搜索资源列表
channelestmation
- 本程序比较了LS(最小二乘）和最小均方误差准侧下OFDM信道估计的误码率，给出了LS及MESE实现的源程序，是信道估计初学者的理想参考资料-This procedure compares the LS (least squares) and minimum mean square error of quasi-lateral channel estimation of OFDM bit error rate, given the realization of the LS and the MES
SER_LMS
- SER（序贯回归算法）和LMS（最小均方算法）的matlab仿真及对比-SER (Sequential regression algorithm) and the LMS (least mean square) of matlab simulation and comparison
wienerfilter
- 通过计算机MATLAB仿真分析和研究了维纳滤波器的阶数、信号的噪声方差、随机信号的采样点数、经过维纳滤波的均方误差之间的关系-MATLAB simulation by computer analysis and research of Wiener filter order, the signal of the noise variance, random signal sampling points, after Wiener filter mean square error of the r
nlms
- Normalized Least mean square algorithm in matlab
LMS-MATLAB
- LMS-MATLAB最小均方算法的Matlab源程序,模式识别中的分类器-LMS-MATLAB least-mean-square algorithm of Matlab source code, Pattern Recognition Classifier
Adaptive_Filters_Theory_and_Applications
- Least Mean Square Newton Algorithm
Least-square-filtering
- 这个包中包含学习最小均方滤波的一个例子及其和其它滤波方法的一些比较。-This package contains the learning of least mean square with an example. And it compared least mean square method with other filtering methods.
lms1
- 智能天线方向图——波束形成最小均方(LMS)算法-Smart antenna pattern- beam forming least mean square (LMS) algorithm
LMS
- Least Mean Square (LMS) equalizer used in coherent receivers
delta
- MATLAB code on linear minimum mean square error (LMMSE) estimation and its application to the problem of channel equalization in digital communication systems. amr amin: code on the application of channel equalization in digital communication sys
dm_demo
- MATLAB code on linear minimum mean square error (LMMSE) estimation and its application to the problem of channel equalization in digital communication systems. amr amin: code on the application of channel equalization in digital communication sys
Untitled
- MATLAB code on linear minimum mean square error (LMMSE) estimation and its application to the problem of channel equalization in digital communication systems. amr amin: code on the application of channel equalization in digital communication sys
ENEE634_report1
- Least Mean Square algorithm
s882211MatlabProject
- Least Mean Square using matlab
leastsquare
- Inter-symbol interference if not taken care off may cause severe error at the receiver and the detection of signal becomes difficult. An adaptive equalizer employing Recursive Least Squares algorithm can be a good compensation for the ISI probl
image
- 利用图像处理工具箱实现均方误差（MSE）、峰值信噪比（PSNR）和熵的源代码-By image processing toolbox to achieve the mean square error (MSE), peak signal to noise ratio (PSNR) and the entropy of the source code
zishiyingjiangzao
- 这里介绍了一种基于自适应滤波的噪声抵消法，采用归一化最小均方误差算法，采集实际噪声环境下各种不同信噪比的带噪语音样本进行降噪处理，实验结果表明，处理后信号的信噪比得到了较大程度的提高，大大改善了听音效果，具有很高的可懂度，且语音自然度好，没有失真；并与谱减法进行了比较，自适应噪声抵消法的降噪幅度比谱减法有一定提高，在听音效果上，用自适应噪声抵消法处理后的语音在清晰度，自然度方面优于谱减法。-Here a novel adaptive noise cancellation method using
LMS
- matlab中的LMS算法 采用LMS最小均方算法进行智能天线的仿真-Matlab LMS algorithm Adopt LMS least mean-square algorithm simulation of smart antenna
LS-LMMSE-Estimation
- LS (Least Square) & LMMSE (Minimum Mean Square Error)
Root-mean-square
- 均方根值趋势图，经本人试用，完全能够求解特征熵-Root mean square trend chart, through my trial, fully able to solve the characteristic entropy