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Important Extrema of Time Series

Important Extrema of Time Series. Eugene Fink Harith S. Gandhi. Example:. 1, 5, 5, 9, 9, 6, 3, 4, 5, 4, 3, 6, 9, 5, 1, 3, 7, 5, 6, 7. 10. 8. 6. 4. 2. 0. Time series. A time series is a sequence of real values measured at equal intervals. Results. Concept of important extrema.

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Important Extrema of Time Series

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  1. Important Extremaof Time Series Eugene Fink Harith S. Gandhi

  2. Example: 1, 5, 5, 9, 9, 6, 3, 4, 5, 4, 3, 6, 9, 5, 1, 3, 7, 5, 6, 7 10 8 6 4 2 0 Time series A time series is a sequence of real values measured at equal intervals.

  3. Results • Concept of important extrema • Fast identification of these extrema • Applications to compressionand indexing of time series

  4. 6 8 8 2 2 2 6 6 6 Summary We have developed a technique for identifying major minima and maxima in a time series. , and finding the importance of each minimum and maximum.

  5. major minor major minor major Mountain analogy A major peak is the highest point of some mountain, which is much higher than the foot of the mountain.

  6. importance segment Importance of an extremum A local maximum in a time series is “the top of a mountain,” that is, the maximal value in some segment of the series. THE DEFINITION FOR MINIMA IS SYMMETRIC The importance of a maximum is the “mountain height,” that is, its vertical distance from the foot of the mountain.

  7. If a mountain top is a plateau, its endpoints are left and right maxima. strict left right Strict, left, and right extrema If a mountain top is a single point,it is called a strict maximum. THE DEFINITION FOR MINIMA IS SYMMETRIC

  8. Algorithm Fast identification of major extrema. • Determines the importances of all extrema in one pass through a series • Can process a live series in real time, without storing it in memory • Complexity • For an n-point series with m extrema: • Running time is O(n) • Required memory is O(m)

  9. Demo

  10. Applications • Compression of a time series by extracting its major extrema • Indexing of a series and retrieval of segments similar to a given pattern

  11. 8 6 8 6 6 6 compressed Lossy compression Select a given percentage of the most important extrema, along with the two endpoints, and discard all other points. initial

  12. Lossy compression Select a given percentage of the most important extrema, along with the two endpoints, and discard all other points. • Advantages • Very fast compression procedure • Preserving major minima and maxima • Real-time compression of live series

  13. 8 6 importance 4 2 0 place in the series Indexing of extrema We index extrema of a series by importance and place in the series. 8 6 8 2 2 2 6 6 6

  14. Indexing of extrema We index extrema of a series by their importance and place in the series. We use a range tree, which supports indexing of points by two coordinates. 8 6 importance 4 2 0 place in the series

  15. segment Retrieval We can quickly look up a compressed version of any given segment, and then retrieve more and more of its details. 8 6 importance 4 2 0 place in the series

  16. Retrieval We can quickly look up a compressed version of any given segment, and then retrieve more and more of its details. 8 6 importance 4 2 0 place in the series segment

  17. Retrieval We can quickly look up a compressed version of any given segment, and then retrieve more and more of its details. This procedure supports fast search for segments similar to a given pattern. Pattern Series

  18. Important extrema in the first and second derivatives of a series Extensions • Generalized vertical distancebetween points of a series ...

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