Efficiently Measuring Complexity on the Basis of Real-World Data

Entropy

Valentina A. Unakafova¹ 

[1] Institute of Mathematics, University of Lübeck, Lübeck D-23562, Germany; E-Mail:

关键词: permutation entropy;    ordinal patterns;    efficient computing;    complexity;   

DOI  :  10.3390/e15104392

来源: mdpi

【 摘 要 】

Permutation entropy, introduced by Bandt and Pompe, is a conceptually simple and well-interpretable measure of time series complexity. In this paper, we propose efficient methods for computing it and related ordinal-patterns-based characteristics. The methods are based on precomputing values of successive ordinal patterns of order d, considering the fact that they are “overlapped” in d points, and on precomputing successive values of the permutation entropy related to “overlapping” successive time-windows. The proposed methods allow for measurement of the complexity of very large datasets in real-time.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.