Fractal techniques as alternative of Fourier transform for fast search of periodic events in time series

In our day Fourier analysis is commonly used in varies fields, that require information extraction form time series data. However, the Fourier technique has own pros and cons and we can found, that more contemporary approaches can give significant improvements in some cases. We take the example of astrophysical problem and try to resolve it with Fourier analysis in comparison with Fractal analysis. From our results one can find, that in cases of noise extraction Fractal techniques are more efficient and decrease the time of analysis of time series. The proposed approaches can be applied on other fields, to analyze the data sets with dramatically increased volume. (paper)