基于时频特征的卷积神经网络跳频调制识别

李红光,郭英,眭萍,齐子森

Frequency hopping modulation recognition of convolutional neural network based on time-frequency characteristics

Hong-guang LI,Ying GUO,Ping SUI,Zi-sen QI

表 2 6种参数组合的CNN调制识别训练结果

Tab.2 Training results of CNN modulation recognition based on six parameter combinations

${K_{\rm l}}$ r ${R_{\rm{c}}}$/kB $V$/（幅·s−1） ${R_{{\rm{psr}}}}$/% $7 \times 7$ 2 2269.476 2.92 91.32 $5 \times 5$ 2 1585.653 5.24 87.39 $3 \times 3$ 2 357.248 8.23 83.46 $3 \times 3$ 4 357.248 8.23 86.75 $3 \times 3$ 6 357.248 8.23 90.14 $3 \times 3$ 8 357.248 8.23 91.18