非平稳信号的的递递推最小二乘盲分离  

Recursive least-squares algorithm for blind separation of nonstationary signals

作　　者：徐洪涛[1] 王跃钢[1] 陈霞[2] 

机构地区：[1]第二炮兵工程学院304教研室,陕西西安710025 [2]第二炮兵工程学院403教研室,陕西西安710025

出　　处：《控制理论与应用》2011年第5期735-740,共6页Control Theory & Applications

基　　金：国家安全重大基础研究资助项目(61355020301)

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.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.

关 键 词：盲分离 非平稳信号 递推最小二乘 遗忘因子 

分 类 号：TN911.7[电子电信—通信与信息系统]