Permutation entropy: a natural complexity measure for time series
We introduce complexity parameters for time series based on comparison of neighboring values. The definition directly applies to arbitrary real-world data. For some well-known chaotic dynamical systems it is shown that our complexity behaves similar to Lyapunov exponents, and is particularly useful...
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| Veröffentlicht in: | Physical review letters 2002-04, Vol.88 (17), p.174102-174102, Article 174102 |
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| container_end_page | 174102 |
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| container_issue | 17 |
| container_start_page | 174102 |
| container_title | Physical review letters |
| container_volume | 88 |
| creator | Bandt, Christoph Pompe, Bernd |
| description | We introduce complexity parameters for time series based on comparison of neighboring values. The definition directly applies to arbitrary real-world data. For some well-known chaotic dynamical systems it is shown that our complexity behaves similar to Lyapunov exponents, and is particularly useful in the presence of dynamical or observational noise. The advantages of our method are its simplicity, extremely fast calculation, robustness, and invariance with respect to nonlinear monotonous transformations. |
| doi_str_mv | 10.1103/physrevlett.88.174102 |
| format | Article |
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| ispartof | Physical review letters, 2002-04, Vol.88 (17), p.174102-174102, Article 174102 |
| issn | 0031-9007 1079-7114 |
| language | eng |
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| source | American Physical Society Journals |
| title | Permutation entropy: a natural complexity measure for time series |
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