欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
以主成份分析、局部保持及核映射理论为基础,提出了一种核化有全局性类内近邻保持正交算法。该算法的目标函数融合了样本的全局与局部信息,同时由于采用非线性映射及基向量的正交性限制,因此能够提取出更为有效的分类特征。但由于非线性函数的未知,因此无法直接对准则函数进行求解,对此根据核映射理论,本文将算法的不可解的准则函数转化为核空间上可解的准则函数,并给出了具体的理论推导及求解步骤。人脸库上的实验结果表明所提方法的有效性。
英文摘要：
Based on the principal component analysis, locality preserving projection and kernel mapping theory, kernel within-class neighborhood preserving orthogonal algorithm with global structure is proposed. The object function of proposed method takes the global and local information of the samples into account. At the same time, by using nonlinear mapping and the orthogonal restriction of base vectors, this algorithm can extract more effective classification features. Being unknown nonlinear function, the object function can not be directly calculated. But according to the kernel mapping theory, the equivalent object function of the proposed algorithm is established in the kernel feature space. The deducing process and solving steps are given. Experimental results on face database demonstrate the effectiveness of the proposed method.
同期刊论文项目
同项目期刊论文
期刊信息
位置：