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  2. Dynamic time warping - Wikipedia

    en.wikipedia.org/wiki/Dynamic_time_warping

    In time series analysis, dynamic time warping (DTW) is an algorithm for measuring similarity between two temporal sequences, which may vary in speed. For instance, similarities in walking could be detected using DTW, even if one person was walking faster than the other, or if there were accelerations and decelerations during the course of an ...

  3. Time Warp Edit Distance - Wikipedia

    en.wikipedia.org/wiki/Time_Warp_Edit_Distance

    In comparison to other distance measures, (e.g. DTW (dynamic time warping) or LCS (longest common subsequence problem)), TWED is a metric. Its computational time complexity is O ( n 2 ) {\displaystyle O(n^{2})} , but can be drastically reduced in some specific situations by using a corridor to reduce the search space.

  4. Graphical time warping - Wikipedia

    en.wikipedia.org/wiki/Graphical_time_warping

    As each GTW subgraph is dual to a DTW graph, the maximum flow within each GTW subgraph can be solved in linear time through dynamic programming. In many applications, a rough approximate solution of the warping paths can be estimated, which could serve as the initialization to accelerate the solving process.

  5. Category:Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Category:Dynamic_programming

    18 languages. العربية ... Pages in category "Dynamic programming" The following 48 pages are in this category, out of 48 total. ... Graphical time warping; H.

  6. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    In terms of mathematical optimization, dynamic programming usually refers to simplifying a decision by breaking it down into a sequence of decision steps over time. This is done by defining a sequence of value functions V 1 , V 2 , ..., V n taking y as an argument representing the state of the system at times i from 1 to n .

  7. Functional data analysis - Wikipedia

    en.wikipedia.org/wiki/Functional_data_analysis

    Functional data analysis (FDA) is a branch of statistics that analyses data providing information about curves, surfaces or anything else varying over a continuum. In its most general form, under an FDA framework, each sample element of functional data is considered to be a random function.

  8. Held–Karp algorithm - Wikipedia

    en.wikipedia.org/wiki/Held–Karp_algorithm

    The Held–Karp algorithm, also called the Bellman–Held–Karp algorithm, is a dynamic programming algorithm proposed in 1962 independently by Bellman [1] and by Held and Karp [2] to solve the traveling salesman problem (TSP), in which the input is a distance matrix between a set of cities, and the goal is to find a minimum-length tour that visits each city exactly once before returning to ...

  9. Needleman–Wunsch algorithm - Wikipedia

    en.wikipedia.org/wiki/Needleman–Wunsch_algorithm

    A better dynamic programming algorithm with quadratic running time for the same problem (no gap penalty) was introduced later [5] by David Sankoff in 1972. Similar quadratic-time algorithms were discovered independently by T. K. Vintsyuk [ 6 ] in 1968 for speech processing ( "time warping" ), and by Robert A. Wagner and Michael J. Fischer [ 7 ...