共查询到19条相似文献,搜索用时 296 毫秒
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传统的最小均方误差(LMS)算法难以同时获取较快的收敛速度和较小的稳态误差,而变步长LMS算法可获得二者之间的平衡。对已有的一些变步长LMS算法进行了分析,在变系数步长(VFSS)算法的基础上,引入输入信号因子,并建立步长因子与误差信号之间新的非线性函数关系,提出一种改进的变步长LMS算法,该算法不仅继承了VFSS算法在低信噪比环境下抗噪声性能好的特点,而且能够快速跟踪系统的变化,仿真结果表明改进算法的性能优于现有算法。 相似文献
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提出了一种新颖的变步长符号算法用于DS/CDMA系统的多用户检测。这种算法对盲平均符号算法的步长又一次采用二次最小均方误差算法,克服了盲平均符号算法受步长影响的缺点,并利用符号算法计算复杂度低的特点,加快了算法的收敛速度。仿真表明,这种算法能够自动迅速地适应环境的变化并且不受初始步长和学习率的影响,在性能上优于与其类似的自适应接收机。 相似文献
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本文通过分析几种变步长LMS算法,结合VSS-NLMS算发和NLMS算法的优点,采用符号函数降低原有算法的计算复杂度,对变步长参数进行调整,提出了一种改进的变步长LMS算法,通过仿真验证,新提出的算法在收敛速度和稳态误差上也有一定优点,具有工程实际意义。 相似文献
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一种新的变步长LMS自适应滤波算法及其仿真 总被引:1,自引:0,他引:1
传统变步长LMS算法存在收敛速度慢、易受噪声影响等缺点,为了提高算法性能,论文建立了LMS算法中步长因子μ(n)和误差信号e(n)的相关统计量之间的非线性关系,提出了一种基于改进的双曲正切函数的变步长LMS(HTLMS)算法.算法采用当前误差与上一步误差乘积的绝对值来调节步长,并引入了绝对估计误差的扰动量来更新自适应滤波器抽头向量,因而具有收敛速度快、噪声抑制能力强和稳态误差低等特点.计算机仿真结果表明,在不同信噪比条件下,与多种LMS算法相比,本文算法都具有较快的收敛速度和较好的稳态误差. 相似文献
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针对同时同频全双工(Co-frequency and Co-time Full Duplex,CCFD)系统已有的数字域干扰对消方法收敛速度慢和对消比低的问题,本文提出了迭代变步长最小均方(Least Mean Square,LMS)算法,利用该算法实现了快速收敛的高对消比数字域干扰对消.首先,改进Logistic函数,缩短其函数值由大至小的变化区间,再利用该非线性函数计算随迭代次数变化的步长因子值,从而加快干扰对消的收敛速度,高精度递推估计自干扰信道参数,即获得高的对消比.最后,理论分析了该对消方法收敛性和计算复杂度,得到了稳态条件下对消比的闭合表达式.仿真表明,该方法与已有变步长LMS对消方法相比,对消比可增加6dB以上,收敛速度可提高1倍,与最小二乘信道估计干扰对消方法相比,对消比提高了至少10dB. 相似文献
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Channel estimation is one of the key technologies for ensuring reliable wireless communications under impulsive noise environments. This paper studies robust adaptive channel estimation methods for mitigating harmful impulsive noises, which are described as alpha‐stable (α ‐stable) distribution models. Traditional adaptive channel estimation using the second‐order statistics based least mean square (SOS‐LMS) algorithm does not perform well under α ‐stable noise environments, even though it was considered one of attractive approaches for estimating channels in the case of Gaussian noises. Unlike the traditional SOS‐LMS algorithm, in this research, we propose a stable sign‐function‐based LMS algorithm, which can mitigate the impulsive noises. Specifically, we first construct the cost function with minimum ℓ 1‐norm error criterion and then derive the updating equation of the proposed algorithm. Compared with the traditional SOS‐LMS, the effectiveness of the proposed algorithm is validated via Monte Carlo simulations in various α ‐stable noise scenarios. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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Lu Lu Haiquan Zhao Kan Li Badong Chen 《Circuits, Systems, and Signal Processing》2016,35(9):3244-3265
To overcome the performance degradation of adaptive filtering algorithms in the presence of impulsive noise, a novel normalized sign algorithm (NSA) based on a convex combination strategy, called NSA-NSA, is proposed in this paper. The proposed algorithm is capable of solving the conflicting requirement of fast convergence rate and low steady-state error for an individual NSA filter. To further improve the robustness to impulsive noises, a mixing parameter updating formula based on a sign cost function is derived. Moreover, a tracking weight transfer scheme of coefficients from a fast NSA filter to a slow NSA filter is proposed to speed up the convergence rate. The convergence behavior and performance of the new algorithm are verified by theoretical analysis and simulation studies. 相似文献
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最小均方(Least Mean Square, LMS)算法的更新方向是对最速下降方向的估计,其收敛速度也受到最速下降法的约束。为了摆脱该约束,该文在对LMS算法分析的基础上,提出一种针对LMS算法的分块方向优化方法。该方法通过分析误差信号来选择更新向量,使得算法的更新方向尽可能接近Newton方向。基于此方法,给出一种方向优化LMS(Direction Optimization LMS, DOLMS)算法,并推广到变步长DOLMS算法。理论分析与仿真结果表明,该方法与传统分块LMS算法相比,有更快的收敛速度和更小的计算复杂度。 相似文献
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针对传统固定步长CMA盲均衡算法中收敛速度和剩余误差这对矛盾,提出了一种新型变步长恒模盲均衡算法,即由瑞利分布函数实施对其步长的调节,通过调整该步长公式中的两个参数以加快收敛速度和减小剩余误差,并且在此基础上对该算法进行了改进。用4QAM信号,通过典型电话信道对固定步长的CMA算法,基于瑞利步长的CMA和改进后的CMA算法进行计算机仿真。通过对仿真出的算法收敛曲线以及输出星座图进行分析,最终得出在瑞利步长算法的基础上改进后的CMA算法克服了前两种算法的缺点,即具有收敛速度更快,剩余误差更小的优点。 相似文献
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少模光纤模式复用存在模式耦合和差分模式时延,必须通过自适应均衡算法补偿。为了降低长距离少模光纤通信系统中自适应均衡算法的复杂度,采用基于变步长-频域块最小均方算法的多输入多输出均衡器对2×2模分复用系统解复用。利用频域块最小均方自适应算法修正均衡器权系数,并通过变步长函数调整步长因子,兼顾算法收敛速度和收敛性能。算法可通过快速傅里叶变换降低计算复杂度。在112Gbit/s的1000km少模光纤高速通信仿真系统中,保证相同收敛速度情况下,提高信号Q2因子3.7dB,并在可编程现场门阵列上验证了100km少模光纤通信系统时的算法性能。结果表明,该算法能够实现模分复用系统的信号解复用,达到快速收敛、低稳态失调的目的。 相似文献
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This paper proposes a two-stage affine projection algorithm (APA) with different projection orders and step-sizes. The proposed algorithm has a high projection order and a fixed step-size to achieve fast convergence rate at the first stage and a low projection order and a variable step-size to achieve small steady-state estimation errors at the second stage. The stage transition moment from the first to the second stage is determined by examining, from a stochastic point of view, whether the current error reaches the steady-state value. Moreover, in order to prevent the sudden drop of convergence rate on switching from a high projection order to a low projection order, a matching step-size method has been introduced to determine the initial step-size of the second stage by matching the mean-square errors (MSEs) before and after the transition moment. In order to continuously reduce steady-state estimation errors, the proposed algorithm adjusts the step-size of the second stage by employing a simple algorithm. Because of the reduced projection orders and variable step-size in the steady-state, the algorithm achieves improved performance as well as extremely low computational complexity as compared to the existing APAs with selective input vectors and APAs with variable step-size. 相似文献