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The aim of this study is to develop a time series classification method based on scale-space theory. Our study has been conducted in three steps: In the first step, scale-space extrema of time series found through using SiZer (SIgnificant ZERo crossings of the derivatives) method and local features set constructed around the determined extreme points, based on interval-widths list entered by the user...
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