基于SAMME+ResNet的多相码信号识别方法

doi:10.3969/j.issn.1001-506X.2020.10.12

Abstract

Abstract:

In view of the characteristics of the traditional polyphase code signal recognition methods, such as low classification accuracy, uneven class recognition rate and non-generality of recognition methods in the case of low signal to noise ratio (SNR), a polyphase code signal recognition method based on stagewise additive modeling using a multi-class exponential loss function (SAMME) algorithm in ensemble learning and residual neural network (ResNet) is proposed. Simulation experiments are carried out to classify and identify five kinds of polyphase code signals, and the validity of the model is verified. The influence of different quantity base learners on the model is analyzed. Finally, the proposed method is compared with the traditional classification methods. Simulation results show that when the SNR is lower than 6 dB, the proposed method improves the classification accuracy by about 10% compared with single residual network and reduces the difference of recognition rate between classes and also has great advantages over common classification methods.

Key words: polyphase code, signal recognition, ensemble learning, residual neural network (ResNet)

CLC Number:

TN971.1

Yicong SUN, Runlan TIAN, Huixu DONG, Liang SUN. Polyphase code signal recognition method based on SAMME+ResNet[J]. Systems Engineering and Electronics, 2020, 42(10): 2239-2245.

Figures/Tables 9

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References 24

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层名	结构
卷积层	3×3, 16
残差网络层1	$ \left[ \begin{array}{l}3 \times 3, 16\\3 \times 3, 16\end{array} \right] \times 3$
残差网络层2	$ \left[ \begin{array}{l}3 \times 3, 32\\3 \times 3, 32\end{array} \right] \times 3$
残差网络层3	$ \left[ \begin{array}{l}3 \times 3, 64\\3 \times 3, 64\end{array} \right] \times 3$
池化输出层	平均池化, softmax,全连接

模型	集成精度/%	最大基学习器精度/%	精度增加量/%	训练时间/min:s
ResNet 20	87.667	-	-	03:46
SAMME+ResNet 20(2)	89.333	87.933	1.400	07:17
SAMME+ResNet 20(3)	93.111	90.667	2.444	10:51
SAMME+ResNet 20(4)	92.667	91.133	1.534	14:30

分类方法	时间
文献[23]方法	01′32″
文献[24]方法	19′23″
VGG-19	06′59″
GoogleNet	08′24″
本文方法	10′51″

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Polyphase code signal recognition method based on SAMME+ResNet

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