Enhancing weak signal components in time-frequency distributions by wavelet pre-processing

Most real world signals consist of stronger low frequency components than high frequency ones. However, in many cases, high frequency components with small amplitude values represent the components of interest. Although time-frequency distributions (TFDs) have been commonly utilized to analyze such signals, the masking effect of large amplitude components, which severely reduce the sensitivity of TFDs, has been a significant problem. In this work we present a new method to pre-condition the input data using wavelet analysis and synthesis procedures before computing the TFD. This method attenuates interfering components in the TFD so that the masking effect is greatly reduced. EEG data are used to demonstrate the approach