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关于自适应滤波的算法仿真，其中应用了LMS算法和RLS算法，也比较了他们的性能-Adaptive filtering algorithms on the simulation, which applied the LMS algorithm and RLS algorithm, also compare the performance of their
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拟使用基于LMS与RLS的自适应算法在MATLAB平台上对带有两个权的自适应线性组合器进行仿真,进而对两类算法的性能作比较，同时也考察了两种算法在不同参数条件下曲线收敛性的变化-Intending to use the LMS and RLS-based adaptive algorithm in the MATLAB platform with two pairs of the right to self-adaptive linear combiner is simulated, and t
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用ＭＡＴＬＡＢ实现ＬＭＳ算法和ＲＬＳ算法权矢量的比较-LMS algorithm using MATLAB and the RLS algorithm to achieve the right to compare the vector
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用matlab仿真LMS算法和RLS算法的收敛性，并对rls算法和lms算法做比较-Matlab simulation with the LMS algorithm and RLS algorithm convergence, and rls algorithms and lms algorithm to compare
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To Compare thr RlS and LMS algorithm we utilised and improved the exisiting functinal from matlab, precisely the scheme of RLS and LMS algorithms for adaptive noise cancellation.
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分别用LMS和RLS算法实现回音对消，并比较二者收敛性能，及不同信道参数对算法的影响-LMS and RLS algorithms were used to achieve echo cancellation, and compare the convergence performance of the two, and different channel parameters affect the algorithm
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盲信号分离(BSS)指在源信号混合和传输信道未知的情况下，只利用接收天线的输出观测混合信号抽取源信号的方法。本文简要阐述了常用的瞬时混合盲信号分离的LMS与RLS自适应算法，对RLS自适应算法重点研究分析了基于普通梯度与自然梯度的两种算法，并通过仿真实验来分析比较几种方法的性能。-Blind signal separation (BSS) refers to the source signal and transmission channel mixing unknown circumstanc
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智能天线自适应算法的研究，比较了LMS、RLS和MVDR三种算法的性能。-Smart antenna adaptive algorithm study to compare the performance of the LMS, RLS and MVDR three algorithms.
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比较实现了自适应滤波器的LMS算法与ＲＬＳ算法，不同的参数，仿真图！-compare the RLS and LMS alorigthm,with different varibles
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自适应波束形成算法中，LMS算法和RLS算法的性能分析与比较优劣性-Adaptive beamforming algorithm, LMS algorithm and RLS algorithm performance analysis and compare the advantages and disadvantages of
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RLS和LMS对比分析和研究，比较了它们的性能和优缺点，调试成功，可以使用-RLS and LMS comparative analysis and research to compare their performance advantages and disadvantages, debugging, you can use
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图1为均衡带限信号所引起失真的横向或格型自适应均衡器(其中横向FIR系统长M=11), 系统输入是取值为±1的随机序列，其均值为零；参考信号；信道具有脉冲响应：
式中用来控制信道的幅度失真(W = 2～4, 如取W = 2.9,3.1,3.3,3.5等)，且信道受到均值为零、方差(相当于信噪比为30dB)的高斯白噪声的干扰。试比较基于下列几种算法的自适应均衡器在不同信道失真、不同噪声干扰下的收敛情况(对应于每一种情况,在同一坐标下画出其学习曲线):
1）横向/格-梯型结构LMS算法
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比较LMS,RLS, 和Kalman滤波器多用户检测器的性能 不错的-Compare LMS, RLS, and Kalman filter multiuser detector performance is quite good
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比较两种算法的权值收敛速度，并对比不同u值对LMS算法以及λ值对RLS算法的影响。(Compare the weight convergence speed of the two algorithms, and compare the impact of different U values on the LMS algorithm and lambda value on the RLS algorithm.)
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比较LMS,RLS, 和Kalman滤波器多用户检测器的性能 不错的(Compare LMS, RLS, and Kalman filter multiuser detector performance is quite good)
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