The birth of Dynamic Time Warping (DTW) has a certain history (Itakura, a Japanese scholar), and its purpose is relatively simple. It is a method of measuring the similarity of two different time series of different lengths. It is widely used, mainly in template matching, for example, in isolated word speech recognition (whether two segments of speech represent the same word), hand gesture recognition, data mining and information retrieval.

DTW.py

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．