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估计香农熵:递归图与符号动力学

Estimating the Shannon entropy: recurrence plots versus symbolic dynamics.

作者信息

Letellier Christophe

机构信息

CORIA UMR 6614 - Université de Rouen, Avenue de l'Université, Boîte Postale 12, F-76801 Saint-Etienne du Rouvray cedex, France.

出版信息

Phys Rev Lett. 2006 Jun 30;96(25):254102. doi: 10.1103/PhysRevLett.96.254102. Epub 2006 Jun 29.

Abstract

Recurrence plots were first introduced to quantify the recurrence properties of chaotic dynamics. A few years later, the recurrence quantification analysis was introduced to transform graphical representations into statistical analysis. Among the different measures introduced, a Shannon entropy was found to be correlated with the inverse of the largest Lyapunov exponent. The discrepancy between this and the usual interpretation of a Shannon entropy is solved here by using a new definition--still based on the recurrence plots--and it is verified that this new definition is correlated with the largest Lyapunov exponent, as expected from the Pesin conjecture. A comparison with a Shannon entropy computed from symbolic dynamics is also provided.

摘要

递归图最初被引入以量化混沌动力学的递归特性。几年后,递归量化分析被引入,将图形表示转化为统计分析。在引入的不同度量中,发现香农熵与最大李雅普诺夫指数的倒数相关。这里通过使用一个新定义(仍然基于递归图)解决了这与香农熵通常解释之间的差异,并且验证了这个新定义与最大李雅普诺夫指数相关,正如佩辛猜想所预期的那样。还提供了与从符号动力学计算得到的香农熵的比较。

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