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于 2020-11-12 发布
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说明:  本文提出了一种用于通信系统中无线电信号检测的自动调制识别框架。该框架考虑了深度卷积神经网络(CNN)和长期短期记忆网络(LSTM)。 此外,我们提出了一种预处理信号表示,其组合了调制信号的同相,正交和四阶统计。所提供的数据表示允许我们的CNN和LSTM模型对我们的测试数据集实现8%的改进。(Automatic Modulation Recognition using Deep Learning Architectures, 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC))

文件列表:

Deep-Architectures-for-Modulation-Recognition-master, 0 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\CNN, 0 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\CNN\CNN.py, 9977 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\cldnn, 0 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\cldnn\lstm.py, 11109 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\inception, 0 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\inception\inception.py, 11172 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\readme.md, 361 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\resnet, 0 , 2017-08-03
Deep-Architectures-for-Modulation-Recognition-master\resnet\resnet.py, 14269 , 2017-08-03

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