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f_lms
- 均衡技术是克服码间干扰(Inter-Symbol Interference,ISI)的有效措施,由于信道特性的随机性与时变性,实际中消除码间干扰最常用的是自适应均衡器。本文对基于最小均方(Least Mean Squares,LMS)算法和递推最小二乘(Recursive Least Squares,RLS)算法的自适应均衡器进行仿真研究,分析了信道特性与设计参数对自适应均衡器的收敛速度与稳态性能的影响。 -Equalization technique is to overcome inte
LMS_NLMS_RLS
- 基于RLS算法，NLMS和LMS的自适应滤波器的MATLAB程序-LMS and RLS algorithm performance comparisons, including the right value compared with the
RLS
- 基于RLS算法的自适应线性预测,matlab代码，可以一用-Adaptive linear prediction based on RLS algorithm, matlab code, one can use
RLS2
- RLS多次仿真实验的对比分析，matlab下可以直观体现-RLS comparative analysis of several simulation, matlab visual expression
RLS_LMS
- 通过分析介绍自适应滤波器中经典算法LMS与RLS的异同，并且运用matlab进行仿真，使得初学者对于matlab在仿真过程的运用有更为直观的理解。并且对于自适应滤波有更清晰的认识。-By analyzing the introduction of classical adaptive filter algorithm LMS and RLS similarities and differences, and the use of matlab simulation, matlab for beg
rlsfilter1
- 一种rls算法自适应滤波器在MATLAB中的实现-One kind rls adaptive filter algorithm implemented in MATLAB
3
- 对基于LMS(最小均方)、NLMS（归一化最小均方）、RLS（递归最小二乘）算法的自适应噪声抵消系统进行MATLAB仿真，发现这几种算法都能从高背景噪声中有效地抑制干扰提取出有用信号，显示出了良好的的收敛性能，相比之下RLS算法去噪效果较好，呈现出更快的收敛速度，更强的稳定性和抑噪能力(the principle of LMS (minimum mean square), NLMS (normalized least mean square), RLS (recursive least squa