@inproceedings{fbe7ac4e9306416e8260c1cfb02da39d,
title = "Modulation Recognition Algorithm of Communication Signals Based on Artificial Neural Networks",
abstract = "With the development of wireless communication technologies and computer science, modulation recognition of communication signals has attracted more and more attention. This paper studies a modulation recognition method based on artificial neural networks (ANN). Two kinds of communication channels are tested with the modulation recognition method, namely additive white Gaussian noise (AWGN) channel and Rayleigh channel. Simulations are formed in MATLAB environment. According to the simulation results, the modulation recognition method can achieve an average recognition accuracy of 96\% in the AWGN channel and 82\% in the Rayleigh channel.",
keywords = "Artificial neural network, Modulation recognition, Signal classification",
author = "Dongzhu Li and Liang Ye and Xuanli Wu",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 9th International Conference on Communications, Signal Processing, and Systems, CSPS 2020 ; Conference date: 04-07-2020 Through 05-07-2020",
year = "2021",
doi = "10.1007/978-981-15-8411-4\_50",
language = "英语",
isbn = "9789811584107",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "384--389",
editor = "Qilian Liang and Wei Wang and Xin Liu and Zhenyu Na and Xiaoxia Li and Baoju Zhang",
booktitle = "Communications, Signal Processing, and Systems - Proceedings of the 9th International Conference on Communications, Signal Processing, and Systems",
address = "德国",
}