| [1] |
王国宏,白杰,张翔宇,等.基于FRFT域特征差异的压制干扰检测与分类算法[J].北京航空航天大学学报,2018,44(6):1124-1132.
|
| [2] |
VUOHTONIEMI R,MÄKELÄ J,VARTIAINEN J,et al.Detection of broadcast signals in cognitive radio based PLC using the FCME algorithm[C]//Proceedings of the 18th IEEE International Symposium on Power Line Communications and Its Applications.Washington D.C.,USA:IEEE Press,2014:70-74.
|
| [3] |
YAN Haohui,ZHOU Bin,LIU Jing,et al.Radio signal recognition based on constructing typical spectrum[C]//Proceedings of the 2nd IEEE International Conference on Computer and Communications.Washington D.C.,USA:IEEE Press,2016:1889-1894.
|
| [4] |
MOUMENA A.Abnormal behavior detection of jamming signal in the spectrum using a combination of compressive sampling and intelligent bivariate K-means clustering technique in wideband cognitive radio systems[C]//Proceedings of the 4th International Conference on Electrical Engineering.Washington D.C.,USA:IEEE Press,2015:1-4.
|
| [5] |
黄莹,郝新红,孔志杰,等.基于熵特征的调频引信目标与干扰信号识别[J].兵工学报,2017,38(2):254-260.
|
| [6] |
KONG Mingming,LIU Jing,ZHANG Zihao,et al.Radio ground-to-air interference signals recognition based on support vector machine[C]//Proceedings of IEEE International Conference on Digital Signal Processing.Washington D.C.,USA:IEEE Press,2015:987-990.
|
| [7] |
王桂胜,任清华,姜志刚,等.基于信号特征空间的TDCS干扰分类识别[J].系统工程与电子技术,2017,39(9):1950-1958.
|
| [8] |
FU Ying,WANG Xing.Radar signal recognition based on modified semi-supervised SVM algorithm[C]//Proceedings of the 2nd IEEE Conference on Advanced Information Technology,Electronic and Automation Control.Washington D.C.,USA:IEEE Press,2017:2336-2340.
|
| [9] |
KRIZHEVSKY A,SUTSKEVER I,HINTON G E.ImageNet classification with deep convolutional neural networks[C]//Proceedings of the 25th International Conference on Neural Information Processing Systems.New York:ACM Press,2012:1097-1105.
|
| [10] |
SIMONYAN K,ZISSERMAN A.Very deep convolutional networks for large-scale image recognition[EB/OL].[2018-10-01].https://arxiv.org/pdf/1409.1556.pdf.
|
| [11] |
SZEGEDY C,LIU Wei,JIA Yangqing,et al.Going deeper with convolutions[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Computer Society,2015:1-9.
|
| [12] |
HE Kaiming,ZHANG Xiangyu,REN Shaoqing,et al.Deep residual learning for image recognition[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:770-778.
|
| [13] |
HU Jie,SHEN Li,SUN Gang.Squeeze-and-excitation networks[EB/OL].[2018-10-01].https://arxiv.org/pdf/1709.01507.pdf.
|
| [14] |
PENG Shengliang,JIANG Hanyu,WANG Huaxia,et al.Modulation classification using convolutional neural network based deep learning model[C]//Proceedings of 2017 Wireless and Optical Communication Conference.Washington D.C.,USA:IEEE Press,2017:1-5.
|
| [15] |
YA Tu,LIN Yun,WANG Hui.Modulation recognition of digital signal based on deep auto-ancoder network[C]//Proceedings of IEEE International Conference on Software Quality,Reliability and Security Companion.Washington D.C.,USA:IEEE Press,2017:256-260.
|
| [16] |
LIN Min,CHEN Qiang,YAN Suicheng.Network in network[EB/OL].[2018-10-01].https://arxiv.org/pdf/1312.4400.pdf.
|
| [17] |
IOFFE S,SZEGEDY C.Batch normalization:accelerating deep network training by reducing internal covariate shift[C]//Proceedings of the 32nd International Conference on Machine Learning.New York,USA:ICML Press,2015:448-456.
|
| [18] |
SZEGEDY C,IOFFE S,VANHOUCKE V,et al.Inception-v4,inception-resnet and the impact of residual connections on learning[EB/OL].[2018-10-01].https://arxiv.org/pdf/1602.07261.pdf.
|
| [19] |
XIE Saining,GIRSHICK R,DOLLÁR P,et al.Aggregated residual transformations for deep neural networks[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2017:5987-5995.
|