Name
Title | ||
|---|---|---|
Intelligent Denoising-Aided Deep Learning Modulation Recognition With Cyclic Spectrum Features for Higher Accuracy |
Abstract | ||
|---|---|---|
Deep-learning-based modulation recognition methods can extract the features of signals automatically with the usage of the deep neural network (DNN). However, the background noises might lower the recognition accuracy and induce longer convergence time. In order to improve the recognition accuracy and to reduce the computational complexity, in this article, we propose to construct the dataset base... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TAES.2021.3083406 | IEEE Transactions on Aerospace and Electronic Systems |
Keywords | DocType | Volume |
Modulation,Feature extraction,Noise reduction,Deep learning,Signal to noise ratio,Correlation,Noise measurement | Journal | 57 |
Issue | ISSN | Citations |
6 | 0018-9251 | 1 |
PageRank | References | Authors |
0.43 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lin Zhang | 1 | 38 | 22.81 |
| Heng Liu | 2 | 1 | 0.43 |
| Xiaoling Yang | 3 | 1 | 0.43 |
| Yuan Jiang | 4 | 1 | 0.43 |
| Zhiqiang Wu | 5 | 134 | 17.56 |