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

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.