Effective Feature-Based Automatic Modulation Classification Method Using DNN Algorithm

被引：0

作者：

Lee, Sang Hoon ^{[1
]}

Kim, Kwang-Yul ^{[1
]}

Kim, Jae Hyun ^{[2
]}

Shin, Yoan ^{[1
]}

机构：

[1] Soongsil Univ, Sch Elect Engn, Seoul 06978, South Korea

[2] Ajou Univ, Dept Elect & Comp Engn, Suwon 16499, 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; deep neural network; cumulant; correlation; effective features;

D O I：

10.1109/icaiic.2019.8669036

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 an effective feature-based automatic modulation classification (AMC) method using a deep neural network (DNN). In order to classify the modulation type, we consider effective features according to the modulation signals. The proposed method removes the meaningless features that have little influence on the classification and only uses the effective features that have high influence by analyzing the correlation coefficients. From the simulation results, we observe that the proposed method can make the AMC system low complexity.

引用

页码：557 / 559

页数：3

共 50 条

[31] A Study on Prosodic Feature-Based Automatic Classification of Languages from Northeastern India
Dutta, Sushanta Kabir
Singh, Lairenlakpam Joyprakash
[J]. ADVANCES IN COMMUNICATION, DEVICES AND NETWORKING, 2018, 462 : 583 - 589
[32] Cyclic Feature-Based Modulation Recognition Using Compressive Sensing
Xie, Lijin
Wan, Qun
[J]. IEEE WIRELESS COMMUNICATIONS LETTERS, 2017, 6 (03) : 402 - 405
[33] Feature-Based Digital Modulation Recognition Using Compressive Sampling
Sun, Zhuo
Wang, Sese
Chen, Xuantong
[J]. MOBILE INFORMATION SYSTEMS, 2016, 2016
[34] Sensing-Based Feature Engineering and Asynchronous OFDM Blind Modulation Classification Using SMOTE-DNN
Yang, Yuxiao
Yang, Junkai
Xu, Chang
Shen, Xiaobo
[J]. IEEE SENSORS JOURNAL, 2024, 24 (14) : 22117 - 22128
[35] A Feature-Based Method for Automatic Anomaly Identification in Power Quality Measurements
Zyabkina, Olga
Domagk, Max
Meyer, Jan
Schegner, Peter
[J]. 2018 IEEE INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS (PMAPS), 2018,
[36] Semi-automatic range to range registration: a feature-based method
Chao, C
Stamos, L
[J]. FIFTH INTERNATIONAL CONFERENCE ON 3-D DIGITAL IMAGING AND MODELING, PROCEEDINGS, 2005, : 254 - 261
[37] A Feature-based Automatic Dimension Marking Method for In-process Models
Shao Li
Zhang Shusheng
Zhou Chao
Bai Xiaoliang
[J]. MECHATRONICS ENGINEERING, COMPUTING AND INFORMATION TECHNOLOGY, 2014, 556-562 : 6089 - 6093
[38] Hierarchical Hypothesis and Feature-Based Blind Modulation Classification for Linearly Modulated Signals
Majhi, Sudhan
Gupta, Rahul
Xiang, Weidong
Glisic, Savo
[J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2017, 66 (12) : 11057 - 11069
[39] Is blind image steganalysis practical using feature-based classification?
Ahd Aljarf
Haneen Zamzami
Adnan Gutub
[J]. Multimedia Tools and Applications, 2024, 83 : 4579 - 4612
[40] Mushroom Classification Using Feature-Based Machine Learning Approach
Maurya, Pranjal
Singh, Nagendra Pratap
[J]. PROCEEDINGS OF 3RD INTERNATIONAL CONFERENCE ON COMPUTER VISION AND IMAGE PROCESSING, CVIP 2018, VOL 1, 2020, 1022 : 197 - 206

← 1 2 3 4 5 →