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在DS-spread spectrum系统中,噪声为加性高斯白噪声,传统单用户检测,线性解相关多用户检测和最小均方误差多用户检测的性能比较-In the DS-spread spectrum system, the noise is additive white Gaussian noise, the traditional single-user detection, the linear decorrelating multiuser detector and minimum mean-sq
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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
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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
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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
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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
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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
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频域不同导频密度的信道估计在被研究，并且在高低时延信道其信道估计被固定了导频分配时域。频域信道估计是基于插补，多项式的广义线性模型（或最小二乘法）和维纳滤波（或线性最小均方误差法）的方法。时域的信道估计是用线性插补完成的。我们通过测量在基于克拉克散射模型的瑞利衰落信道上并带有QPSK调制的粗误码率，已经比较了所有这些方案的结果。-Different pilot density in frequency domain channel estimate to research, and its hi
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项目采用matlab对强迫零均衡器、最小均方误差均衡器、自适应线性均衡器进行了编程实现，并给出了计算机的仿真结果以及对仿真结果的分析，最后，给出递归最小二乘准则下的均衡器仿真予以比较。-Forced to zero on the project using matlab equalizer, minimum mean square error equalizer, adaptive linear equalizer is programmed to achieve, and gives the
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一个线性预测的matlab仿真程序，先用模型生成原始信号(平稳随机过程)，然后利用最小均方误差准则计算出预测系数，最后利用预测系数对原始信号进行预测(利用原始信号过去n个时刻的值预测当前时刻的值)。-This is a matlab program for linear prediction. First, we use all-pole model to generate a signal(stationary signal), then utilize the Minimum Mean-S
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研究了自适应参数谱估计的基本原理，提出了基于最小均方误差(MMSE)准则的LMS格型滤波算法实
现自适应参数谱估计的方法。通过对仿真测试信号和线性调频信号的计算表明，该方法能够在改善谱分辨率的
同时提高运算效率，满足遥测速变信号的处理和分析计算的要求-This paper discusses the principle of adaptive parametric spectrum estimation．It provides an approach to es—
timate po
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线性最小均方误差估计LMMSE的matlab算法-Linear minimum mean square error of the LMMSE estimation algorithm matlab
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卡尔曼滤波器的算法C实现
最佳线性滤波理论起源于40年代美国科学家Wiener和前苏联科学家Ｋолмогоров等人的研究工作，后人统称为维纳滤波理论。从理论上说，维纳滤波的最大缺点是必须用到无限过去的数据，不适用于实时处理。为了克服这一缺点，60年代Kalman把状态空间模型引入滤波理论，并导出了一套递推估计算法，后人称之为卡尔曼滤波理论。卡尔曼滤波是以最小均方误差为估计的最佳准则，来寻求一套递推估计的算法，其基本思想是：采用信号与噪声的状态空间模型，利用前一时刻地估计值和现时刻的观测值来
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运用最小均方误差方法实现波束形成，包括均匀直线阵和平面阵-Using the minimum mean square error method to achieve beamforming, including the uniform linear array and planar array.
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LMMSE，线性最小均方误差估计，一种参数估计的方法，使用的代价函数为均方误差。-The LMMSE, linear minimum mean square error estimation, a parameter estimation method, using the cost function for the mean square error.
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线性最小均方误差估计，估计恢复出的信号星座图-The linear minimum mean square error estimation，Estimation of LMMSE signal constellation restoration
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用MATLAB实现的卡尔曼滤波，根据有用信号和干扰噪声的统计特性（自相关函数或功率谱），以线性最小均方误差（MSE），能最大程度的滤除干扰噪声，提取有用信号。-Kalman filter using MATLAB, based on the statistical properties of the useful signal and interference noise (autocorrelation function or power spectrum), linear minimum m
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OFDM信道估计的几种方法的仿真，包括最小二乘(LS)法、最小均方误差(MMSE)法、线性最小均方误差(LMMSE)法以及奇异值（SVD）分解法等，毕设资料，非常珍贵-several OFDM channel estimation methods,which contains the least-squares (LS), the minimum mean square error (MMSE), the linear minimum mean square error (LMMSE) and
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卡尔曼滤波是解决以均方误差最小为准则的最佳线性滤波问题，它根据前一个估计值和最近一个观察数据来估计信号的当前值。而本程序是利用matlab实现卡尔曼滤波-Kalman filter is the solution to the minimum mean square error criterion optimal linear filtering problem, which according to the previous estimate and the most recent obser
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一种去马赛克的方法，根据论文《Color demosaicking via directional linear minimum mean square-error estimation》-A demosaicing method, according to the paper " Color demosaicking via directional linear minimum mean square-error estimation"
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基于IT++的MIMO下行链路线性最小均方误差（MMSE）均衡检测算法采用4QAM调制-MIMO linear minimum mean square error (MMSE) equalization detection algorithm based IT++ using 4QAM modulation
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