Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)

Research on a New Method of Signal Data Recognition and Acquisition

Authors
Kai Zhou, Xueling Zhang, Jiajia Chen
Corresponding Author
Kai Zhou
Available Online July 2018.
DOI
10.2991/cecs-18.2018.72How to use a DOI?
Keywords
Radio, data acquisition, neural network, monitoring.
Abstract

With the development of 5G communication, radio monitoring data will have an explosive growth. Due to the large size, huge variety and strong specialty of radio data, data acquisition is becoming a concerned difficulty. The key links in radio service data recognition and acquisition are studied, and a new method of data acquisition is proposed. the improved BP neural network algorithm is used to improve the accuracy of data identification, enhance the generalization ability of the system, and realize the automatic identification and storage of data. Experimental results show that the new method can reduce the system complexity and has high efficiency.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
Series
Advances in Computer Science Research
Publication Date
July 2018
ISBN
10.2991/cecs-18.2018.72
ISSN
2352-538X
DOI
10.2991/cecs-18.2018.72How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Kai Zhou
AU  - Xueling Zhang
AU  - Jiajia Chen
PY  - 2018/07
DA  - 2018/07
TI  - Research on a New Method of Signal Data Recognition and Acquisition
BT  - Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
PB  - Atlantis Press
SP  - 423
EP  - 428
SN  - 2352-538X
UR  - https://doi.org/10.2991/cecs-18.2018.72
DO  - 10.2991/cecs-18.2018.72
ID  - Zhou2018/07
ER  -