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Table 11 Training and prediction times of ML-DRSNet, ML-DCNN, and MT-DCNN at optimal step and window sizes

From: A multi-label deep residual shrinkage network for high-density surface electromyography decomposition in real-time

Method

Window size

(data point)

Step size

(data point)

Training time

(s/epoch)

Prediction time

(ms/window)

ML-DRSNet

20

50

88.59

15.15

ML-DCNN

140

50

18.03

69.36

MT-DCNN

140

10

180.64

76.96

  1. The prediction time shown in the table is the sum of the model’s prediction time and the optimal window size