Li, S.; Cui, Y.; Zhang, Q.; Li, Z.; Gao, R.; Tian, F.; Tian, Q.; Liu, B.; Jiang, J.; Wang, Y.;
et al. Multi-Carrier Signal Recognition Method Based on Multi-Feature Input and Hybrid Training Neural Network. Electronics 2022, 11, 579.
https://doi.org/10.3390/electronics11040579
AMA Style
Li S, Cui Y, Zhang Q, Li Z, Gao R, Tian F, Tian Q, Liu B, Jiang J, Wang Y,
et al. Multi-Carrier Signal Recognition Method Based on Multi-Feature Input and Hybrid Training Neural Network. Electronics. 2022; 11(4):579.
https://doi.org/10.3390/electronics11040579
Chicago/Turabian Style
Li, Shanshan, Yi Cui, Qi Zhang, Zhipei Li, Ran Gao, Feng Tian, Qinghua Tian, Bingchun Liu, Jinkun Jiang, Yongjun Wang,
and et al. 2022. "Multi-Carrier Signal Recognition Method Based on Multi-Feature Input and Hybrid Training Neural Network" Electronics 11, no. 4: 579.
https://doi.org/10.3390/electronics11040579
APA Style
Li, S., Cui, Y., Zhang, Q., Li, Z., Gao, R., Tian, F., Tian, Q., Liu, B., Jiang, J., Wang, Y., & Xin, X.
(2022). Multi-Carrier Signal Recognition Method Based on Multi-Feature Input and Hybrid Training Neural Network. Electronics, 11(4), 579.
https://doi.org/10.3390/electronics11040579