{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T16:31:45Z","timestamp":1759941105863},"reference-count":18,"publisher":"World Scientific Pub Co Pte Lt","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Bifurcation Chaos"],"published-print":{"date-parts":[[2005,5]]},"abstract":"<jats:p> In this contribution, eleven different measures of the complexity of multichannel EEGs are described, and their effectiveness in discriminating between two behavioral conditions (eyes open resting versus eyes closed resting) is compared. Ten of the methods were variants of the algorithmic complexity and the covariance complexity. The eleventh measure was a multivariate complexity measure proposed by Tononi and Edelman. The most significant between-condition change was observed with Tononi\u2013Edelman complexity which decreased in the eyes open condition. Of the algorithmic complexity measures tested, the binary Lempel\u2013Ziv complexity and the binary Lempel\u2013Ziv redundancy of the first principal component following mean normalization and normalization against the standard deviation gave the most significant between-group discrimination. A time-dependent generalization of the covariance complexity that can be applied to nonstationary multichannel signals is also described. <\/jats:p>","DOI":"10.1142\/s0218127405012764","type":"journal-article","created":{"date-parts":[[2005,7,7]],"date-time":"2005-07-07T13:48:02Z","timestamp":1120744082000},"page":"1737-1744","source":"Crossref","is-referenced-by-count":11,"title":["QUANTITATIVE CHARACTERIZATION OF THE COMPLEXITY OF MULTICHANNEL HUMAN EEGS"],"prefix":"10.1142","volume":"15","author":[{"given":"P. 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