现代电子技术2013，Vol.36Issue(1)：11-14,4.
ODNPP降维算法在毫米波探测器目标识别中的应用
ODNPP dimension reduction algorithm for recognition of millimeter wave detector target
摘要
Abstract
On the basis of neighborhood preserving projection algorithm, a new dimensionality reduction algorithm based on manifold learning named orthogonal discriminant neighborhood preserving projections (ODNPP) is proposed in this paper. The algorithm making full use of the class information of samples increases class scatter constraint in the objective function and intro-duces orthogonalization processing to calculate orthogonal projection matrix. ODNPP algorithm, NPP, NPDP and ONPP are ap-plied respectively in the simulation experiment of millimeter wave detector target recognition, and the experimental results show that ODNPP algorithm can find low dimensional manifold that embedded in the observed data of high dimensional space. ODNPP algorithm is used to reduce the dimensionality of the feature, and the reduced features can obtain higher recognition rates.关键词
降维/流行学习/毫米波探测器/目标识别Key words
dimensionality reduction/manifold learning/millimeter wave detector/target recognition分类
信息技术与安全科学引用本文复制引用
张蓉蓉,李跃华..ODNPP降维算法在毫米波探测器目标识别中的应用[J].现代电子技术,2013,36(1):11-14,4.基金项目
国防预研项目资助(9140A05070910BQ02) （9140A05070910BQ02）
