Feature Image-Based Automatic Modulation Classification Method Using CNN Algorithm

被引：0
|
作者：
Lee, Jung Ho [1 ]
Kim, Kwang-Yul [1 ]
Shin, Yoan [1 ]
机构：
[1] Soongsil Univ, Sch Elect Engn, Seoul 06978, South Korea
来源：
2019 1ST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION (ICAIIC 2019) | 2019年
关键词：
automatic modulation classification; cumulant; deep learning; convolutional neural network; feature extraction;
D O I：
10.1109/icaiic.2019.8669002
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we propose a feature image-based automatic modulation classification (AMC) method to classify modulation type. The proposed method uses a convolutional neural network (CNN) which is one of deep learning algorithms for image classification. In order to classify the modulation type, various features are transformed in a two-dimensional image and this image is used as the input of the CNN. From the simulation results, we show that the proposed method improves classification performance.
引用
收藏
页码：560 / 563
页数：4
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