期刊
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
卷 20, 期 3, 页码 775-785出版社
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S021812741002606X
关键词
Complexity measure
A generalized Statistical Complexity Measure (SCM) is a functional that characterizes the probability distribution P associated to the time series generated by a given dynamical system. It quantifies not only randomness but also the presence of correlational structures. We review here several fundamental issues in such a respect, namely, ( a) the selection of the information measure I; (b) the choice of the probability metric space and associated distance D; ( c) the question of de. ning the so-called generalized disequilibrium Q; (d) the adequate way of picking up the probability distribution P associated to a dynamical system or time series under study, which is indeed a fundamental problem. In this communication we show (point d) that sensible improvements in the final results can be expected if the underlying probability distribution is extracted via appropriate consideration regarding causal effects in the system's dynamics.
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