改进SVSLMS算法在系统辨识中的应用及性能分析  

Application and performance analysis of improved SVSLMS algorithm in system identification

作　　者：邹宁[1] 徐松涛[1] 任国磊[2] 

机构地区：[1]空军工程大学工程学院,西安710038 [2]西安通信学院,西安710106

出　　处：《计算机工程与应用》2011年第10期229-232,共4页Computer Engineering and Applications

摘　　要：通过建立步长因子μ与误差信号e(n)之间的非线性函数关系,提出了一种改进的自适应可变步长最小均方(LMS)算法。该算法具有在误差e(n)接近0处缓慢变化的优点,克服了S函数变步长LMS算法在自适应稳态阶段μ取值偏大的缺点;具有初始阶段和未知系统时变阶段步长自动增大而稳态时步长很小的特点,解决了收敛时间和稳态误差的矛盾。将算法应用到系统辨识中,对比一般的变步长算法,改进的算法在平稳过程中具有更快的辨识速度和更小的稳态误差,同时还具有更好的跟踪时变系统的能力。By building a nonlinear function relationship between μ and the error signal e（n）,this paper proposes an improved variable step size LMS（Least Mean Square） adaptive filtering algorithm.This variable step size algorithm avoids the shortcoming of changing step size of SVSLMS（Variable Step Size LMS based on Sigmoid Function）.Also in the stage of adaptive steady state,it has the virtue of e（n） slightly changing at point close to zero.Meanwhile the algorithm efficiently overcomes the discrepancy between the convergence rate and the steady error.When applied to system identification,this algorithm constitutes a significant improvement in the identification speed with very small steady error in stationary environment and is of better tracking capability,as compared with the traditional algorithms with step size.

关 键 词：最小均方算法 变步长 自适应滤波 系统辨识 

分 类 号：TN911.7[电子电信—通信与信息系统]