CAJ | 학술논문

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.
이주성빈분석、국부보지급핵영사이론위기출,제출료일충핵화유전국성류내근린보지정교산법.해산법적목표함수융합료양본적전국여국부신식,동시유우채용비선성영사급기향량적정교성한제,인차능구제취출경위유효적분류특정.단유우비선성함수적미지,인차무법직접대준칙함수진행구해,대차근거핵영사이론,본문장산법적불가해적준칙함수전화위핵공간상가해적준칙함수,병급출료구체적이론추도급구해보취.인검고상적실험결과표명소제방법적유효성.
Based on the principal component analysis, 1ocality 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.