研究文章
飙升排序的联合概率建模的神经高峰火车和波形
表3
数据集的分类错误率WaveClus semiartificial。
|
| 数据集 |
信噪比 |
GMM |
WaveClus方法 |
提出了 |
|
| Easy1 |
清洁 |
0.93% |
0.00% |
0.97% |
| 10 dB |
0.72% |
0.00% |
0.77% |
| 5分贝 |
0.89% |
0.00% |
0.85% |
| 0分贝 |
0.81% |
0.21% |
0.85% |
| −5分贝 |
1.25% |
0.52% |
0.97% |
| −10 dB |
8.18% |
3.47% |
6.20% |
|
| Difficult1 |
清洁 |
3.18% |
0.45% |
2.58% |
| 10 dB |
4.83% |
0.94% |
3.46% |
| 5分贝 |
6.89% |
1.36% |
5.32% |
| 0分贝 |
19.77% |
20.0% |
37.21% |
|
|
