This paper proposes a novel method based on the time-frequency coherent representation for quantifying synchronization of multi-channel signals with high resolution. The presented wavelet-coherent technique provides the information regarding both the degree of coherence and the relation of phase difference. The wavelet coherence enables to provide the synchronization and the direction of information flow between two-channel signals. In addition, real EEG recordings are collected based on the cognitive targets during sentences identification and the wavelet coherence is employed for the analysis of the multi-channel EEG signals. It is observed from both the magnitude spectra and phase of the wavelet coherence that there are obvious differenc...
AbstractThe electrophysiological brain activities are nonlinear in nature as measured by Electroence...
A method of single-trial coherence analysis is presented, through the application of continuous mult...
Time-frequency coherence has been widely used to quantify statistical dependencies in bivariate data...
This paper proposes a novel method based on the time-frequency coherent representation for quantifyi...
The synchrony analysis has been used as a tool for the purpose of investigating how the cognitive pr...
The study of the synchronization of EEG signals can help us to understand the underlying cognitive p...
The use of coherence is a wellestablished standard approach for the analysis of biomedical signals....
Abstract—Electroencephalograms (EEGs) provide a noninvasive way of measuring brainwave activity from...
The functional integration between the different parts of the brain is usually quanti¿ed through a m...
Multi-channel recording of electroencephalogram (EEG) provides a measure of spatial-temporal pattern...
A coherence function is a measure of the correlation of two signals and may be used as a measure for...
This paper deals with processing the EEG signals obtained from 16 spatially arranged electrodes to m...
This is the author accepted manuscript. The final version is available from IEEE via the DOI in this...
The study of the correlations that may exist between neurophysiological signals is at the heart of m...
It is hypothesized that the perception of an alternative image in ambiguous figures would be manifes...
AbstractThe electrophysiological brain activities are nonlinear in nature as measured by Electroence...
A method of single-trial coherence analysis is presented, through the application of continuous mult...
Time-frequency coherence has been widely used to quantify statistical dependencies in bivariate data...
This paper proposes a novel method based on the time-frequency coherent representation for quantifyi...
The synchrony analysis has been used as a tool for the purpose of investigating how the cognitive pr...
The study of the synchronization of EEG signals can help us to understand the underlying cognitive p...
The use of coherence is a wellestablished standard approach for the analysis of biomedical signals....
Abstract—Electroencephalograms (EEGs) provide a noninvasive way of measuring brainwave activity from...
The functional integration between the different parts of the brain is usually quanti¿ed through a m...
Multi-channel recording of electroencephalogram (EEG) provides a measure of spatial-temporal pattern...
A coherence function is a measure of the correlation of two signals and may be used as a measure for...
This paper deals with processing the EEG signals obtained from 16 spatially arranged electrodes to m...
This is the author accepted manuscript. The final version is available from IEEE via the DOI in this...
The study of the correlations that may exist between neurophysiological signals is at the heart of m...
It is hypothesized that the perception of an alternative image in ambiguous figures would be manifes...
AbstractThe electrophysiological brain activities are nonlinear in nature as measured by Electroence...
A method of single-trial coherence analysis is presented, through the application of continuous mult...
Time-frequency coherence has been widely used to quantify statistical dependencies in bivariate data...