AINeutralarXiv – CS AI · 6h ago6/10
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Hamiltonian-Inspired Attention Mechanism for Scalable RF Transmitter Fingerprinting
Researchers propose the Hamiltonian Transformer, a physics-informed deep learning architecture for identifying wireless transmitters via RF fingerprinting that achieves 99.12% accuracy in controlled settings but maintains 61.64% accuracy when scaling to 150 devices. The model uses norm-preserving attention mechanisms inspired by Hamiltonian mechanics to improve generalization across receiver types, channels, and time periods compared to standard CNN and Transformer baselines.