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科技导报
|专题:电子战
2019
, 37
(4) :
55
-62
非合作通信中调制识别算法研究进展
全屏
黄知涛1 , 杨杰1 , 王翔1 , 崔轩2 , 王永芳2
作者信息
1. 国防科技大学, 电子信息系统复杂电磁环境效应国家重点实验室, 长沙 410073;
2. 中国人民解放军海军东海舰队, 宁波 315000
作者简介:
黄知涛,教授,研究方向为通信信号处理、模式识别和人工智能,电子信箱:huangzhitao@nudt.edu.cn;杨杰,硕士研究生,研究方向为调制识别、深度学习,电子信箱:13701350272@163.com
A Survey of modulation recognition algorithms in non-cooperative communication
HUANG Zhitao1 , YANG Jie1 , WANG Xiang1 , CUI Xuan2 , WANG Yongfang2
Affiliations
1. State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha 410073, China;
2. East Sea Fleet, People's Liberation Army Navy of China, Ningbo 315000, China
出版时间: 2019-02-28
doi: 10.3981/j.issn.1000-7857.2019.04.010
文章导航
概述了非合作通信中调制识别技术的概念、内涵;介绍了经典调制识别算法和智能调制识别算法的基本原理与处理流程,分析了每类算法的优势以及存在的问题;针对现有调制识别算法存在的问题,探讨了非合作通信中调制识别算法的发展方向。
非合作通信
/
调制识别
/
特征提取
/
最大似然
/
深度学习
Based on a comprehensive study of the modulation recognition algorithm in the non-cooperative communication, this paper reviews the current research status of the communication signal classical modulation recognition algorithm and the intelligent modulation recognition algorithm based on the deep learning. The concept and the connotation of the modulation recognition technology in the noncooperative communication are explained, focusing on the basic principle and the processing flow of the classical modulation recognition algorithm and the intelligent modulation recognition algorithm, the advantages and disadvantages of each kind of algorithms are analyzed, and the future development direction of the modulation recognition algorithm in the non-cooperative communication are discussed.
non-cooperative communication
/
modulation recognition
/
feature extraction
/
maximum likelihood
/
deep learning
黄知涛, 杨杰, 王翔, 崔轩, 王永芳.
非合作通信中调制识别算法研究进展.
科技导报,
2019
, 37
(4)
: 55
-62
.
DOI: 10.3981/j.issn.1000-7857.2019.04.010
HUANG Zhitao, YANG Jie, WANG Xiang, CUI Xuan, WANG Yongfang.
A Survey of modulation recognition algorithms in non-cooperative communication[J].
Science & Technology Review ,
2019
, 37
(4)
: 55
-62
.
DOI: 10.3981/j.issn.1000-7857.2019.04.010
2019年第37卷第4期
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文章信息
doi: 10.3981/j.issn.1000-7857.2019.04.010
接收时间:2018-10-29
首发时间:2019-03-08
出版时间:2019-02-28
收稿日期:2018-10-29
修回日期:2018-12-11
https://castjournals.cast.org.cn/joweb/kjdb/CN/10.3981/j.issn.1000-7857.2019.04.010
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2种不同金属材料的力学参数
科 Family 属数 Number of genus 种数 Number of species 占总种数比例 Percentage of total species (%) 属 Genus 种数 Number of species 占总种数比例 Percentage of total species (%) 鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78 小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39 多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39 红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87 小菇属 Mycena 11 5.26 光柄菇属 Pluteus 5 2.39 红菇属 Russula 17 8.13 栓菌属 Trametes 5 2.39
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