Table 1.
Running time for learning peak recognition models (Gaussian, SR, KSR, and GMM) from 2000 ICP pulses, and for recognition on 1 and 2000 pulses.
| Gaussian | SR | KSR | GMM | |
|---|---|---|---|---|
| Learning (2000 pulses) | 70 ms | 90 ms | 1,340 ms | 33,940 ms |
| 1.0 | 1.28 | 19 | 484 | |
| Recognition (1 pulse) | 1.3 ms | 0.19 ms | 19.6 ms | 2.3 ms |
| ratio | 6.70 | 1.00 | 100.94 | 11.85 |
| Recognition (2000 pulses) | 2.861 sec | 0.23 sec | 2.028 sec | 15.156 sec |
| ratio | 12.39 | 1.00 | 8.79 | 65.64 |
While the Gaussian model performs the fastest for learning, SR-based model offers the best performance during recognition.