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A statistical measure of complexity with nonextensive entropy

Author

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  • Yamano, Takuya

Abstract

A statistical measure of complexity utilising the concept of entropy or information is proposed. Our way in this study is to use a nonextensive entropy instead of an extensive (additive) Shannon entropy in the definition, but can be characterised as a difference between the qth-order Rényi entropy and the second one. Furthermore, we devise a conditional, joint, and mutual complexity measure as a coherent possibility. The behavior of the measure for the logistic map shows that it is more sensitive to nonextensivity at the transition point ac∼3.8284… than any other values when 0

Suggested Citation

  • Yamano, Takuya, 2004. "A statistical measure of complexity with nonextensive entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 131-137.
    • Handle: RePEc:eee:phsmap:v:340:y:2004:i:1:p:131-137
    DOI: 10.1016/j.physa.2004.03.087
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    Cited by:

    1. Rajaram, R. & Castellani, B., 2016. "An entropy based measure for comparing distributions of complexity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 35-43.
    2. Contreras-Reyes, Javier E., 2015. "Rényi entropy and complexity measure for skew-gaussian distributions and related families," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 84-91.

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