SVD Filter Based On Noise Singular Values Clustering

摘要：

Aiming at determining the optical reconstruction rank of singular value matrix in SVD filter, a new method based on noise singular values clustering is proposed in this paper. Variable forward standard deviation (F-Std) has been defined and the mutation point in F-Std is used to separate signal singular values from noise singular values. Experiments have been simulated by some noisy signals using the new SVD filter and other two commonly used methods, the results and root mean square errors of these filters are shown that the new SVD filter is not only optimal or near to optimal and more effective than the two methods but also robust to the shape of the trajectory matrix even when the signals SNR varies from very high to -11.7dB.

关键词： singular value decomposition noise singular value clustering forward standard deviation root square mean error

作者: FAN Di LV Changzhi CAi Qinguang

作者单位: Shandong University of Science and Technology, Qingdao, 266510, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 3027-3030

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）