- Title
- Generalized statistical complexity measure: a new tool for dynamical systems
- Creator
- Rosso, O. A.; Larrondo, H. A.; Martin, M. T.; Plastino, A.
- Relation
- 2nd International Conference Net-Works 2008. Modelling and Computation on Complex Networks and Related Topics: Proceedings of the 2nd International Conference Net-Works 2008 (Pamplona, Spain 9-11 June, 2008) p. 149-155
- Relation
- http://www.fisica.unav.es/networks2008
- Publisher
- Universidad Rey Juan Carlos
- Resource Type
- conference paper
- Date
- 2008
- Description
- The generalized Statistical Complexity Measure (SCM) is a functional that characterizes the probability distribution P associated to the time series generated by a dynamical system under study. It quantifies not only randomness but also the presence of correlational structures. In this seminar several fundamental issues are reviewed: a) selection of the information measure I; b) selection of the probability metric space and its corresponding distance D; c) definition of the generalized disequilibrium Q; d) selection of the probability distribution P associated to a dynamical system or time series under study, which in fact! is a basic problem. Here we show that improvements can be expected if the underlying probability distribution is "extracted" by appropriate consideration regarding causal effects in the system's dynamics. Several well-known model-generated time series, usually regarded as being of either stochastic or chaotic nature, are analyzed. The main achievement of this approach is the possibility of clearly distinguish between them in the Entropy-Complexity representation space, something that is rather difficult otherwise.
- Subject
- complexity measure; Statistical Complexity Measure (SCM); time series; probability distribution
- Identifier
- uon:6097
- Identifier
- http://hdl.handle.net/1959.13/802456
- Identifier
- ISBN:9788469138199
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