期刊文献+

基于局部切空间偏离度的自适应邻域选取算法 被引量:4

Adaptive Neighborhood Selection Algorithm Based on Deflection Angle of Local Tangent Space
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摘要 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. 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.
出处 《模式识别与人工智能》 EI CSCD 北大核心 2010年第6期815-821,共7页 Pattern Recognition and Artificial Intelligence
基金 国家自然科学基金(No.60372071) 辽宁省教育厅高等学校科学研究基金(No.2004C031)资助项目
关键词 局部切空间 偏离度 正交投影 噪音 Local Tangent Space Deflection Angle Orthogonal Projection Noise
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参考文献8

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同被引文献51

  • 1杨剑,李伏欣,王珏.一种改进的局部切空间排列算法[J].软件学报,2005,16(9):1584-1590. 被引量:36
  • 2程军圣,于德介,杨宇.基于EMD和SVM的滚动轴承故障诊断方法[J].航空动力学报,2006,21(3):575-580. 被引量:31
  • 3王和勇,郑杰,姚正安,李磊.基于聚类和改进距离的LLE方法在数据降维中的应用[J].计算机研究与发展,2006,43(8):1485-1490. 被引量:31
  • 4阳建宏,徐金梧,杨德斌,黎敏.基于主流形识别的非线性时间序列降噪方法及其在故障诊断中的应用[J].机械工程学报,2006,42(8):154-158. 被引量:31
  • 5TENENBAUM J B, DE SILVA V, LANGFORD J C. A global geometric framework for nonlinear dimensionality reduction [ J ]. Science, 2000,290 (5500) :2319-2323.
  • 6VIACHOS M, DOMENICONI C, GUNOPULOS D, et al. Non-linear dimensionality reduction techniques for classi- fication and visualization [ C ]. Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, USA, 2002: 645-651.
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  • 8JIANG Q SH,JIA M P,HU H,et al. Machinery fault diagnosis using supervised manifold learning [ J ]. Mechanical Systems and Signal Processing, 2009, 23 ( 7 ): 2301-2311.
  • 9LI M, XU J W, YANG J H, et al. Multiple manifolds analysis and its application to fault diagnosis [ J ]. Mechanical Systems and Signal Processing, 2009, 23 ( 8 ): 2500-2509.
  • 10LEI Y G,ZUO M J. Gear crack level identification based on weighted K nearest neighbor classification algorithm [J]. Mechanical Systems and Signal Processing,2009,23 (5) : 1535-1547.

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