The Multiple Complex Exponential Model and Its Application to EEG Analysis
Chen Dao · Hangtian yixue yu yixue gongcheng · 1992
A new approach to the analysis of electroencephalogram(EEG) signal, which is based on a multiple complex exponential (MCE) model was introduced. Parameters of the model were estimated by using an algorithm of nonharmonic Fourier expansion (NHFE). The main idea of the algorithm was outlined and the estimated result on a simulated data was presented, and compared with those obtained by the conventional methods of signal analysis. A preliminary work on various application possibilities of MCE model in EEG data analysis was described. The results showed that the parameters of MCE model reflect the essential information contained in an EEG s(?)gment. These parameters will characterize the EEG signal in a more objective way because they are more close to the recent supposition of nonlinear character of the brain's dynamic behaviour.