An Improved Noise Reduction Algorithm Based on Manifold Learning and Its Application to Signal Noise Reduction

摘要：

In the noise reduction algorithm based on manifold learning, phase space data may be distorted and reduction targets are chosen at random, it made efficiency and effect of noise reduction lower. To solve this problem, a improved noise reducation method (local tangent space mean reconstruction) was proposed. The process of global array by affine transformation will be replaced with mean reconstruction, and the intrinsic dimension was estimate as dimension of reduction targets by using maximum likehood estimation method, the data in addition to intrinsic dimension space will be eliminated. Noise reduction experiment to fan vibration signal with noise shows this method had better noise reduction effect.

关键词： manifold learning local tangent space Arrangement noise reduction

作者: Guangbin Wang Liangpei Huang

作者单位: Institute of Vibration, Shock and diagnosis, Hunan University of Science and Technology, Xiangtan 411201, china

会议类型: 国际会议

会议名称: 2010 International Conference on Advanced Mechanical Engineering(2010年先进机械工程国际学术会议 AME 2010)

会议地点: 洛阳

会议语种:英文

页码: 653-656

在线出版日期: 2010-09-04（万方平台首次上网日期，不代表论文的发表时间）