Digital Modulation Classification using Kernel Fisher Discriminant Analysis for Reconfigurable Software Radio

摘要：

In this paper,a new classification method based on kernel fisher discriminant analysis is used in the digital signals classification.The second,fourth and sixth order cumulants of the received signals are used as the classification vector firstly,then the kernel thought is used to map the feature vector to the high dimensional feature space and linear fisher discriminant analysis is applied to signal classification.The radial basis kernel function is selected and one against one or one against rest of multi-class classifier is designed and method of parameter selection using cross-validating grid is adopted to build an effective and robust KFDA classifier.Through the experiments it can be concluded that compared with SVM classifier,KFDA can get almost the same classification accuracy and requires less time.

作者: Xin Zhou Guopeng Yang Ying Wu

作者单位: Zhengzhou InformationScience and TechnologyInstitute,Henan,China Zhengzhou Institute ofSurveying and Mapping,Henan,China Information Science and Technology Institute,Zhengzhou,Henan,China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）