Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications

Simulation analysis based on the dual spectrum characteristic algorithm of communication radio station

Authors
Wenle Yuan, Xuanmin Lu, Wensheng Luo, Jinjie Cao
Corresponding Author
Wenle Yuan
Available Online November 2016.
DOI
https://doi.org/10.2991/aiea-16.2016.71How to use a DOI?
Keywords
Double spectrum; Higher-order Statistics; Fourier; feature extraction; pattern identification.
Abstract

In order to study the characteristics of double spectrum radio signals, based on higher order statistics and the double spectrum definition and properties, using two kinds of direct and indirect spectrum feature extraction algorithm, and two kinds of radio signal spectrum estimation is simulated. Therefore, it is concluded that the higher order statistics to inhibit Gauss process.

Copyright
© 2016, 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 2016 International Conference on Artificial Intelligence and Engineering Applications
Series
Advances in Computer Science Research
Publication Date
November 2016
ISBN
978-94-6252-270-1
ISSN
2352-538X
DOI
https://doi.org/10.2991/aiea-16.2016.71How to use a DOI?
Copyright
© 2016, 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  - Wenle Yuan
AU  - Xuanmin Lu
AU  - Wensheng Luo
AU  - Jinjie Cao
PY  - 2016/11
DA  - 2016/11
TI  - Simulation analysis based on the dual spectrum characteristic algorithm of communication radio station
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence and Engineering Applications
PB  - Atlantis Press
SP  - 399
EP  - 404
SN  - 2352-538X
UR  - https://doi.org/10.2991/aiea-16.2016.71
DO  - https://doi.org/10.2991/aiea-16.2016.71
ID  - Yuan2016/11
ER  -