in the experiment. We also provide an exact decomposition of temporal correlation function by using Kramers-Moyals coefﬁcients. We
show that for the stationary time series, the two point temporal correlation function has
an exponential decaying behavior with a characteristic correlation time scale. Our results
conﬁrm that, there is no deﬁnite relation between correlation and Markov time scales. How ever both of them behave as monotonic increasing function of discharge current intensity.
Finally to complete our analysis, the multifractal behavior of reconstructed time series using its Keramers-Moyals coefﬁcients and original data set are investigated. Extended self
similarity analysis demonstrates that ﬂuctuations in our experimental setup deviates from
Kolmogorov (K41) theory for fully developed turbulence regime.
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