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Found 3 papers, 1 papers with code
Mixing Signals: Data Augmentation Approach for Deep Learning Based Modulation Recognition
Data augmentation, as the strategy of expanding dataset, can improve the generalization of the deep learning models and thus improve the accuracy of the models to a certain extent.
SR2CNN: Zero-Shot Learning for Signal Recognition
This paper proposes a ZSL framework, signal recognition and reconstruction convolutional neural networks (SR2CNN), to address relevant problems in this situation.
Spectrum Sensing Based on Deep Learning Classification for Cognitive Radios
We present spectrum sensing as a classification problem and propose a sensing method based on deep learning classification.
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