Recent work on statistical complexity

¨  Detecting and quantifying stochastic and coherence resonances via information-theory complexity measurements

Phys. Rev. E 79, 040106(R) (2009).

O. A. Rosso, C. Masoller

paper in pdf format (143 KB)

 

¨  Detecting and quantifying temporal correlations in stochastic resonance via information theory measures

Special Issue on Stochastic Resonance

O. A. Rosso, C. Masoller

Eur. Phys. J. B 69, 37–43 (2009).

paper in pdf format (331 KB)

 

¨  Quantifying complexity and noise induced order via information theory measures and ordinal patterns symbolic analysis

Talk at IFISC CSIC-UIB, Palma de Mallorca, Spain 17/2/2010 (pdf file 3 Mb, video)

 

¨  Quantifying noise-induced order and noise-induced complexity via information theory measures

Invited Talk in Instabilities and Non-equilibrium Structures XII (on the occasion of the 60th birthday of Pierre Coullet). Viña del Mar, Chile, December 2009 (pdf file 1.3 Mb)

 

¨  Detecting and quantifying noise induced complexity

Invited Talk in XI Latin American Workshop on Nonlinear Phenomena (LANWP09), Buzios, Brazil, October 2009 (pdf file 900 kb)

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Most systems in nature are neither completely ordered nor completely disordered, but something in between. Complexity is characterized by a certain degree of organization, structure, memory, regularity, symmetry, and patterns. Within the framework of Information Theory, the statistical complexity of a system is zero in the extreme situations of complete knowledge (or “perfect order”) and total ignorance (or “complete randomness”). Both are simple situations, as one is fully predictable, and the other one has a simple statistical description. In order to capture the diversity and the rich spectrum of unpredictability occurring between these two extreme situations, many statistical complexity measures have been proposed in the literature, which are useful tools for analyzing high-dimensional dynamics presenting underlying, hidden, or unobserved states that might organize the system’s behavior. Statistical complexity measures are particularly useful when there is no prior knowledge of the hidden dynamics.