非平稳信号的递推最小二乘盲分离
Recursive least-squares algorithm for blind separation of nonstationary signals
摘要点击 1598  全文点击 1431  投稿时间:2010-01-04  修订日期:2010-05-08
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DOI编号  10.7641/j.issn.1000-8152.2011.5.CCTA100010
  2011,28(5):735-740
中文关键词  盲分离  非平稳信号  递推最小二乘  遗忘因子
英文关键词  blind source separation  nonstationary signal  recursive least-squares  forgetting factor
基金项目  国家安全重大基础研究资助项目(61355020301).
作者单位E-mail
徐洪涛 第二炮兵工程学院 304教研室 xuhongtaoppp@163.com 
王跃钢 第二炮兵工程学院 304教研室  
陈霞 第二炮兵工程学院 403教研室  
中文摘要
      针对非平稳信号盲分离问题提出了一种基于递推最小二乘(RLS)算法的非平稳信号盲分离新方法. 首先引入遗忘因子对常规代价函数进行指数加权修正, 得到一种新的具有递归结构的代价函数; 然后利用RLS算法最小化代价函数, 推导最优分离矩阵的自适应更新算法, 逐步实现信号分离. 该算法避免了最小二乘类算法关于学习速率选择困难的缺点, 具有收敛速度快、稳定性好等优点. 仿真实验验证了算法的有效性.
英文摘要
      For the blind separation of nonstationary signals, we propose a new method which is based on the recursive least-squares(RLS) algorithm. A forgetting factor is introduced to modify the normal cost-function by incorporating the exponential weighting-factors to obtain a new cost-function with a recursive structure. This new cost-function is minimized by using RLS algorithm. An adaptive updating algorithm is derived for the optimal separation matrix which is for gradually separating the signals. This algorithm alleviates the difficulty in selecting the learning speed in the least-mean-squares algorithms, and possesses excellent performances in convergence and stability. Simulations are carried out to verify the validity of the new algorithm.