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The Dynamic Time Warping Distance Measure as Q U BO Formulation

机译:动态时间翘曲距离度量为Q U BO公式

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Dynamic Time Warping (DTW) is a representative of a distance measure that is able to calculate the distance between two time series. It is often used for the recognition of handwriting or spoken language. The metaheuristic Quantum Annealing (QA) can be used to solve combinatorial optimization problems. Similar to Simulated Annealing it seeks to find a global minimum of a target function. In order to use specialized QA hardware, the problem to be optimized needs to be translated into a Quadratic Unconstrained Binary Optimization (QUBO) problem. With this paper we investigate whether it is possible to transfer the DTW distance measure into a QUBO formulation. The motivation behind is the hope on an accelerated execution once the QA hardware scales up and the aspiration of gaining benefits due to quantum effects that are not given in the classical calculation. In principle, we find that it is possible to transform DTW into a QUBO formulation suitable for executing on QA hardware. Also, the algorithm returns not only the minimum total distance between two sequences, but also the corresponding warping path. However, there are several difficulties that make a manual intervention necessary.
机译:动态时间规整(DTW)是距离度量的代表,该距离度量能够计算两个时间序列之间的距离。它通常用于识别手写或口头语言。元启发式量子退火(QA)可用于解决组合优化问题。与“模拟退火”相似,它试图找到目标函数的全局最小值。为了使用专用的QA硬件,需要优化的问题需要转换为二次无约束二进制优化(QUBO)问题。通过本文,我们研究了是否有可能将DTW距离度量转换为QUBO公式。背后的动机是,一旦QA硬件得以扩展,人们就希望能够加快执行速度,并希望获得经典计算中未提供的量子效应,从而获得收益。原则上,我们发现可以将DTW转换为适合在QA硬件上执行的QUBO公式。而且,该算法不仅返回两个序列之间的最小总距离,而且还返回相应的变形路径。但是,有一些困难使得必须进行手动干预。

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