| 基于支持向量机的N型激波识别技术 |
| |
| 引用本文： | 吕永林,字正华.基于支持向量机的N型激波识别技术[J].云南师范大学学报(自然科学版),2009,29(4):35-38. |
| |
| 作者姓名： | 吕永林 字正华 |
| |
| 作者单位： | 1. 楚雄师范学院经济信息管理及计算机应用系,云南,楚雄,675000
2. 云南财经大学信息学院,云南,昆明,650221 |
| |
| 基金项目： | 云南省自然科学基金，云南省教育厅科研立项基金 |
| |
| 摘 要： | 超音速目标识别过程中，其产生的N型激波容易与爆炸波混淆在一起，从爆炸波中识别N型激波非常重要。本文提出一种从爆炸波中识别N型激波的技术，通过用5．56mm，7．62mm，12．7mm超音速枪弹做射击试验和TNT炸药爆炸试验，获取N型激波和爆炸波原始数据，进行了特征提取，并采用主成份分析（PCA）方法对特征数据进行压缩处理后，用支持向量机（SVM）方法进行分类识别。结果表明，文中提出的识别方法是可行的和有效的。
|
| 关 键 词： | N型激波 爆炸燥声 识别技术 主成份分析 支持向量机(SVM) |
Recognition Technique of Shock N-wave Based on Support Vector Machine(SVM) |
| |
| Lu Yong-lin,ZI Zheng-hua.Recognition Technique of Shock N-wave Based on Support Vector Machine(SVM)[J].Journal of Yunnan Normal University (Natural Sciences Edition),2009,29(4):35-38. |
| |
| Authors: | Lu Yong-lin ZI Zheng-hua |
| |
| Institution: | Lu Yong -lin , ZI Zheng - hua ( 1. Department of Economic Information Management and Computer Application, Chuxiong Normal University, Chuxiong 675000, China; 2. School of Information, Yunnan University of Finance and Economics,Kunming 650221, China) |
| |
| Abstract: | It is important to distinguish shock N-wave from explosive noise in recognizing different supersonic targets. A recognition technique of shock N-wave was proposed in this paper. By experimental test for 5.56mm, 7.62mm, 12.7mm projectiles and TNT explosion, original data were obtained and then feature extraction was carried out. We employed principal component analysis (PCA) to compress data set of original feature variables and method of support vector machine (SVM) to learn and train data set. Results show that the recognition approach employed in this paper is feasible and effective. |
| |
| Keywords: | Shock N-wave Explosive noise Recognition technique Principal component analysis (PCA) Support vector machine (SVM) |
| 本文献已被 维普 万方数据 等数据库收录！ |
|
