摘要
在提取雷达辐射源特征参数的基础上,利用支持向量机(SVM)算法分别就一般正常参数、存在畸变参数、用主成分分析降维处理后三种情况进行了识别实验,对比分析了在这三种情况下归一化前后的实验结果,得出了几点结论,对特征向量的归一化处理有一定的指导意义。
Supposing radar emitters feature vectors has been obtained,and support vector machine（SVM） algorithm is used to carry out recognition experiment under the three situations： normal situation,with mutation parameter and reducing dimensions using principal component analysis.And the experiment results under the three situations are compared and analyzed.And some conclusions are summarized,which has some instruction meaning to feature vector normalization.
出处
《电子信息对抗技术》
2010年第6期30-33,共4页
Electronic Information Warfare Technology
关键词
归一化
主成分分析
支持向量机
辐射源识别
normalization
principal component analysis
support vector machine
identification
