Research on Dynamical Evolution Process of EEG Signal
Jiang Hua Hu · Jisuanji gongcheng · 2013
The research of Electroencephalogram(EEG) signals is an important means of diagnosis of brain disease.Taking EEG signals of epilepsy for example,for the complexity of the seizures,the evolution process is studied.It uses of the method of the Proper Orthogonal Decomposition(POD) to decompose and compress the EEG signals,chooses multiple variables to reflect electrical pathological characteristic of EEG brain,and uses the improved method of Fisher discrimination to classify the signal,determines the key points of the dynamic evolvement process of EEG signals.Experimental results show that combined with POD decomposition and Fisher discriminant method,it can not only reduce the workload of data analysis,and can effectively distinguish the EEG signal dynamic evolution process.