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A new method to extract coherent bursts from turbulent signals is presented. It uses the wavelet representation which keeps track of both time and scale and thus preserves the temporal structure of the analyzed signal, in contrast to the Fourier representation which scrambles it among the phases of all Fourier coefficients. Using orthogonal wavelets,turbulent signals can be decomposed into coherent and incoherent components, which are orthogonal and whose properties can thus be studied independently. Diagnostics based on the wavelet representation are also introduced to compare the statistical properties of the original signals with their coherent and incoherent components. The wavelet-based extraction method is applied to the saturation current fluctuationsmeasuring the plasma densityfluctuations at the edge of the tokamak Tore Supra, Cadarache, France. This procedure disentangles the coherent bursts, which contain most of the density variance, are intermittent and correlated with non-Gaussian statistics, from the incoherent background fluctuations, which are much weaker, non-intermittent, noise-like and almost decorrelated with quasi-Gaussian statistics. We conjecture that the coherent bursts are responsible for turbulent transport, whereas the remaining incoherent fluctuations only contribute to turbulent diffusion

Extraction of coherent bursts from turbulent edge plasma in magnetic fusion devices using orthogonal wavelets