Signals Modulation Recognition Based On Efficient Attribute Reduction With Neighborhood Rough Set

被引：0
|
作者：
Han, Yingzheng [1 ]
Wu, Juanping [1 ]
Liang, Xiaofang [1 ]
机构：
[1] Taiyuan Univ Technol, Coll Informat Engn, Taiyuan 030024, Shanxi, Peoples R China
来源：
ADVANCES IN MANUFACTURING TECHNOLOGY, PTS 1-4 | 2012年 / 220-223卷
关键词：
modulation recognition; BP neural network; neighborhood rough set; fast attribute reduction; feature selection;
D O I：
10.4028/www.scientific.net/AMM.220-223.2301
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The purpose of communication signals automatic modulation recognition is to judge signal modulation styles and estimate signal modulation parameters on the precondition of unknown modulation information. According to the seven kinds communication modulation signals studied in this paper, select a group of feature parameters based on the time-frequency characteristics of communication signals. The fast algorithm for attribute reduction based on neighborhood rough set using feature selection is introduced in detail. Then, using back propagation network as classification instruments to identify signals. The simulation shows that the method can not only reduce the number of feature parameters, but also improve the recognition rate.
引用
收藏
页码：2301 / 2307
页数：7
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