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

页码：560 / 563

页数：4

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