Table 7 Comparison of Technique 1 and Technique 2 for modulation scheme classification and parameter optimization.
Aspect | Technique 1 | Technique 2 |
|---|---|---|
Methodology | Hierarchical classification with primary and parameter-specific classifiers | Direct classification of full dataset without hierarchy |
Primary classification accuracy | 98.18% (decision tree) | N/A |
FSK, PSK M classification | 99.81% (decision tree) | N/A |
CPM M classification | 99.81% (ensemble subspace KNN) | N/A |
CPM L classification | 99.84% (ensemble subspace KNN) | N/A |
CPM h classification | 99.91% (ensemble subspace KNN) | N/A |
CPM mode classification | 99.3% (narrow neural network) | N/A |
PSK/FSK mode classification | 99.8% (decision tree) | N/A |
Overall mode classification accuracy | 99.41% (narrow neural network and decision tree) | 98.35% (bilayered neural network) for direct classification |
Classifier types | Decision tree, narrow neural network and ensemble subspace KNN | Neural network |
Approach | Hierarchical classification by modulation type and parameters (M, h, L, mode) | Single-step mode classification |
