论文标题

朝着动态时翘曲距离的有效交互式计算

Towards Efficient Interactive Computation of Dynamic Time Warping Distance

论文作者

Nishi, Akihiro, Nakashima, Yuto, Inenaga, Shunsuke, Bannai, Hideo, Takeda, Masayuki

论文摘要

动态时间翘曲(DTW)是一种广泛使用的方法,它使我们能够有效地比较两个时间序列的速度。给定两个字符串$ a $和$ b $的各个长度$ m $和$ n $,有一种基本的动态编程算法,可以计算$ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a $ a和$ b $的dtw距离,并在$θ(mn)$ $时间和空间中进行最佳对齐。在本文中,我们解决了动态字符串的DTW距离的交互式计算问题,该问题表示为$ \ mathrm {d^2tw} $,其中可以在字符串的任意位置执行字符的编辑操作(插入,删除,替换)。让$ m $和$ n $是$ a $ a $ a $ a $ a $ a $ a和$ b $的运行长度编码的尺寸。 We present an algorithm for $\mathrm{D^2TW}$ that occupies $Θ(mN+nM)$ space and uses $O(m+n+\#_{\mathrm{chg}}) \subseteq O(mN + nM)$ time to update a compact differential representation $\mathit{DS}$ of the DP table per edit operation, where $ \ #_ {\ Mathrm {Chg}} $表示$ \ Mathit {ds} $中的单元格数,其值在编辑操作后会更改。我们的方法至少与Froese等人最近提出的算法一样有效。以$θ(mn + nm)$时间运行,并且当$ \ #_ {\ mathrm {chg}} $时,$更快的速度小于$ O(mn + nm)$,正如我们的初步实验所暗示的那样,在大多数情况下,这可能是这种情况。

The dynamic time warping (DTW) is a widely-used method that allows us to efficiently compare two time series that can vary in speed. Given two strings $A$ and $B$ of respective lengths $m$ and $n$, there is a fundamental dynamic programming algorithm that computes the DTW distance for $A$ and $B$ together with an optimal alignment in $Θ(mn)$ time and space. In this paper, we tackle the problem of interactive computation of the DTW distance for dynamic strings, denoted $\mathrm{D^2TW}$, where character-wise edit operation (insertion, deletion, substitution) can be performed at an arbitrary position of the strings. Let $M$ and $N$ be the sizes of the run-length encoding (RLE) of $A$ and $B$, respectively. We present an algorithm for $\mathrm{D^2TW}$ that occupies $Θ(mN+nM)$ space and uses $O(m+n+\#_{\mathrm{chg}}) \subseteq O(mN + nM)$ time to update a compact differential representation $\mathit{DS}$ of the DP table per edit operation, where $\#_{\mathrm{chg}}$ denotes the number of cells in $\mathit{DS}$ whose values change after the edit operation. Our method is at least as efficient as the algorithm recently proposed by Froese et al. running in $Θ(mN + nM)$ time, and is faster when $\#_{\mathrm{chg}}$ is smaller than $O(mN + nM)$ which, as our preliminary experiments suggest, is likely to be the case in the majority of instances.

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