计算机工程2012，Vol.38Issue(19)：175-178,4.DOI:10.3969/j.issn.1000-3428.2012.19.045
基于神经网络和主元分析的人脸识别算法
Face Recognition Algorithm Based on Neural Network and Principal Component Analysis
摘要
Abstract
According to the high dimension, small sample classification problem, this paper puts forward two important criterions to estimate the initial width of RBF unit. Principal Component Analysis(PCA) method used the training sample set is projected onto the eigenface space, in order to reduce the dimensionality, using Fisher linear discriminant to generate a group of the most discriminant features, different classes of the training data can be separated as much as possible, and the same samples are as close as possible. The results prove that this algorithm both in the classification error rate or in the learning efficiency can show excellent performance.关键词
人脸检测/特征提取/人脸识别/聚类算法/神经网络/主元分析Key words
face detection/ feature extraction/ face recognition/ clustering algorithm/ neural network/ principal component analysis分类
信息技术与安全科学引用本文复制引用
何正风,孙亚民..基于神经网络和主元分析的人脸识别算法[J].计算机工程,2012,38(19):175-178,4.基金项目
广东省自然科学基金资助项目(S2011020002719,10152800001000016) （S2011020002719,10152800001000016）
