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This study explores the combination of t-Distributed Stochastic Neighbor Embedding (t-SNE) dimensionality reduction technique and the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to address the challenges in multi-parameter radar signal sorting. As the complexity of radar signals has been increasing, traditional signal processing methods have revealed limitations. t-SNE effectively extracts essential features from the data by reducing dimensionality, eliminating noise and redundant information, and providing a clearer boundary for subsequent DBSCAN clustering. In the experiment, we generated five different types of radar signal data and conducted analyses using t-SNE and DBSCAN. The results show that the t-SNE dimensionality reduction combined with the DBSCAN clustering algorithm performs well in terms of purity and silhouette score, confirming the effectiveness of this method in complex radar signal sorting.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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