ECG signals can be identified using mean power of wavelet-packet coefficients and entropy of wavelet coefficients. These parameters are of diagnostic value for patient cardiosignal comparison.Frequency-amplitude parameters of ECG signals are rather sophisticated. Analysis of ECG signals requires high frequency and amplitude resolution. This is required to localize low-frequency and high-frequency components.There are two methodological approaches to analysis of this problem.The first approach is preliminary division of nonsta-tionary signal into time segments (frames). The time segments are quasi-stationary portions with invariable statistics (almost invariable) within a given time range and further parametric analysis (autoregression model AR [1] or sliding mean model [2] or local Fourier transform). Quasi-stationary portions should be detected with minimal delay. Series statistical analysis methods are used to detect fast discoordination moments [3,4].
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