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lms
Date : 2012-04-09 Size : 88kb User : hj7518@163.com

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非常不错的LMS学习材料 附带LMS仿真结果-LMS is very good study material incidental LMS simulation results
Date : 2026-01-08 Size : 26kb User : wangxin

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lms算法极为最小均方误差算法, 是均衡器消除码间串扰一种算法;-lms algorithm
Date : 2026-01-08 Size : 14kb User : 赵阳

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智能天线的自适应算法通过迭代运算获取用于波束形成的最优权值矢量时,是否具有较快的收敛速度和较小的稳态误差成为决定波束形成性能的主要因素.据此提出在传统的LMS算法中引入变步长和变换域的思想,采用改进的自适应算法用于波束形成.MATLAB仿真结果表明,该算法具有较快的收敛速度和较小的稳态误差,波束形成的性能更优.-lms
Date : 2026-01-08 Size : 5.35mb User : 11

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lms 算法的详细说明 (基于LMS与RLS算法的自适应均衡器性能研究)-lms detailed description of the algorithm (LMS and RLS algorithm based adaptive equalizer performance of)
Date : 2026-01-08 Size : 241kb User : 任伟

LMS算法验证,节实验数据说明和程序设计-LMS algorithms and test data section, and program design
Date : 2026-01-08 Size : 8kb User : DASHITOU

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lms algorithm Noise Cancellation
Date : 2026-01-08 Size : 113kb User : 杨芸丞

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LMS最小二乘法,拟合曲线的基本原理:成对等精度地测得一组数据x,试找出一条最佳的拟合曲线。(LMS Least Squares, the basic principle of fitting the curve: pairs of precision to measure a set of data x, try to find a best fit curve.)
Date : 2026-01-08 Size : 9kb User : 唐tang

用MATLAB实现的LMS自适应滤波算法及变步长自适应算法程序。(LMS adaptive filtering algorithm and variable step size adaptive algorithm program implemented by MATLAB.)
Date : 2026-01-08 Size : 11kb User : liuxiansh

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lms algorithm for signal processing applications lms algorithm for signal processing applications
Date : 2026-01-08 Size : 25kb User : sreddy

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lms algorithm for signal processing applications
Date : 2026-01-08 Size : 25kb User : sreddy

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lms algorithm for signal processing application
Date : 2026-01-08 Size : 38kb User : sreddy

自适应波束形成算法:如何用matlab生成自适应波束(Adaptive beamforming algorithm)
Date : 2026-01-08 Size : 1kb User : 蜗ke

介绍了噪声抵消的原理和从强噪声背景中自适应滤波提取有用信号的方法,并对最小均 方 (LMS, Least Mean Squares) 、归一化 LMS(NLMS, Normalized Least Mean Squares) 和递推最小二乘 (RLS, Recursive Least Squares) 三种基本自适应算法进行了对比研究。计算机模拟仿真结果表明,这 几种算法都能通过有效抑制各种干扰来提高强噪声背景中的信号检测特性。相比之下, RLS 算法 具有良好的收敛性能,除收敛速度快于 LMS 算法和 NLMS 算法以及稳定性强外,而且具有更高的 起始收敛速率;更小的权噪声,更大的抑噪能力。(The theory of noise canceling and the method for abstracting the desired signal from strong background noise were described by using adaptive filtering and the LMS algorithms NLMS algorithms and RLS algorithms were compared)
Date : 2026-01-08 Size : 286kb User : 如此逼真的假
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