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We propose a recurrence time based approach to characterize brain electrical activity. Unlike many other nonlinear methods, the proposed approach does not require that the EEG data be either chaotic or stationary. It works well on clean signals and is robust to noise. Furthermore, it only contains a few parameters that are largely signal-independent, and hence, is very easy to use. By analyzing single...
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