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基于LMS(最小均方误差算法)的自适应滤波的源程序
- 基于LMS(最小均方误差算法)的自适应滤波的源程序，基于matlab-based on the LMS (minimum mean square error algorithm) adaptive filtering of the source, based on Matlab
最小均方误差算法
- 这是智能天线的最小均方误差算法程序，非常好用，使在matlab中实现的。
LMS.rar
- 用于计算最小均方误差的代码，包含了归一化的uniform函数,Used to calculate the minimum mean square error of the code, including the normalization of the uniform function
mmse
- 最小均方误差（MMSE）的算法用MATLAB的仿真-mmse
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
phase_detrending
- 相位对准技术，用多正弦波进行相位的校准，给出了最小均方误差的仿真图形-phase_detrending
lms
- 智能天线算发中的最小均方误差算法，运行后可以直接出结果-Smart Antenna count made in the MMSE algorithm, after running the results can be directly
lr_lmmse_estimation
- 基于最小均方误差的方法LMMMSE，对信道参数进行估计。-MMSE-based method LMMMSE, on the estimated channel parameters.
wiener_ch2
- 求解出在最小均方误差滤波器单位冲激函数h(n)。求解过程需要通过利用循环嵌套的编程思想，比较在逐次增加滤波器阶数的过程中得到的最小均方误差与最初设定的最小均方误差的阈值，当达到要求时，可以进一步确定滤波器的阶数。-how to use this function: [hx,hy]=wiener_ch2(w,N)
RLS
- RLS最小均方误差算法的自适应滤波程序及其应用-Least-mean-square error RLS adaptive filtering algorithm and its application procedure
MATLAB_Programming_LMS_Adaptive_Equalizer
- 一个MATLAB程序，用以实现基于最小均方误差算法的自适应均衡器，通常可以直接应用在数字通信系统中-A MATLAB program used to implement an LMS adaptive equalizer which can be directly applied in the digital communication systems
SNR_and_MSE
- mmse与snr的算法仿真，最小均方误差和最大信噪比，获得自适应算法的最优权，实现抗干扰-mmse snr algorithm and simulation, the minimum mean square error and maximum signal to noise ratio, the right of access to optimal adaptive algorithm to achieve anti-jamming
lms
- 本程序可用于实现最小均方误差算法-LMS algorithm
BP
- 神经网络的计算，包括训练和测试两部分，利用的是最小均方误差算法。-Nerual network calculation,including training and working part,utilizing MMSE algorithm.
LMS-RLSAdaptiveFilter
- 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 affect
Least Squares Maximum Likelihood as Algorithm
- 最小二乘，极大似然定位算法，其中包括二维和三维的最小均方误差定位算法以及连续定位算法(Least squares, maximum likelihood localization algorithm, which includes two-dimensional and three-dimensional minimum mean square error localization algorithm and continuous positioning algorithm)
BPSK通信系统均衡器仿真试验
- 报告第二部分给出了均衡器结构以及迫零均衡器和最小均方误差均衡器理论推导，第三部分 给出了均衡器的 Matlab 仿真；第四部分给出了两种均衡器的仿真结果及对比；附录给出了两种 均衡器的 Matlab 程序，总的程序，以及托普利兹矩阵与卷积作比较和自相关的计算。(The second part of the report gives the theoretical derivation of the equalizer structure and the zero-forcing equalize
OMLSA
- 这是目前传统单通道语音增强中效果最好的算法，作者Iseal Cohen大神,采用基于最小均方误差MMSE准则，代码里，噪声估计由最初的MCRA更新为效果更好的IMCRA。(This is the most effective algorithm for traditional single channel speech enhancement. The author, Iseal Cohen great God, uses the minimum mean square error MMSE c
LMS_estimation
- MATLAB对带噪声的信号进行最小均方误差估计，得到去噪声的信号。(MATLAB is used to estimate the minimum mean square error of the signal with noise, and the noise is obtained.)
LRSs
- 递归最小二乘(RLS)是一种自适应滤波算法，它可以递归地找到最小化加权线性最小二乘代价函数与输入信号相关的系数。这种方法与其他算法相比较，例如最小均方(LMS)，旨在减少均方误差。在RLS的推导中，输入信号被认为是确定性的，而对于LMS和类似的算法，它们被认为是随机的。(Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimiz