Robust analysis of dynamical change in scalp electroencephalogram time series

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In recent years, there have been exciting developments in our understanding of brain functions. However, many problems remain unsolved. Among them is dynamical analysis of the brain that is one of the biggest challenges in science. This analysis helps in understanding, predicting and recognizing brain functions. Scalp electroencephalogram (EEG) time series is a non-invasive recording that reflects physiological states of brain activities. Analysis of dynamical change in EEG time series can be extremely useful in many research and diagnosis applications, such as detecting different sleep stages and pathologic states including epileptic seizure, psychiatric disorders, Alzheimer's, Parkinson's and Creutzfeldt-Jakob's diseases.