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EEG time-frequency analysis based on the improved S-transform

机译:基于改进S变换的脑电时频分析

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S-transform, which is a combination of short-time Fourier transform and wavelet transform, has attract intensive interest in recent years as an important tool to investigate non-stationary signal time-frequency distribution. S transform can be self-improved by the EEG characteristics to select a suitable mother wavelet. The improved S-transform will be used to analyze the time-frequency of the EEG characters. A comparison among the Short-time Fourier transform, wavelet transformation and the improved S-transform indicates that improved S-transform gives the best energy distribution in the time-frequency filed.
机译:S变换是短时傅立叶变换和小波变换的结合,近年来作为研究非平稳信号时频分布的重要工具,引起了人们的广泛关注。 S变换可以通过EEG特性进行自我改进,以选择合适的母小波。改进的S变换将用于分析EEG字符的时频。短时傅立叶变换,小波变换和改进的S变换之间的比较表明,改进的S变换在时频场中提供了最佳的能量分布。

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