SSRCNN: A Semi-Supervised Learning Framework for Signal Recognition
IEEE Transactions on Cognitive Communications and Networking(2021)
摘要
Due to the emergence of deep learning, signal recognition has made great strides in performance improvement. The success of most deep learning methods relies on the accessibility of abundant labeled training data. However, the annotation of signals is quite expensive, making it challenging to train deep learning models substantially. This calls for the development of semi-supervised learning (SSL)...
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关键词
Task analysis,Deep learning,Modulation,Feature extraction,Training data,Training,Semantics
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