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

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 consumption levels show that the PSO-LDA algorithm not only has well recognition effect, but also can break through the restriction of the sample dimension. Compared with other improved LDA algorithm, it’s more flexible, and easier to implement.

Key words: Linear Discriminant Analysis(LDA), projection vector, matrix of the discrete degree, Particle Swarm Optimization(PSO), PSO-LDA , algorithm