Online query algorithm of dynamic time sequences based on fast fourier transform

Zichun Zhang, Yongdan Liu, Xiaoyun Guo, Jianhua Zhu
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引用次数: 0

Abstract

An algorithm of online similarity query of dynamic time sequences is proposed as for the need of time sequences real-time analysis. This algorithm uses improved Euclidean Distance as similar measurement and then evaluates the similar distance between dynamic time sequences and pattern time sequences in a batch pattern using Fast Fourier Transform. In order to shorten waiting time prediction patterns are used to predict feature value and accomplish fast response of online query by comparing the similarity between prediction sequences and pattern sequences. Simulation results show that the proposed algorithm can efficiently and correctly solve the online similar query.
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基于快速傅立叶变换的动态时间序列在线查询算法
针对时间序列实时分析的需要,提出了一种动态时间序列在线相似度查询算法。该算法采用改进的欧几里得距离作为相似度量,然后利用快速傅里叶变换对批处理模式下动态时间序列和模式时间序列之间的相似距离进行评估。为了缩短等待时间,采用预测模式通过比较预测序列与模式序列的相似性来预测特征值,实现在线查询的快速响应。仿真结果表明,该算法能够有效、正确地解决在线相似查询问题。
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