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

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

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.