Dualformer applies a parameter-sharing DualNN via Transformer patches to complex signals, claiming better results on AMR, SSR, and SSP tasks than baselines.
A complex-valued transformer for automatic modulation recognition,
2 Pith papers cite this work, alongside 30 external citations. Polarity classification is still indexing.
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A new AMC architecture with cross-channel self-attention and feature-preserving denoising achieves 3-14% higher accuracy than benchmarks at low-to-medium SNRs on the RML2018.01a dataset.
citing papers explorer
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Dualformer: Efficient Feature Extractor for Complex-valued Blind Communication Signal Analysis
Dualformer applies a parameter-sharing DualNN via Transformer patches to complex signals, claiming better results on AMR, SSR, and SSP tasks than baselines.
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Cross-Validated Cross-Channel Self-Attention and Denoising for Automatic Modulation Classification
A new AMC architecture with cross-channel self-attention and feature-preserving denoising achieves 3-14% higher accuracy than benchmarks at low-to-medium SNRs on the RML2018.01a dataset.