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A useful digital signal modulation recognition scheme inspired by the deep auto-encoder network is proposed in this investigation. In our proposed method, there ...
Abstract—Automated Modulation Classification (AMC) shows great significance for any receiver that has little knowledge of the modulation scheme of the ...
Dec 7, 2022 · Bibliographic details on Modulation Recognition of Digital Signal Based on Deep Auto-Ancoder Network.
May 8, 2024 · We describe an effective way of initializing the weights that allows deep autoencoder networks to learn low-dimensional codes that work much ...
To test modulation classification accuracy, we used in-phase and quadrature samples from data sets at various signal-to-noise levels to evaluate 5 DL networks ...
[16] proposed a novel MLP-based modulation neural network recogniser using instantaneous frequency and bandwidth features of signals. In [15], Lu et al.
Based on this, this paper proposes a signal modulation recognition method based on multi-feature fusion and constructs a deep learning network with a double- ...
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The results show that, compared with the classical machine learning algorithm, the proposed algorithm has higher recognition accuracy at low SNR, ...
This study considered Higher Order Cumulants (HOCs) up to 6th-order, and results revealed that the ANN classifiers have the best performance/complexity trade- ...
Method for AMC using powerful capability of deep networks. •. Comparison between a shallow and deep network in the application of AMC.