基于核融合的多信息流形学习算法  

Multi-information manifold learning algorithm based on kernel fusion

作　　者：刘元[1] 吴小俊[1] 

机构地区：[1]江南大学物联网工程学院,江苏无锡214122

出　　处：《计算机应用研究》2016年第3期673-676,共4页Application Research of Computers

基　　金：国家自然科学基金资助项目(61373055);高等学校博士学科点专项科研基金资助项目(20130093110009)

摘　　要：流形学习算法可分为全局流形学习与局部流形学习,它们分别保持了流形上的全局特征信息与局部特征信息,但是实验证明仅基于全局特征或局部特征信息的流形学习算法不能很好地保持真实的流形结构,影响了学习效果。基于流形学习的核的视角,融合了全局流形学习算法ISOMAP与局部流形学习算法LTSA的核矩阵,提出了可以同时保持流形结构的全局特征信息与局部特征信息的流形学习算法。在人工数据集和人脸图像集上的仿真实验验证了该算法的有效性。Manifold learning algorithms can be divided into global manifold learning and local manifold learning,and they keep global features and local features of manifolds respectively. However,experiments show that manifold learning algorithm based only on global or local feature information can not maintain the real structure of manifold well which affects the results of manifold learning. Therefore,in the view of kernel,this paper proposed a multi-information manifold learning algorithm based on the kernel fusion of the ISOMAP and LTSA. The proposed algorithm can maintain the global and local features of manifolds synchronously,and the experimental results on several synthetic data and standard face databases indicate the effectiveness of the algorithm.

关 键 词：核融合 流形学习 多信息 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TP301.6[自动化与计算机技术—控制科学与工程]