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Outline
To address the issue of attenuation and waveform distortion in laser echo signals, laser echo signal model is constructed. Lightweight CNN-Transformer hybrid network is built to extract both local details and global temporal features of the signal, and a dynamic adjustment mechanism is designed to adaptively fuse local and global features. Furthermore, cognitive enhancement module is introduced, which utilizes an external memory bank to store and retrieve prior information from historical echoes, and optimizes feature inference through knowledge distillation loss. The results indicate that the attenuation of the laser echo is positively correlated with the severity of adverse weather conditions. Through distillation learning, the student network fully retains the core feature extraction logic of the teacher network. The proposed Dynamic Cognitive Enhancement Network algorithm reduces Mean Squared Error (MSE) by 40.2% and improves Peak Signal to Noise Ratio (PSNR) by 2.21 dB compared to the suboptimal model.
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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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