搜索资源列表
ls_mmse_chestimation_ofdm
- 最小二乘，最小均方误差的OFDM信道估计MATLAB代码-least squares, the minimum mean square error of OFDM channel estimation MATLAB code
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
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
objective_evaluation
- 图像评价的几个标准，包括峰值信噪比，均方误差，平均绝对误差，图像保真度，信噪比的MATLAB代码，采用基本编程方法，适合初学者加深图像客观评价标准的理解。-Image evaluation of several criteria, including PSNR, MSE, mean absolute error, image fidelity, signal to noise ratio of the MATLAB code, using the basic programming for be
MUD
- 比较传统单用户检测、线性解相关多用户检测、最小均方误差多用户检测的误码率函数MUD.m-mud.m
wwwww
- 自适应滤波器的MATLAB程序，基于最小均方误差原理。-digital signal processing
lms1
- 自适应滤波器算法与实现——最小均方误差LMS-Adaptive filter algorithm- least-mean-square error LMS
LMSandVSLMS
- 本程序对两种固定步长和一种变步长最小均方误差算法的权值收敛进行了仿真，结果表明变步长的算法效果更优。-This programme compare LMS algorithm with VSLMS algorithm. The result indicate that the latter is better.
ZF_MMSE_LMS_SATO_CMA
- 1.原始信号A，通过信道受噪声污染后的信号q，然后分别经过均衡器ZF（MMSE）得到信号U，可以画出U的分布图 2.分别应用LMS,SATO,CMA算法得到U。（其中包括最佳延迟、均方误差的计算）所有结果均以图像形式显示。-1. The original signal A, subject to noise pollution through the channel after the signal q, and then through the equalizer, respectively
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
xindaoguji
- 利用卡尔曼滤波器进行信道估计 提示：信道估计的状态方程和测量方程可分别表示为 要求：给出信道均方误差随样本数增加的曲线，给出matlab程序及具体的估计过程。 -Use of Kalman filter channel estimation Tip: the state of the channel estimation and measurement equations could be specified as required: given the channe
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
matlab
- 计算方法：函数平方逼近多项式的均方误差计算-Calculation method: function square mean square error of approximation calculation of polynomial
bpsk
- 层空时码有三种普遍的检测算法：最大似然（Maximum Likelihood ,ML）检测算法、迫零（zero forcing ,ZF）检测算法、最小均方误差（Minimum Mean Squared Error,MMSE）检测算法。-There are three layers in general space-time code detection algorithms: maximum likelihood (Maximum Likelihood, ML) detection algori
VBLAST-MMSE-ZF
- v-blast仿真程序，用了迫零检测和最小均方误差检测。（包括排序和不排序）-v-blast simulation program, using the Zero forcing and minimum mean square error. (Including sorting and unsorted)
LMS算法的matlab程序
- LMS算法是一种基于最小均方误差准则,通过调节权系数使得滤波器的输出信号y(n)与期望响应信号d(n)之间的均方误差的最小的算法。
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
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.)