Table 3 Indicators of several typical filtering algorithms after processing.
From: Time frequency analysis of elastic wave PSO OMP for defects in flat steel of down conductors
Indicators Algorithm | SNR(dB) | PSNR(dB) | RMSE(V) | MSE(V2) | SIMI(%) | Calculation Cost | TIME(s) |
|---|---|---|---|---|---|---|---|
PSO-MP(Gabor) | 28.89484 | 65.20794 | 3.93E-4 | 1.54E-7 | 99. 9998 | Moderate | 1.02 |
K-SVD | 22.18386 | 46.39776 | 2.091E-3 | 4.37E-6 | 99.1962 | Low | 0.5 |
LRMR | 32.68880 | 3.900427 | 0.445982 | 0.1989 | 98.0059 | Moderate | 0.45 |
Wavelet | 26.31004 | 68.5162 | 2.62E-3 | 6.87E-08 | 99.8477 | Low | 0.08 |
Auto Encoder | 26.12440 | 45.6458 | 3.6E-3 | 1.3307E −5 | 99.8273 | High | 4.2 |
Liner Residual Learning | 26.00690 | 158.4409 | 8.3617E −9 | 6.9918E −17 | 99.998 | High | 4.2 |
Adaptive Residual Learning | 25.94140 | 72.6908 | 1.6211E −4 | 2.6278E −8 | 99.948 | Low | 0.2 |
Polynomial Residual Learning | 26.55450 | 74.6247 | 1.2975E −4 | 1.6835E −8 | 99.990 | Low | 0.3 |
