基于局部切空间偏离度的自适应邻域选取算法

基于对局部切空间的几何性质的理论研究结果，提出一种基于局部切空间偏离度的自适应邻域选取算法。该算法基于局部切空间的正交投影计算局部中心化样本点与其切空间的夹角，更好地刻画出局部切空间的性质，能够区分不属于该邻域的样本点，同时具有较好的抗噪音能力。该算法是对该领域研究中的局部切空间排列算法的一个有效改进，具有局部高曲率的流形学习功能。实验证实该算法的有效性。

Adaptive Neighborhood Selection Algorithm Based on Deflection Angle of Local Tangent Space

An adaptive neighborhood selection algorithm is proposed based on deflection angle of local tangent space by using the geometric properties of local tangent space. It computes the angle between local centralized samples and its tangent space based on the orthogonal projection of local tangent space. It depicts the properties of local tangent space better, and discriminates the samples which do not belong to this neighborhood and possesses better antinoise ability. The proposed algorithm is a modification to local tangent space alignment with manifold learning function of local high curvature. Experimental results show that the proposed algorithm is effective.