Complex AM signal model for non-stationary signals
Signal Processing
Complex FM signal model for non-stationary signals
Signal Processing
Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
The use of a filter bank and the Wigner-Ville distribution fortime-frequency representation
IEEE Transactions on Signal Processing
The application of the Hilbert spectrum to the analysis of electromyographic signals
Information Sciences: an International Journal
Discrimination between ictal and seizure-free EEG signals using empirical mode decomposition
Research Letters in Signal Processing
A hybrid time-frequency method based on improved Morlet wavelet and auto terms window
Expert Systems with Applications: An International Journal
Removing interference components in time-frequency representations using morphological operators
Journal of Visual Communication and Image Representation
Adaptive windowed cross Wigner-Ville distribution as an optimum phase estimator for PSK signals
Digital Signal Processing
International Journal of Data Analysis Techniques and Strategies
Automatic classification of sleep stages based on the time-frequency image of EEG signals
Computer Methods and Programs in Biomedicine
Hi-index | 0.01 |
A new method for time-frequency representation (TFR) of a signal, which combines the Fourier-Bessel (FB) expansion and the Wigner-Ville distribution (WVD) has been presented in this paper. The FB expansion decomposes a multicomponent signal into a number of monocomponent signals, and then the WVD technique is applied on each component of the composite signal to analyze its time-frequency distribution (TFD). The simulation results show that the proposed technique based on the FB decomposition is a powerful tool for analyzing multicomponent nonstationary signals and for obtaining the TFR of the signal without introducing cross terms.