Ya.A. Turovsky, S.D. Kurgalin, A.G. Semenov

The typologization power indicator of the electroencephalograms (EEG) locals maximums wavelet coefficients matrix was hold. The brain activity, which reflected in the locals powers maximums of the wavelets coefficients matrix dynamics, is important for brain activity investigation. The time dynamic of the locals powers maximums, which forming locals maximums series (LMS) W 2 in (a,b) space was analyzed. The algorithm of the LMS averaging in power data was offer, as LMS averaging in frequency data analog. The three methods of the averaging, for physiological interpretation LMS was present. The five types of the locals maximums dynamics were detected. The charting of the series of the local maximum types distribution were realized. In the investigation was detected, what «stable» type of the LMS and theirs value associated with diapasons of the value starts and ends points LSM. In this diapasons of the power dynamics the value was detected as significant. This method help investigated the association the powers value and dynamics LSM in different brain locus and in the rest and mental activity. The parts, of the EEG-signals associated with nerve centre activity may be detected with the scalogramms help. The algorithm, which used in this investigations may be employ for analysis not only EEG-signals, they may be employ for analysis electrocardiogram, heart rate variability, blood pressure monitoring and so on. This method will help to detect new physiological phenomenon in signals.