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LMS最小均方自适应滤波算法仿真，绝对可靠-LMS least mean square adaptive filter algorithm simulation, absolutely reliable
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一种变步长的归一化最小均方自适应滤波算法的实现-A variable step size normalized least mean square adaptive filter algorithm to achieve
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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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Adaptive noise cancelation unit with LMS(Least Mean Square)filter
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Least Mean Square System Identification from Adaptive Filter Theory
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摘要:分析了最小均方误差滤波和递归最小二乘滤波算法、自适应滤波的神经网络方法、
基于QR分解的方法、统一模型下的自适应滤波及基于高阶累积量的自适应算法的优缺点，并对自适应滤波算法的未来发展做了展望。
-the author analyzes the minimum mean square error filter and recursive least square filter algorithm, an adaptive filter neural network method,
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LMS自适应滤波器是使滤波器的输出信号与期望响应之间的误差的均方值为最小，因此称为最小均方（LMS）自适应滤波器，这个是LMS在matlab的m文件，使用方便-LMS adaptive filter is the mean square value of the minimum error between the filter output signal and desired response, so called least-mean-square (LMS) adaptive filte
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在基于Mean-Shift的目标跟踪算法中，尺度自适应机制是算法研究的一个重要方向。一种典型的方法采
用Lindeberg的尺度空间理论以获取目标尺度信息。但现有算法中将尺度由2．D矢量压缩为1一D量，未能精细地
刻画目标仿射变换时的尺度变化，从而限制了算法的适用范围。为此，该文将尺度维1．D滤波推广至2一D，构造得
到了相应的垂D尺度空间，并利用窄间维和尺度维的Mean-Shift交替迭代，实现了同时在空间位置和尺度方向对
目标的有效跟踪，提高了算法在目标尺度变化时的自适应性，
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MATLAB的图像处理基础的资料\3
程序代码说明
P0301：数字图像矩阵数据的显示及其傅立叶变换
P0302：二维离散余弦变换的图像压缩
P0303：采用灰度变换的方法增强图像的对比度
P0304：直方图均匀化
P0305：模拟图像受高斯白噪声和椒盐噪声的影响
P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波
P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波
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自适应滤波器的原理和最小均方(LMS)算法，利用MATLAB实现了自适应系统辨
识和自适应干扰抵消-the theory of Adaptive Filter and LMS(1east mean square)algorithm．
Meanwhile，it manages to use MATLAB to realize the adaptive system identifier and interference cancella—
tion．
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自适应滤波程序，选用的是维纳滤波、最小二乘法、最陡下降法、均方最小二乘法等-Adaptive filtering process, the choices are the Wiener filter, least squares method, steepest descent method, mean square least squares method
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lms滤波算法的MATLAB源代码,lms为变步长最小均方自适应滤波算法-matlab source code of lms algorithm. lms is the least mean square adaptive filter algorithm
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自适应LMS（最小均方误差）滤波器。（改变步长检查收敛速率）-Adaptive LMS (minimum mean square error) filter
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线性最小均方自适应滤波器设计Matlab程序。-Linear minimum mean square adaptive filter design
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The Recursive least squares (RLS) is an adaptive filter which recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This is in contrast to other algorithms such as the least mean
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Adaptive Noise Canceler algorithm using Least Mean Square
(LMS) filter implemented in MATLAB
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LMS自适应滤波器算法的matlab程序 最小均方算法 Least mean square-LMS adaptive filter algorithm matlab program LMS algorithm Least mean square
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RLS 递归最小二乘滤波器算法！！！！！！！！！！！！！！！！！！！！！(Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This approach is in
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考虑次级声反馈的自适应滤波器算法，基本原理是最小均方误差(Filter X Least Mean Square adaptive filter)
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信道均衡的MATLAB程例，是一个很好的例子，对于做通信信道仿真研究的就有较高的参考和使用价值。(In this example we have a typical channel equalization scenario. We want
to estimate the transmitted sequence with 4-QAM symbols. In
order to accomplish this task we use an ad
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