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Dynamic time warping(DTW)spends most of the time in generating the correlation table,and it establishes the global path constraints to reduce the time complexity.However,the global constraints restrain just in terms of the time axis.In this paper,we therefore propose another version of DTW,to be called branch-and-bound DTW(BnB-DTW),which adaptively controb its global path constraints by reflecting the contents of input patterns. Experimental results show that the suggested BnB-DTW algorithm performs more efficiently than other conventional DTW approaches while not increasing the optimal warping cost.
Dynamic time warping (DTW) spends most of the time in generating the correlation table, and it establish the global path constraints to reduce the time complexity. However, the global constraints restrain just in terms of the time axis. In this paper, we propose another version of DTW, to be called branch-and-bound DTW (BnB-DTW), which adaptively controb its global path constraints by reflecting the contents of input patterns. Experimental results show that the suggested BnB-DTW algorithm performs more than than other conventional DTW approaches while not increasing the optimal warping cost.