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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
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均衡技术是克服码间干扰(Inter-Symbol Interference,ISI)的有效措施,由于信道特性的随机性与时变性,实际中消除码间干扰最常用的是自适应均衡器。本文对基于最小均方(Least Mean Squares,LMS)算法和递推最小二乘(Recursive Least Squares,RLS)算法的自适应均衡器进行仿真研究,分析了信道特性与设计参数对自适应均衡器的收敛速度与稳态性能的影响。
-Equalization technique is to overcome inte
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matlab的各种自适应仿真分析。。自适应信息处理的算法、方案繁多，究其实质可归纳为遵循最小均方误差(Least Mean Square，LMS)准则及最小二乘(Least Square，LS)准则两大类，其他算法大多是这两种算法的演进。-matlab simulation analysis of various adaptive. . Adaptive information processing algorithms, a variety of plans, their essence ca
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LMS: Least mean squares (LMS) algorithms is a type of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean squares of the error signal (difference between the desired and the actual
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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
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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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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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这个matlab代码是实现基于最小二乘算法的常数模算法。较最小均方误差算法，该算法收敛速度较快。-Matlab code to achieve the constant modulus algorithm based on least squares algorithm. Than the minimum mean square error algorithm, the algorithm converges faster.
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最小二乘法matlab源代码，拟合函数并计算均方误差-Matlab source code of the least squares method，Fitting functionAnd calculate the mean square error
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用Matlab仿真实现最小二乘法和总体最小二乘法估计
假设仿真的观测数据 产生，其中 为0均值， 单位方差的高斯白噪声，取n=1,2,....128。
试用TLS，取AR阶数为4，估计AR参数 和正弦波频率；再用SVD-TLS ，估计AR参数 和正弦波频率。
(1)、在仿真中，AR阶数取为4和6。
(2)、执行SVD-TCS时，AR未知。仿真运行至少二十次。
-Simulation using Matlab and the overall least squares leas
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RLS_LMS code the Least Mean Squares (LMS) and the Recursive Least. Squares (RLS) algorithms realize the design and simulation of adaptive algorithms in noise canceling, and ... of two algorithms .The adaptive filter with MATLAB are simulated and the
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PCA分类，用于较好的去噪降维，matlab的各种自适应仿真分析。。自适应信息处理的算法、方案繁多，究其实质可归纳为遵循最小均方误差(Least Mean Square，LMS)准则及最小二乘-PCA classification for better denoising dimensionality reduction, a variety of adaptive matlab simulation analysis. . Adaptive information processing alg
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Alexander D. Poularikas-Adaptive Filtering_ Fundamentals of Least Mean Squares with MATLAB® -CRC Press (2014)
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对HARQ系统的吞吐量分析，VDkLrhx参数多姿态，多角度，有不同光照,最小均方误差（MMSE）的算法，包括最小二乘法、SVM、神经网络、1_k近邻法,QiNdKHq条件是学习PCA特征提取的很好的学习资料，用MATLAB实现的压缩传感。- HARQ throughput analysis of the system, VDkLrhx parameter Much posture, multi-angle, have different light, Minimum mean square
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直线阵采用切比学夫加权控制主旁瓣比，最大似然（ML）准则和最大后验概率（MAP）准则，包括最小二乘法、SVM、神经网络、1_k近邻法,matlab开发工具箱中的支持向量机，调试通过可以使用，最小均方误差（MMSE）的算法。-Linear array using cut than learning laid upon the right control of the main sidelobe ratio, Maximum Likelihood (ML) criteria and maximum
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实现了对10个数字音的识别，使用高阶累积量对MPSK信号进行调制识别，使用混沌与分形分析的例程，对于初学matlab的同学会有帮助，采用偏最小二乘法，均值便宜跟踪的示例。- To achieve the recognition of 10 digital sound, Using high-order cumulants of MPSK signal modulation recognition, Use Chaos and fractal analysis routines, Matlab f
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DC-DC power single-part set-loop control, Least-squares regression analysis algorithm, Example tracking mean cheap.
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lms与rls算法比较,MATLAB 程序仿真，比较两种自适应滤波算法。最小均方(LMS)、递归最小二乘(RLS)(LMS and RLS algorithm comparison, MATLAB program simulation, comparison of two adaptive filtering algorithm. Least mean square (LMS) and recursive least squares (RLS))
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对基于LMS(最小均方)、NLMS（归一化最小均方）、RLS（递归最小二乘）算法的自适应噪声抵消系统进行MATLAB仿真，发现这几种算法都能从高背景噪声中有效地抑制干扰提取出有用信号，显示出了良好的的收敛性能，相比之下RLS算法去噪效果较好，呈现出更快的收敛速度，更强的稳定性和抑噪能力(the principle of LMS (minimum mean square), NLMS (normalized least mean square), RLS (recursive least squa
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least mean squares in matlab simulation
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