Multivariate time series classification with parametric derivative dynamic time warping

作者：Gorecki Tomasz^*; Luczak Maciej

来源：Expert Systems with Applications, 2015, 42(5): 2305-2312.

DOI：10.1016/j.eswa.2014.11.007

• Dynamic time warping
• Derivative dynamic time warping
• Multivariate time series

Multivariate time series (MIS) data are widely used in a very broad range of fields, including medicine, finance, multimedia and engineering. In this paper a new approach for MTS classification, using a parametric derivative dynamic time warping distance, is proposed. Our approach combines two distances: the DTW distance between MTS and the DTW distance between derivatives of MTS. The new distance is used in classification with the nearest neighbor rule. Experimental results performed on 18 data sets demonstrate the effectiveness of the proposed approach for MTS classification.

• 出版日期2015-4-1