共查询到20条相似文献,搜索用时 281 毫秒
1.
自适应滤波器在系统辨识、回声消除、信道均衡等领域获得了广泛应用.符号子带自适应滤波器(Sign Subband Adaptive Filter,SSAF)具有较强的抗脉冲干扰能力,但当输入信号受到噪声干扰时,其对未知系统系数向量的估计会产生偏差.为了解决上述问题,本文基于无偏估计准则,提出了一种偏差补偿符号子带自适应滤波器(Bias-Compensated Sign Subband Adaptive Filter,BC-SSAF).为了解决定步长自适应滤波器需要在收敛速度和稳态失调之间进行折中的问题,本文采用随机梯度法来更新正则化参数,提出了变正则化参数偏差补偿符号子带自适应滤波器(Variable Regularization Bias-Compensated Sign Subband Adaptive Filter,VR-BC-SSAF).仿真结果验证了BC-SSAF和VR-BC-SSAF性能的优越性. 相似文献
2.
本文提出了两种基于多带结构的仿射投影符号子带自适应滤波器(Affine Projection Sign Subband Adaptive Filter, AP SSAF)的改进方法。针对稀疏系统的系统识别,设计了两种子带自适应滤波器。首先给出了AP SSAF的变正则化参数更新方程,文中采用随机梯度下降法来更新正则化参数,来使系统的均方偏差最小化,该方法能同时兼顾快速收敛及低稳态失调。其次将权重分布矩阵引入AP SSAF得到系数比例AP SSAF,该方法能够利用系统的稀疏性提高AP SSAF的收敛性能。仿真中将本文所提算法用于一般系统识别以及回波抵消,实验结果验证了本文的算法对脉冲噪声具有稳健性,具有较好的跟踪性能,并具有较快的收敛速度及低稳态失调。 相似文献
3.
在电子回声消除应用中,为提高自适应算法的收敛速度,提出一种改进的仿射投影算法及其快速实现形式.新算法利用回声路径的稀疏结构特征,通过收敛步长控制矩阵,按滤波器各系数幅值大小,等比例地为其指定相应收敛步长,以加快大系数收敛,最终达到加快滤波器整体收敛速度的目的.对新算法进行的统计学分析,为其快速收敛于目标系统的算法特性提供了理论依据.仿真实验表明与传统自适应算法相比,新算法能减小稳态失调并大幅提高收敛速度,其低计算复杂度亦保证了系统的实时性. 相似文献
4.
5.
6.
针对已有的变步长自适应算法收敛速度和稳态误差矛盾的问题,提出了一种新的变步长最小均方自适应滤波算法。新的算法在类S函数的基础上,引入调节因子P对步长函数的形状进行实时调整,并以误差的自相关时间均值估计调节步长,使得算法在初始时具有较快的收敛速度,稳态时有更平滑的步长变化。在新算法中引用最大似然加权算法进一步抑制自适应滤波器权系数伪峰。将新算法和最大似然加权应用在自适应时延估计的实验中,结果表明:在已有参数固定的条件下,新提出的算法具有更快的收敛速度和更小的稳态误差。同时,时延估计实验中能有效地实现信噪比-3 dB以上的准确时延估计。 相似文献
7.
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
8.
针对方向向量偏差会导致最小均方(LMS)算法的性能急剧下降这一问题,提出了一种基于可变对角载入的顽健自适应波束形成算法.采用最陡下降法对信号方向向量进行优化求解,并在每次迭代过程中更新对角载入值,进而求出最优的权重向量,避免了矩阵求逆运算和特征值分解运算,大大降低了计算复杂度.通过建立步长与输入信号的关系得到可变的步长因子,克服了收敛速度和稳态误差之间的矛盾.该算法收敛速度快,抗扰动性强,对信号方向向量偏差具有很强的顽健性,从而改善了阵列输出的信干噪比,使其更接近最优值.理论分析和仿真结果表明与传统自适应波束形成算法相比,所提顽健算法具有更好的性能. 相似文献
9.
11.
Shengkui Zhao Douglas L. Jones Suiyang Khoo Zhihong Man 《Circuits, Systems, and Signal Processing》2014,33(7):2251-2265
The least-mean-square-type (LMS-type) algorithms are known as simple and effective adaptation algorithms. However, the LMS-type algorithms have a trade-off between the convergence rate and steady-state performance. In this paper, we investigate a new variable step-size approach to achieve fast convergence rate and low steady-state misadjustment. By approximating the optimal step-size that minimizes the mean-square deviation, we derive variable step-sizes for both the time-domain normalized LMS (NLMS) algorithm and the transform-domain LMS (TDLMS) algorithm. The proposed variable step-sizes are simple quotient forms of the filtered versions of the quadratic error and very effective for the NLMS and TDLMS algorithms. The computer simulations are demonstrated in the framework of adaptive system modeling. Superior performance is obtained compared to the existing popular variable step-size approaches of the NLMS and TDLMS algorithms. 相似文献
12.
13.
14.
A number of time-varying step-size algorithms have been proposed to enhance the performance of the conventional LMS algorithm. Experimentation with these algorithms indicates that their performance is highly sensitive to the noise disturbance. This paper presents a robust variable step-size LMS-type algorithm providing fast convergence at early stages of adaptation while ensuring small final misadjustment. The performance of the algorithm is not affected by existing uncorrelated noise disturbances. An approximate analysis of convergence and steady-state performance for zero-mean stationary Gaussian inputs and for nonstationary optimal weight vector is provided. Simulation results comparing the proposed algorithm to current variable step-size algorithms clearly indicate its superior performance for cases of stationary environments. For nonstationary environments, our algorithm performs as well as other variable step-size algorithms in providing performance equivalent to that of the regular LMS algorithm 相似文献
15.
LMS和归一化LMS算法收敛门限与步长的确定 总被引:4,自引:0,他引:4
从LMS算法失调量的准确表达式出发,根据输入信号特征值分布重新研究了LMS,归一化LMS(Normalized LMS,NLMS)算法收敛的必要条件,推导出LMS和NLMS 算法收敛的步长门限,并分析了输入信号特征值分布、滤波器阶数对算法收敛步长门限的影响,推导出满足性能失调下步长的自适应计算公式,减小了应用 LMS,NLMS算法时步长选取的盲目性,与已有的算法相比,具有计算简单、实用、自适应性能强,同时可获得满意失调量的特点,计算机模拟结果表明该方法的正确性。 相似文献
16.
迭代变步长LMS算法及性能分析 总被引:1,自引:0,他引:1
针对固定步长LMS(Least Mean Square)算法(FXSSLMS)不能同时满足快速收敛和小稳态失调误差的问题,该文提出了迭代变步长LMS算法(IVSSLMS)。与已有的变步长LMS算法(VSSLMS)不同,该算法的步长因子不再是由输出误差信号控制,而是建立了与迭代时间的改进Logistic函数非线性关系,克服了定步长算法收敛慢及已有变步长算法抗噪声干扰能力差的问题。最后从理论上分析了算法的性能,给出了其参数取值方法。理论分析和仿真均表明,所提算法能够在快速收敛情况下获得小的稳态失调误差,在有色噪声干扰下稳态失调误差比已有算法降低了约7 dB。 相似文献
17.
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
18.
Proportionate自适应算法利用稀疏冲激响应的结构特征,极大地加速了算法的收敛速度。但是快速收敛与低稳态失调是一对矛盾的需求,固定步长算法必需折中选择一个步长参数来满足应用的要求。本文提出了一种适用于proportionate算法的变步长方法,有效解决了收敛速度和稳态失调之间的矛盾。所提的算法首先利用最小干扰原理,得到了一个proportionate NLMS算法的推导;进而将干扰信号考虑进算法的系数更新过程,通过在每一步迭代中用后验误差去补偿干扰信号的负面作用,得到一个新的优化准则;最后利用这个准侧,推导出了一个适用于proportionate算法的步长调节方法。仿真实验验证了本文方法的有效性。 相似文献
19.
Variable Step Size LMS Algorithm Based on Function Control 总被引:1,自引:0,他引:1
This paper proposes a function-controlled variable step size least mean square (VSLMS) algorithm for channel estimation in low-SNR or colored input signals. The proposed method aligns the step size update with the steady-state error and alleviates the impact of high-level noise. It improves the filter performance in terms of fast convergence rate and low misadjustment error. Simulation results demonstrate the effectiveness and verify the theoretic analysis of the proposed VSLMS algorithm. 相似文献