Inter subject inconsistency measures of EEG data on the basis of correlation dimension
نویسندگان
چکیده
Careful attentions must be required for analyzing high dimensional Electroencephalographic (EEG) signals. There have many discrepancy or linearity when signals are recorded at different stimulations for a subject. When these signals are collected for different trails of a subject, there have similarity also. In this paper, we want to measure this correspondence on the basis of correlation aspect. For this reason, we incorporate neural network with canonical correlation analysis (CCA) as a linear and nonlinear function. The effectiveness of the network capabilities is tested with a sine-cosine reference signals. KeywordsElectroencephalographic (EEG); canonical correlation analysis (CCA); neutral network; inconsistency
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