一种改进的变步长自适应滤波器LMS算法

本文提出一种改进的LMS算法(即MS-LMS)，并建立了步长因子μ与误差信号e(n)之间另一种新的非线性函数关系。该关系不仅具有原有算法在误差e(n)接近零处缓慢变化的优点，而且低信噪比环境下比原有算法具有更好的收敛性能。理论分析和计算机仿真结果表明，在低信噪比的环境下，改进算法的收敛速度和稳态误差的性能指标都有较大的提高，并对系统发生的突变表现出较强的鲁棒性。     

一种改进的自适应LMS算法

本文对LMS算法中的收敛因子μ进行了详细的数学分析,提出了一种较好的选择μ的方法。计算机模拟结果证实了该算法的优越性。     

一种自适应线谱对滤波器的终点误差LMS算法及其学习特性

本文提出了一种计算线谱对（LSP）系数的新算法．该算法以最小均方（LMS）误差型算法为基础，梯度计算使用系统终点误差。对接收到的语音观测样本在一个时序的基础进行迭代更新计算，直接产生LSP系数，形成一个LMS算法的自适应LSP滤波器。实验结果表明，该算法与其它自适应滤器的LMS算法比较，具有更高的收敛率和较低的失调。     

自适应滤波器LMS算法的DSP实现

滤波器在数字信号处理中有着广泛的应用,针对常规滤波器因具有固定的滤波器系数,对某些信号处理系统不能实现最优滤波,设计了一种自适应滤波器及实现的软件算法,并通过DSP得到验证。结果表明该滤波器实现方法简单、不依赖模型,具有较强的稳健性。     

LMS算法自适应滤波器的DSP实现

论文主要研究了自适应滤波器的基本结构和最小均方误差算法(LMS算法),同时采用MATLAB语言对该算法进行了仿真,然后使用SY-5402EVM评估板对其进行了DSP实现,并对结果进行了分析。     

一种改进的频域LMS自适应滤波器算法

本文首先提出了轮流受限自正交分块频域批处理ＬＭＳ（轮流受限自正交ＰＢＦＬＭＳ）算法，接着对此算法进行了计算机仿真。最后对受限、轮流受限和无限制ＰＢＦＬＭＳ算法进行了综合比较，并得出结论。     

LMS自适应滤波器的仿真与实现

本文概述了LMS算法和LMS滤波器的的基本原理,利用MATLAB和DspBuilder立算法模型,完成LMS自适应滤波器的仿真与设计,有效地提高了FPGA的设计效率．降低了设计人员对硬件的要求。     

LMS自适应滤波器的设计理论研究

主要介绍了自适应滤波器的基本理论思想,具体阐述了自适应滤波器的基本原理、算法及设计方法。首先介绍自适应滤波器的原理,然后对FIR结构滤波器做了详细的阐述,自适应算法是整个系统的核心,重点对LMS算法的设计方法,设计步骤做了分析,最后对LMS算法进行MATLAB仿真,根据性能评价标准和实验结果表明,该自适应滤波器滤波效果优越。     

模糊LMS算法主从滤波器的设计及应用

文章提出了一种基于模糊最小均方（LMS）算法的主从滤波器的设计,采用模糊推理机制,通过从滤波器输出的信噪比来调节主滤波器的步长,从而达到快速而稳定的收敛,并将其应用于噪声抵消系统中。仿真结果表明,该算法（FMS-LMS）比传统LMS算法及只有主从滤波器的算法具有更好的性能。     

用于ADSL中的变步长LMS算法

本文给出了一种改进的LMS算法，该算法可应用于非对称数字用户线中实现回波抵消功能，从而在低频段的子通道内同时传输上行和下行的数据。新算法利用误差信号的相关值调节算法步长，具有较好的抗干扰性能，解决了算法收敛时间和稳态误差间的矛盾，为实际应用提供了更大的控制灵活性。仿真结果表明，在低信噪比的环境中，改进算法的收敛速度和稳态误差等性能指标都有较大的提高。并对随机出现的脉冲干扰表现出较好的鲁棒性。     

基于LMS算法与RLS算法的自适应滤波

自适应信号处理的理论和技术已经成为人们常用滤波和去噪技术。文中讲述了自适应滤波的原理以及LMS算法和RLS算法两种基本自适应算法的原理及步骤。并用MATLAB分别对两种算法进行了自适应滤波仿真和实现。     

Estimating second-order Volterra system parameters from noisy measurements based on an LMS variant or an errors-in-variables method

This paper deals with the identification of a nonlinear SISO system modelled by a second-order Volterra series expansion when both the input and the output are disturbed by additive white Gaussian noises. Two methods are proposed. Firstly, we present an unbiased on-line approach based on the LMS. It includes a bias correction scheme which requires the variance of the input additive noise. Secondly, we suggest solving the identification problem as an errors-in-variables issue, by means of the so-called Frisch scheme. Although its computational cost is high, this approach has the advantage of estimating the Volterra kernels and the variances of both the additive noises and the input signal, even if the signal-to-noise ratios at the input and the output are low.     

一种改进的变步长LMS自适应算法

为了提高LMS自适应算法的性能,在对一些变步长LMS算法分析的基础上,提出了步长因子μ(n)与误差信号e(n)之间一种新的非线性函数关系,该算法比固定步长LMS算法收敛速度快,稳定性好,另外与文[5]中算法相比,不需要进行指数运算.将该算法应用于自适应噪声抵消系统的仿真中,计算机仿真结果与实际分析相一致.     

语音去噪LMS自适应滤波器算法的改进

对LMS自适应算法进行了详细的性能分析与讨论,针对LMS算法运算较复杂、适应性较弱、稳定性差的缺点提出了一种HLMS(混合LMS)算法.建立了自适应噪声抵消系统,利用MATILAB软件对食堂、体育馆两处的录音信号进行计算机语音去噪仿真分析.实验结果表明,两种自适应方法均能有效抑制各种噪声污染,提高语音信噪比为60%～8...     

Steady-state analysis of the long LMS adaptive filter

For the well-known LMS adaptive algorithm no general analytic solutions are available for the steady-state weight-error statistics under stationary stochastic excitation. Only approximate tools have been developed using certain assumptions (like the “independence assumption”) and producing more or less reliable results in practical situations. It is only for the case of a vanishingly small stepsize that such assumptions are not required. There a closed-form solution can be determined for any colouring of the input signal and the additive noise.Here another particular problem is analyzed: the long filter, i.e. a tapped-delay line structure with a large number of taps. For the limiting case of an infinitely long filter, exact closed-form solutions are derived for the steady-state weight-error correlations and the associated “misadjustment”, again valid for any colouring of the input signal and the additive noise, and now also for any stepsize guaranteeing stability.The analysis is based upon a feedback approach, with a forward branch generating the above-mentioned solution for vanishing stepsize and a peculiar feedback branch responsible for higher-order corrections. As in any feedback structure, instability can occur beyond a critical value of the feedback parameter. In our case an experimentally supported maximum stepsize is found, beyond which spontaneous oscillations might occur.     

数值稳健的自适应二阶Volterra滤波器

本文采用广义多信道模型，利用ＱＲ分解方法，实现了自适应二阶Ｖｏｌｔｅｒｒａ滤波器，计算机模拟结果表明该帝现收敛速度快，数值性能好。     

Adaptive Multiuser Channel Estimation using Reduced Kalman/LMS Algorithm

This paper presents an adaptive multiuser channel estimator using the reduced-Kalman least-mean-square (RK-LMS) algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh distributed tap coefficients. The multiuser channel estimator based on minimum-mean-square-error (MMSE) criterion is used to predict the filter coefficients. We also present its convergence characteristics and tracking performance using the RK-LMS algorithm. Unlike the previously available Kalman filtering algorithm based approach (Chen, Chen IEEE Trans Signal Process 49(7): 1523–1532, 2001) the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser channel estimator used in the code division multiple access wireless systems. The computer simulation results are presented to demonstrate the substantial improvement in its tracking performance under the smoothly time-varying environment.

基于自适应Volterra滤波器的非线性系统辨识

为了识别非线性系统的参数,本文提出了一种基于自适应Volterra滤波器的非线性系统辨识方法。给出了自适应Volterra滤波器的LMS和RLS算法。数值仿真结果表明,该方法对于非线性定常和时变系统都有效。