Time

Dynamic Time Warping of inverted binary signals

Dynamic Time Warping of inverted binary signals
  1. What is dynamic time warping?
  2. What is DTW algorithm?
  3. Is dynamic time warping metric?

What is dynamic time warping?

Dynamic Time Warping (DTW) is a way to compare two -usually temporal- sequences that do not sync up perfectly. It is a method to calculate the optimal matching between two sequences. DTW is useful in many domains such as speech recognition, data mining, financial markets, etc.

What is DTW algorithm?

DTW algorithm. Dynamic time warping (DTW) is a time series alignment algorithm developed originally for speech recognition(1). It aims at aligning two sequences of feature vectors by warping the time axis iteratively until an optimal match (according to a suitable metrics) between the two sequences is found.

Is dynamic time warping metric?

First, you say "dynamic time warping metric", however DTW is a distance measure, but not a metric (it does not obey the triangular inequality). Paper [a] compares DTW to 12 alternatives on 43 datasets, DTW really does work very well for most problems.

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