广东工业大学学报2012，Vol.29Issue(2)：89-93,5.DOI:10.3969/j.issn.1007-7162.2012.02.018
一种基于l1范数的欠定盲源分离算法
An Algorithm for Underdetermined Blind Source Separation Based on l1-norm
谢忠德1
作者信息
- 1. 广东工业大学应用数学学院,广东广州510520
- 折叠
摘要
Abstract
A new two-step algorithm for underdetermined source separation is proposed. Mixing matrix was estimated via clustering methods based on potential functions. Sources were estimated by means of a fast sparse reconstructed algorithm. Every solution to the system equation As(t) =x(t)was expressed as the sum of one of its special solution and a group of linear combination of the basic solution to the corresponding homogeneous linear equation , The number of independent variable needed for estimation was reduced from n to n-m. Blind source separation of signals was done by means of sparse representation. The new algorithm is easily implemented and runs fast, which can well meet the requirements of the blind separation for speed. Simulation experiments show that the proposed algorithm has very good separation efficiency and precision.关键词
欠定盲源分离/势函数/l1范数优化模型/稀疏表示Key words
underdetermined blind source separation/ potential function/ /'-norm optimization model/ sparse representation分类
信息技术与安全科学引用本文复制引用
谢忠德..一种基于l1范数的欠定盲源分离算法[J].广东工业大学学报,2012,29(2):89-93,5.
