A Novel Recognition Algorithm Based on Holder Coefficient Theory and Interval Gray Relation Classifier

被引:22
作者
Li, Jingchao [1 ]
机构
[1] Shanghai Dianji Univ, Sch Elect Informat Engn, Shanghai, Peoples R China
来源
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS | 2015年 / 9卷 / 11期
关键词
Communication signal recognition; Feature extraction algorithm; Holder coefficient; Interval gray relation classfier; MODULATION; PROFILES;
D O I
10.3837/tiis.2015.11.018
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The traditional feature extraction algorithms for recognition of communication signals can hardly realize the balance between computational complexity and signals' interclass gathered degrees. They can hardly achieve high recognition rate at low SNR conditions. To solve this problem, a novel feature extraction algorithm based on Holder coefficient was proposed, which has the advantages of low computational complexity and good interclass gathered degree even at low SNR conditions. In this research, the selection methods of parameters and distribution properties of the extracted features regarding Holder coefficient theory were firstly explored, and then interval gray relation algorithm with improved adaptive weight was adopted to verify the effectiveness of the extracted features. Compared with traditional algorithms, the proposed algorithm can more accurately recognize signals at low SNR conditions. Simulation results show that Holder coefficient based features are stable and have good interclass gathered degree, and interval gray relation classifier with adaptive weight can achieve the recognition rate up to 87% even at the SNR of -5dB.
引用
收藏
页码:4573 / 4584
页数:12
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