计算机与数字工程2013，Vol.41Issue(3)：367-369,465,4.
基于模糊C均值聚类和支持向量机的信号识别方法
Signal Recognition Method Based on Fuzzy C-Means and Support Vector Machine
顾敏剑1
作者信息
- 1. 中国船舶重工集团公司第七二三研究所 扬州225001
- 折叠
摘要
Abstract
To realize the automatic identification of digital signal modulation, the signal modulation recognition method is proposed based on Fuzzy C-Means(FCM)clustering algorithm and support vector machine(SVM). Feature selection method is established based onF-CM The the cluster validity assessment function is constructed to get the Cluster validity function value under different cluster center number and the set of feature parameters of signals is obtained through analysis significant difference in clustering. The signal recognition model structured based on SVM. Simulation results show that classification rates of the algorithm proposed in this paper are much higher than those of clustering algorithm. Especially in low signal to noise ratio, signal recognition has improved significantly.关键词
调制识别/模糊C均值聚类/特征提取/支持向量机Key words
modulation recognition/fuzzy C-Means/feature selection/support vector vachine分类
信息技术与安全科学引用本文复制引用
顾敏剑..基于模糊C均值聚类和支持向量机的信号识别方法[J].计算机与数字工程,2013,41(3):367-369,465,4.
