Physics of auroral phenomena : proceedings of the 36th Annual seminar, Apatity, 26 February – 01 March, 2013 / [ed. board: A. G. Yahnin, A. A. Mochalov]. - Апатиты : Издательство Кольского научного центра РАН, 2013. - 215 с. : ил., табл.

S.E. Revunov et al. obtain the wavelet-skeleton spectra makes it easier for an objective comparison of the spectrums. So much for the successful evaluation o f consistency spectral pattern should contain only the key features that reflect the sets of wavelet-skeleton spectrums. In a study of the basic wavelet function is selected Daubechies o f the fourth order. Scale wavelet transform coefficients in the frequency range considered in the maximum period o f 5, 10, 15, 30, 60, 90, 120, 180, 240, 300 and 360 min. The resulting pattern o f wavelet transforms processed by the search algorithm to represent the local maxima of the results o f the calculation in the form of wavelet-skeleton spectrum. The resulting matrix skeleton range o f each parameter o f each event is a matrix with elements 0 and 1, where 1 corresponds to the local maximum at a particular frequency at a particular time. Then, by plotting each point of skeleton exactly corresponds to one pixel in the image. Such an approach to the construction of wavelet-skeleton spectral sets for the purposes of calculating the objective characteristics of the spectra comparison o f pairs of skeleton was used. 3. The algorithm of the comparative analysis of skeleton spectrums In our paper, a search o f synchronization moments fluctuations of horizontal component o f the geomagnetic field over the entire latitudinal range of the considered magnetic stations during the five days before an intense flare was made. The presence of regions synchronization during this time may serve as a indication of flare. Interpretation of the results of the comparative analysis of the primary skeleton sets calculated in the work on the basis of data from the observatories participating in the experiment. It is complicated by a long duration o f the observed range, which prevents finding moments of synchronization of fluctuations. To solve this problem, after calculating the skeleton of the spectra and their comparison the overall picture with a Gaussian filter with a high contrast ratio, which contributes to visualize the degree of correlation of the vibrational modes at different observatories was treated. Fig. 1 The total amount o f the normalized histogram moments synchronization o f oscillations at all stations for all the analyzed flares by period 180 min. On the horizontal axis represents time in days before the flare of class X. The moment of registration o f flare is located at left. To avoid subjective judgments obtained in the analysis of skeleton sets required numerical evaluation. To do this, the study proposed an original algorithm for comparative analysis o f the spectra with the calculation of skeletons objective characteristics registering moments o f synchronization o f oscillatory modes at all stations. Earlier, it was noted that the construction of graphs skeleton every point exactly corresponds to one pixel in the image. This method for constructing the wavelet-skeleton spectral sets suitable for the purposes of calculating the objective characteristics o f the spectra comparison o f pairs of skeleton. Further processing o f the data will explain step by step. 1. We calculate the wavelet-skeleton patterns o f the horizontal component of the geomagnetic field in the selected frequency bands registered for five days before to each analysis flare, which is then stored in the form o f matrices with 1 and 0 elements. 2. The resulting 6 matrices (one on each station) with single (skeleton point) and zero (no point) elements for a specific frequency range used in the operation o f column subtraction with record values o f the difference in absolute value. 3. The picture with markers, marking the moments o f complete synchronization of oscillations at the stations, a Gaussian filter with high contrast is treated. At this stage the individual, not grouped markers will be screened out (blown out), and the existing group of markers will be highlighted. The non-zero values o f the differences are not considered at all, which allows to reduce the dimension o f the problem to a minimum. As a result, the intensity of diffuse objects in the picture with markers shows the density o f synchronization. 56