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Analyzing Wind Data with Permutation Entropies and Jensen-Shannon Complexities

This study analyzes wind time series data to compare complexities and entropies between event and stationary periods. Using normalized permutation entropies and Jensen-Shannon complexities, results reveal no definitive trends without filtering. An embedding delay of 10 improves separation between signals; however, differences in complexity and entropy remain subtle. Analysis is conducted on 5000-value portions of the CME time series, providing insights into stochastic behavior across various spatial directions.

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Analyzing Wind Data with Permutation Entropies and Jensen-Shannon Complexities

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  1. WIND time series

  2. WIND time series cont.

  3. WIND time series cont.

  4. CH plan for WIND data, no delay

  5. No delay cont. WIND data- Normalized Permutation Entropies WIND data- Jensen-Shannon Complexities

  6. CH plan for WIND data, standard delay 10

  7. Delay 10 cont. WIND data- Normalized Permutation Entropies WIND data- Jensen-Shannon Complexities

  8. WIND complexities and entropies as functions of τ

  9. WIND complexities and entropies as functions of τ

  10. WIND complexities and entropies as functions of τ

  11. WIND complexities and entropies as functions of τ

  12. WIND complexities and entropies as functions of τ

  13. WIND complexities and entropies as functions of τ

  14. WIND complexities and entropies as functions of τ

  15. WIND complexities and entropies as functions of τ

  16. WIND complexities and entropies as functions of τ

  17. The next 5 slides show the results of analysis run on 5000-value portions of the CME time series corresponding to an event and a more stationary period. • Without any filtering, there is no definitive trend across spatial directions marking one portion as more stochastic (lower C, higher PE) than the other. • When an embedding delay of 10 is used, the stationary and event signals to separate as expected for all spatial directions, with the event slightly more complex and less entropic. Still, the difference is quite small.

  18. CME Event

  19. CME Stationary Period

  20. CH plan for CME event and stationary portions, no delay

  21. CH plan for CME event and stationary portions, delay 10

  22. Unfiltered Delay 10

  23. CH plane with positions of 10 sections of B_x fast stream time series Standard Deviation in PE = 0.006 Standard Deviation in C = 0.007

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