An implementation of seir based on multiple eigenspaces , namely seme , is also proposed in this paper 该方法基于一种部分的k - l变换，或者称为主成分分析pca 。
2.
Seme is analyzed and compared with eigenface , pca lda , eigenfeature , and eigenface eigenfeature through experiments . the experimental results show that seme achieves the best performance 本征脸方法取得了如此巨大的成功，以至于成为了人脸识别算法的事实标准和相比较的基准点。
3.
In section 1 , some nonlinear wave equations of this part discussing are recommended ; in section 2 , the elementary tool of this part utilizing is mentioned , namely , the hyperbolic function method ; in section 3 , seme exact solitary wave solutions to these nonlinear wave equations are attained 本部分由三节组成，第一节介绍了所讨论的几类非线性波动方程；第二节介绍了本部分所使用的基本工具，即，双曲函数方法；第三节给出了这些非线性波动方程的若干精确孤立波解。
