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Multi-Channel Attentive Feature Fusion for Radio Frequency Fingerprinting
The features extracted from different channels are fused adaptively using a shared attention module, where the weights of neural features from multiple channels are learned during training the McAFF model.
Learning of Time-Frequency Attention Mechanism for Automatic Modulation Recognition
Recent learning-based image classification and speech recognition approaches make extensive use of attention mechanisms to achieve state-of-the-art recognition power, which demonstrates the effectiveness of attention mechanisms.
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