Research on Sparse Component Analysis and Its Application

摘要：

Sparse component analysis is a signal processing method based on sparse representation. It is widely used in underdetermined blind signal separation. When estimating the mixing matrix, the aliasing level of the mixed-signal scatter at the origin center is too high, and it will affect the accuracy of estimating the mixing matrix. In this paper, in order to overcome the shortcoming, a new “Vanish Circle Kmeans clustering algorithm that can estimate the mixing matrix more effectively is proposed, combined with time-frequency analysis to achieve the instantaneous linear aliasing blind separation signals and obtain a good separation effect.

关键词： Sparse component analysis Vanish circle K-means Underdetermined blind separation Time-frequency analysis

作者: Weijie Zhao Mingrong Ren Yating Zhang

作者单位: College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China

会议类型: 国际会议

会议名称: 2010 International Conference on Image Analysis and Signal Processing(2010 图像分析与信号处理国际会议 IASP 10)

会议地点: 厦门

会议语种:英文

页码: 430-433

在线出版日期: 2010-04-12（万方平台首次上网日期，不代表论文的发表时间）