Description: 基于lms算法的X-LMS算法，比较适合实际模型-LMS algorithm based on X-LMS algorithm, more suitable for the actual model Platform: |
Size: 1024 |
Author:安哲 |
Hits:
Description: 若不希望用与估计输入信号矢量有关的相关矩阵来加快LMS算法的收敛速度，那么可用变步长方法来缩短其自适应收敛过程，其中一个主要的方法是归一化LMS算法（NLMS算法），变步长 的更新公式可写成
W（n+1）=w（n）+ e（n）x（n）
=w（n）+ （3.1）
式中， = e（n）x（n）表示滤波权矢量迭代更新的调整量。为了达到快速收敛的目的，必须合适的选择变步长 的值，一个可能策略是尽可能多地减少瞬时平方误差，即用瞬时平方误差作为均方误差的MSE简单估计，这也是LMS算法的基本思想。
-Want to estimate if the input signal vector and the relevant matrix to speed up the convergence rate of LMS algorithm, then the variable step size method can be used to shorten its adaptive convergence process, one of the main method is normalized LMS algorithm (NLMS algorithm) , variable step-size update formula can be written W (n+ 1) = w (n)+ e (n) x (n) = w (n)+ (3.1) where, = e (n) x (n) the right to express filter update vector iterative adjust the volume. In order to achieve the purpose of fast convergence, we must choose the appropriate value of variable step size, a possible strategy is as much as possible to reduce the instantaneous squared error, which uses the instantaneous squared error as the mean square error MSE of the simple estimate, which is the basic LMS algorithm思想. Platform: |
Size: 3072 |
Author:闫丰 |
Hits:
Description: 功能描述：测试LMS与RLS算法，比较两种算法的收敛特性
文件名：LMS_RLS_sim.m
测试用例：
x(n)+a1*x(n-1)+a2*x(n-2)=e(n)，a1=-1.6,a2=0.81,e(n)为高斯白噪声
文件输出：系数a1的值
调用函数：function [A] = LMS_Algo(M,N,mu,xn)
被调用：无
作者：mingcheng
编写时间：2009-10-13
修改时间：2009-10-13
版本：V1.0 - Function Description: Test LMS and RLS algorithm, the convergence characteristics were compared file name: LMS_RLS_sim.m test case: x (n)+ a1* x (n-1)+ a2* x (n-2) = e (n), a1 =- 1.6, a2 = 0.81, e (n) is Gaussian white noise file output: the value of coefficient a1 call the function: function [A] = LMS_Algo (M, N, mu, xn) is called: No of: mingcheng write time :2009-10-13 modified :2009-10-13 version: V1.0 Platform: |
Size: 1024 |
Author:赵明诚 |
Hits:
Description: 数字信号处理，LMS和RLS实例：给定正弦信号s(n)，现在我们获得得是受影响的数据x(n)=s(n)+v(n) ， v(n)为方差1.25的告示白噪声信号，请设计一个滤波器，使其输出与s(n)的均方误差最小，并给出用LMS和RLS算法的自适应求解方法的MATLAB仿真。-Digital signal processing, LMS and RLS instance: Given a sinusoidal signal s (n), now we get the data have affected x (n) = s (n)+ v (n), v (n) 1.25 for the variance Notice the white noise signal, to design a filter so that the output and s (n) The minimum mean square error, and gives the algorithm with the LMS and RLS adaptive method for solving the MATLAB simulation. Platform: |
Size: 1024 |
Author:codeshare |
Hits:
Description: 使用matlab编写的一种优化的lms算法 xlms算法,比lms算法更精准-Lms algorithm using an optimized algorithm matlab prepared xlms more accurate than lms algorithm Platform: |
Size: 1024 |
Author:孟琦 |
Hits:
Description: 用MATLAB编写的lms算法，设置变量和参量，赋，对于一组输入样本x(n)和对应的期望输出d-MATLAB prepared by the LMS algorithm, set variables and parameters, Fu, for a set of input samples x (n) and the corresponding expected output D Platform: |
Size: 1024 |
Author:江东 |
Hits:
Search - x-lms algorithm matlab