计算机工程与应用2017，Vol.53Issue(1)：39-43,5.DOI:10.3778/j.issn.1002-8331.1503-0137
基于粒子群算法的LDA实现方法研究
Research on implementation method of LDA algorithm based on Particle Swarm Optimization
摘要
Abstract
A novel linear discriminant analysis implementation method is presented to overcome the shortcomings of the traditional LDA algorithm after researching the existing theoretical results. This method amends the Fisher criterion at first, then finds the best discriminant vectors by iteration, analyzes and evaluates them at last. The experimental results on the facial expression recognition using the JAFFE expressions library and the comprehensive evaluation of regional con-sumption levels show that the PSO-LDA algorithm not only has well recognition effect, but also can break through the re-striction of the sample dimension. Compared with other improved LDA algorithm, it’s more flexible, and easier to imple-ment.关键词
线性判别式分析/投影矢量/离散度矩阵/粒子群算法/PSO-LDA算法Key words
Linear Discriminant Analysis(LDA)/projection vector/matrix of the discrete degree/Particle Swarm Optimi-zation(PSO)/PSO-LDA algorithm分类
信息技术与安全科学引用本文复制引用
钟伟,黄元亮,郝真真,姜甜甜..基于粒子群算法的LDA实现方法研究[J].计算机工程与应用,2017,53(1):39-43,5.基金项目
广东省科技计划项目（No.2013B010401019）；珠海市公共平台项目（No.2013D0501990002）。 （）
