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包括：三种LMS算法实现AR(2)的预测，法2、3用递推计算Km,两者区别在于d(n)的取法略微不同；用LSL和FTF算法实现简单的系统辨识。-Include: three LMS algorithm AR (2) the forecast, France 2,3 calculated with recursion Km, whichever is the difference between d (n) of a slightly different取法 LSL and the FTF al
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基于lms的系统辨识的matlab仿真有点小问题-Based on the LMS system identification of the matlab simulation a bit small problem
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基于LMS算法的自适应回波抵消器算法 用于未知系统识别-Based on LMS Algorithm for Adaptive Echo Cancellation Algorithm for unknown system identification
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应用LMS算法，用Matlab编程实现系统识别.-Application of LMS algorithm, using Matlab programming system identification.
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LMS Algorithm for System Identification-LMS Algorithm for System Identification..........
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简单的最小二乘逼近算法，用于系统辨识，方便修改噪声参数和系统参数，为系统辨识和仿真作业的源代码。-Simple least-squares approximation algorithm for system identification to facilitate the modification of system parameters and noise parameters for the system identification and simulation of the sourc
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System identification with adaptive filter using full and partial-update Least-Mean-Squares -System identification with adaptive filter using full and partial-update Least-Mean-Squares
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LMS Algorithm Demo - A system identification by the usage of the LMS algorithm.-LMS Algorithm Demo- A system identification by the usage of the LMS algorithm.
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FIR_A=[1 1 2]
FIR_B=[2 1 1]
function [w_out mse_out ref_out] = LMS(FIR_A,FIR_B,1,wave=square)
[w mse ref res iter] = LMS(FIR_A,FIR_B,L,wave)
LMS filter to solve the system identification problem represented below:
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最小均方算法是一种自适应滤波算法，这里的Matlab程序用于根据LMS最新均方识别一个线性噪声系统-LMS algorithm is an adaptive filter algorithm, where the Matlab program for the latest according to the mean square LMS noise system identification of a linear
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this program demonstrates the use of the LMS algorithm in system identification
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LMS算法实现系统辨识
LMS-Newton算法实现系统辨识
SER算法实现系统辨识
LMS-Lattice算法实系统辨识
SER-Lattice算法实现系统辨识-Lms
Lmsnewton
SER
LMS-lattice
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利用lms算法和rls算法，对通过给定系统h的随机信号进行自适应滤波，通过抽头w对系统进行逆辨识与辨识，同时产生MSE 即均方误差，来描述对信号恢复的效果。-Using lms algorithm and rls algorithms h through a given system adaptive filtering of random signals, the system through the tap w reverse identification and recognition,
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自适应信号处理中的格型LMS算法，并与横向LMS做了比较。应用环境是系统辨识-lattice LMS algorithm of adaptive signal processing were compared with the horizontal LMS algorithm. Application environment is the system identification
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一个使用lms算法的系统识别，用于识别线性噪声系统-Lms algorithm system identification
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一个经典的LMS系统识别的实施，包含输入信号的多个选项-A classic implementation of the LMS system identification, with multiple options of the input signal
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These are codes for system identification using various algorithm like LMS,RLS,PSO+FLA-These are codes for system identification using various algorithm like LMS,RLS,PSO+FLANN
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基本LMS算法，归一化LMS算法，基于LMS算法的系统辨识-Basic LMS algorithm, the normalized LMS algorithm, LMS algorithm based system identification
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用Matlab实现自适应信号处理中的系统辨识，自适应处理器采用自适应线性组合器，未知被控系统采用AR model。用了LMS算法和最速下降法实现。-Realise system identification in adaptive signal processing with matlab.The LMS algorithm and Speedest Descent method are used.
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lms自适应算法源码，同时完成系统辨识仿真(LMS adaptive algorithm source code, at the same time complete system identification simulation)
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