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Efficiently Measuring Complexity on the Basis of Real-World Data.
- Source :
- Entropy; Oct2013, Vol. 15 Issue 10, p4392-4415, 24p
- Publication Year :
- 2013
-
Abstract
- 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- PERMUTATION groups
ENTROPY
TIME series analysis
DATA analysis
THERMODYNAMICS
Subjects
Details
- Language :
- English
- ISSN :
- 10994300
- Volume :
- 15
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- Entropy
- Publication Type :
- Academic Journal
- Accession number :
- 91719483
- Full Text :
- https://doi.org/10.3390/e15104392