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The estimation of the second-order complexity of these time series shows that the second-order complexities do reflect the degree of nonstationarity and thus can be considered as its indicator. It is also shown that the second-order complexities of the EEG signals from subjects doing mental arithmetic are significantly higher than those from subjects in deep sleep or resting with eyes closed. <\/jats:p>","DOI":"10.1142\/s021812740401093x","type":"journal-article","created":{"date-parts":[[2004,9,17]],"date-time":"2004-09-17T06:44:54Z","timestamp":1095403494000},"page":"2979-2990","source":"Crossref","is-referenced-by-count":6,"title":["HIGHER ORDER COMPLEXITY OF TIME SERIES"],"prefix":"10.1142","volume":"14","author":[{"given":"FANJI","family":"GU","sequence":"first","affiliation":[{"name":"Liren Lab., School of Life Sciences, Fudan University, Brain Science Research Center, Institute of Brain Science, Fudan University, Shanghai 200433, P. R. 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