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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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本程序利用自适应LMS算法实现FIR最佳维纳滤波器。可用于观察影响自适应LMS算法收敛性，收敛速度以及失调量的各种因素-This procedure using adaptive LMS algorithm is optimal FIR Wiener filter. Can be used to observe the impact of adaptive LMS algorithm convergence, convergence speed and the amount of imbalan
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本文件介绍采用最小均方算法的自适应横向滤波器,pdf文件内含有相应的MATLAB程序及仿真结果等。-This document describes the use of least mean square adaptive transversal filter algorithm, pdf file containing the appropriate procedures and simulation results of MATLAB.
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提供自适应线谱增强函数。结合LMS算法和自适应滤波来实现线谱增强。实现受白噪声 (mu,sigma)污染的单频信号(frequency f)的增强。-function to perform adaptive line enhancement using LMS algorithm and an adaptive FIR filter。 ALE concept enhances a single tone signal (frequency f) affected by white noise (
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使用LMS算法实现的自适应滤波器范例，对一个加白噪声的正弦信号滤波。并且比较不同步长的滤波器的迭代次数。-LMS algorithm using adaptive filter example, a sinusoidal signal plus white noise filter. And less synchronized long filter iterations.
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介绍了一种用于ip电话的自适应回声消除器，采用LMS自适应滤波器实现。首先通过MATLAB进行LMS算法的步长选择,并用生成的符合G.168要求的带限CCS测试信号对回声消除器的性能进行了测试-Introduced a kind of adaptive echo cancellation ip phone device, using LMS adaptive filter. Carried out by MATLAB first step LMS algorithm selection, and
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this the echo cancelation using lms adaptive filter
-this is the echo cancelation using lms adaptive filter
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用MATLAB实现LMS自适应滤波器的e(n)^2的曲线及清楚LMS算法-LMS adaptive filter using MATLAB implementation of the e (n) ^ 2 and clear the curve of LMS algorithm
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the code contains adaptive filter using lms algorithm with zero mean and variance and it minimize the error and equals the output
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使用自适应滤波（LMS）算法，对受高斯白噪声干扰的正弦信号进行滤波。-Using the adaptive filter (LMS) algorithm, Gaussian white noise by sine signal filtering.
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利用lms自适应滤波器原理，实现波束形成。
波束形成器的零干扰容量随着迭代次数和干扰目标信号比的增大而改善。-Lms adaptive filter using the principle to achieve beamforming. Beamformer with the zero-interference capacity of the number of iterations and the target signal interference ratio increased to
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Matlab Code to filter data using the Least Mean Squares adaptive algorithm. processes an input WAV file and filters out noise according to the setup parameters
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speech signal i.e..wav file is compressed for proper enhancement using adaptive LMS filter and una.
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使用自适应滤波器实现未知系统识别，里面包括
RLS法和LMS法-Unknown system using an adaptive filter to achieve recognition, which includes
RLS method and the LMS method
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给出了kalman、RLS、LMS三种自适应滤波器的仿真matlab程序，在gVJmRJe环境下调试，三种滤波器都采用了10次迭代，平均CtPWTRQ参数性能良好，将仿真值与理论值进行了比较。-Given the Kalman and RLS and LMS three adaptive filter matlab simulation procedures, in the gVJmRJe environment debugging, three kinds of filters using t
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给出了kalman、RLS、LMS三种自适应滤波器的仿真matlab程序，在vqTFFhe环境下调试，三种滤波器都采用了10次迭代，平均iJYAEeY参数性能良好，将仿真值与理论值进行了比较。-Given the Kalman and RLS and LMS three adaptive filter matlab simulation procedures, in the vqTFFhe environment debugging, three kinds of filters using t
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给出了kalman、RLS、LMS三种自适应滤波器的仿真matlab程序，在hhfRXBj环境下调试，三种滤波器都采用了10次迭代，平均vSAtnCY参数性能良好，将仿真值与理论值进行了比较。-Given the Kalman and RLS and LMS three adaptive filter matlab simulation procedures, in the hhfRXBj environment debugging, three kinds of filters using t
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给出了kalman、RLS、LMS三种自适应滤波器的仿真matlab程序，在IixQFds环境下调试，三种滤波器都采用了10次迭代，平均DukvYML参数性能良好，将仿真值与理论值进行了比较。-Given the Kalman and RLS and LMS three adaptive filter matlab simulation procedures, in the IixQFds environment debugging, three kinds of filters using t
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给出了kalman、RLS、LMS三种自适应滤波器的仿真matlab程序，在umwIcVC环境下调试，三种滤波器都采用了10次迭代，平均wnWcrdQ参数性能良好，将仿真值与理论值进行了比较。-Given the Kalman and RLS and LMS three adaptive filter matlab simulation procedures, in the umwIcVC environment debugging, three kinds of filters using t
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给出了kalman、RLS、LMS三种自适应滤波器的仿真matlab程序，在RRoFbxS环境下调试，三种滤波器都采用了10次迭代，平均mjTXwXK参数性能良好，将仿真值与理论值进行了比较。-Given the Kalman and RLS and LMS three adaptive filter matlab simulation procedures, in the RRoFbxS environment debugging, three kinds of filters using t
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