共查询到20条相似文献,搜索用时 15 毫秒
1.
Yingsong Li Masanori Hamamura 《International Journal of Adaptive Control and Signal Processing》2015,29(9):1189-1206
Recently, sparsity‐aware least mean square (LMS) algorithms have been proposed to improve the performance of the standard LMS algorithm for various sparse signals, such as the well‐known zero‐attracting LMS (ZA‐LMS) algorithm and its reweighted ZA‐LMS (RZA‐LMS) algorithm. To utilize the sparsity of the channels in wireless communication and one of the inherent advantages of the RZA‐LMS algorithm, we propose an adaptive reweighted zero‐attracting sigmoid functioned variable‐step‐size LMS (ARZA‐SVSS‐LMS) algorithm by the use of variable‐step‐size techniques and parameter adjustment method. As a result, the proposed ARZA‐SVSS‐LMS algorithm can achieve faster convergence speed and better steady‐state performance, which are verified in a sparse channel and compared with those of other popular LMS algorithms. The simulation results show that the proposed ARZA‐SVSS‐LMS algorithm outperforms the standard LMS algorithm and the previously proposed sparsity‐aware algorithms for dealing with sparse signals. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
2.
Mohammad Shams Esfand Abadi 《International Journal of Adaptive Control and Signal Processing》2010,24(9):786-804
In this article, the concept of proportionate adaptation is extended to the selective partial update (SPU) and set‐membership (SM) normalized subband adaptive filters (NSAFs), and three proportionate normalized subband adaptive filter algorithms are established. The proposed algorithms are the improved proportionate NSAF (IPNSAF), the SPU improved proportionate NSAF (SPU‐IPNSAF), and the SM‐IPNSAF which are suitable for sparse system identification. When the impulse response of the echo path is sparse, the IPNSAF algorithm has faster convergence than NSAF. The performance of IPNSAF is also suitable for dispersive impulse responses. In SPU‐IPNSAF, the filter coefficients are partially updated rather than the entire filter at every adaptation which reduces the computational complexity of IPNSAF. The SM‐IPNSAF exhibits good performance with significant reduction in the overall computational complexity compared with the ordinary IPNSAF. The simulation results show good performance of the proposed algorithms. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
3.
Tarek I. Haweel 《International Journal of Circuit Theory and Applications》2004,32(6):523-536
A new LMS based variable step size adaptive algorithm is presented. The step size is incremented or decremented by a small positive value, whenever the instantaneous error is positive or negative, respectively. The algorithm is simple, robust and efficient. It is characterized by fast convergence and low steady state mean squared error. The performance of the algorithm is analysed for a stationary zero‐mean white‐Gaussian input. MC simulations are provided to demonstrate its improved performance over the conventional LMS (Proc. IEEE 1976; 64 :1151–1162) and some other variable step size adaptive algorithms (IEEE Trans. Signal Process. 1992; 40 :1633–1642; IEEE Trans. Signal Process. 1997; 45 :631–639) within a range of statistical environments. For a non‐stationary input, the proposed algorithm behaves similar to these algorithms. A modified version of the algorithm is presented to perform in the presence of abrupt changes. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
4.
A new two‐microphone Gauss‐Seidel pseudo affine projection algorithm for speech quality enhancement
下载免费PDF全文
![点击此处可从《International Journal of Adaptive Control and Signal Processing》网站下载免费的PDF全文](/ch/ext_images/free.gif)
Mohamed Djendi 《International Journal of Adaptive Control and Signal Processing》2017,31(8):1162-1183
This study addresses the problem of speech quality enhancement by adaptive and nonadaptive filtering algorithms. The well‐known two‐microphone forward blind source separation (TM‐FBSS) structure has been largely studied in the literature. Several two‐microphone algorithms combined with TM‐FBSS have been recently proposed. In this study, we propose 2 contributions: In the first, a new two‐microphone Gauss‐Seidel pseudo affine projection (TM‐GSPAP) algorithm is combined with TM‐FBSS. In the second, we propose to use the new TM‐GSPAP algorithm in speech enhancement. Furthermore, we show the efficiency of the proposed TM‐GSPAP algorithm in speech enhancement when highly noisy observations are available. To validate the good performances of our algorithm, we have evaluated the adaptive filtering properties in computational complexity and convergence speed performance by system mismatch criteria. A fair comparison with adaptive and nonadaptive noise reduction algorithms are also presented. The adaptive algorithms are the well‐known two‐microphone normalized least mean square algorithm, and the recently published two‐microphone pseudo affine projection algorithm. The nonadaptive algorithms are the one‐microphone spectral subtraction and the two‐microphone Wiener filter algorithm. We evalute the quality of the output speech signal in each algorithm by several objective and subjective criteria as the segmental signal‐to‐noise ratio, cepstral distance, perceptual evaluation of speech quality, and the mean opinion score. Finally, we validate the superior performances of the proposed algorithm with physically measured signals. 相似文献
5.
6.
7.
8.
横向时延滤波和IQ正交滤波的滤波效果仿真 总被引:1,自引:1,他引:0
由于横向时延滤波和IQ正交滤波在稳定性、收敛速度和误差率等方面的性能差异对于最小均方算法(LMS,Least Mean Squares)在工程上的实际应用具有参考意义,采用数值仿真的方法模拟了两者实现自适应最小均方算法的具体过程,并对比分析了它们的滤波性能。仿真结果显示IQ正交滤波具有更高的稳定性、更快的收敛速度、更小的误差率,其滤波性能优于横向时延滤波。IQ正交滤波器的阶数为2阶,而横向时延滤波器的阶数通常>10,滤波器阶数越多引入的权噪声也会相对增加,对于稳定性、收敛速度和误差率都是不利的,因此实际应用中优先选择阶数较少的IQ正交滤波器。 相似文献
9.
10.
11.
传统的固定步长的LMS算法难于同时获取较快的收敛速度与较小的稳态误差,基于这一矛盾,本文在分析基本LMS算法的基础上,提出了一种新的变步长LMS算法,该算法具有较快的收敛速度和较小的稳态误差。理论分析和计算机仿真结果表明该算法在收敛速度与稳态误差的性能上均优于基本LMS算法。尤其是在低估噪比的情况下,其性能的优越性更为突出。与传统的LMS算法相比较,新算法更适合于应用到回波消除等实时性要求高的场合。 相似文献
12.
基于带双窗N-1/N重叠频域FIR滤波器的自适应除噪 总被引:2,自引:2,他引:0
基于一种带双窗重叠自适应滤波器,将重叠滤波思想引入LMS算法,给出了窗加权重叠LMS(WO-LMS)算法.与传统的LMS算法相比,WO-LMS算法在同样收敛速度的前提下可以得到较低的稳态均方误差.理论分析了算法的收敛性,实验中通过和LMS算法的比较,验证了WO-LMS算法的优越性. 相似文献
13.
14.
D. Delvecchio L. Piroddi 《International Journal of Adaptive Control and Signal Processing》2014,28(12):1422-1439
Active noise control problems are often affected by nonlinear effects such as distortion and saturation of measurement and actuation devices, which call for suitable nonlinear models and algorithms. The active noise control problem can be interpreted as an indirect model identification problem, due to the secondary path dynamics that follow the control filter block. This complicates the weight update mechanism in the nonlinear case, in that the error gradient depends on the secondary path gradient through nonlinear recursions. A simpler and computationally less demanding approach is here proposed that employs the updating scheme of the standard filtered‐x least mean squares (LMS) or filtered‐u LMS algorithm. As in those schemes, the calculation of the error gradient requires a signal filtering through an auxiliary system, here obtained through a secondary adaptation loop. The resulting dual filtering LMS algorithm performs the adaptation of the controller parameters in a direct identification mode and can therefore be easily coupled with adaptive model structure selection schemes to provide online tuning of the model structure, for improved model robustness. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
15.
本文以负压波信号采集滤波为例,介绍了基于LMS算法的自适应滤波器的基本原理和该滤波器几个关键参数设定的基本方法。实践证明,在采集随机不确定信号时,采用此滤波器进行信号调理具有比传统滤波器不可比拟的优越性。 相似文献
16.
17.
在回声抵消研究中,LMS算法由于具有算法简单、易于实现的特点而得到广泛应用.然而,采用LMS算法的自适应回声抵消器的性能仍然有很大的改进余地,可以通过对算法本身的改进和对利用该算法的自适应滤波器的结构的改进达到更好的性能,主要研究了利用LMS算法的AEC自适应滤波器结构上的改进,提出了一种新的滤波器设计方法,该方法通过将采样信号在输入端拆分,分别输入到多个并联的子滤波器中分别处理,得到对回声信号的估计后将它从掺杂有回声信号的接收信号中消除,并在输出端重新组合,成为对原始信号的恢复.这种并联多通道结构可以有效提高回声抵消器的收敛速度、降低运算量.由于这种方法利用了多通道并联自适应滤波器的结构,因此要求非常严格的数据同步和时间控制.仿真结果表明,这种方法对回声抵消具有良好的效果. 相似文献
18.
Rosalin Nirmal Kumar Rout Debi Prasad Das 《International Journal of Adaptive Control and Signal Processing》2019,33(11):1695-1705
In this paper, the proportionate normalized least mean square (PNLMS) and its modifications, such as improved PNLMS (IPNLMS) and μ‐law PNLMS (MPNLMS) algorithms, developed for a sparse system, are analyzed for a compressed input signal. This analysis is based on a comparative study of the steady‐state error and convergence time for the original signal and the compressed signal. Further, in this paper, a filter PNLMS (FPNLMS) algorithm that is a modification of the IPNLMS algorithm is proposed. The FPNLMS algorithm uses a step size varying in time to adapt to the sparse system. Simulations are carried out to compare the proposed FPNLMS algorithm for different signal‐to‐noise ratio for a compressed input signal with existing algorithms, ie, PNLMS, MPNLMS, and IPNLMS algorithms. The FPNLMS algorithm achieves a better steady‐state and convergence time compared with other existing algorithms in both low and high SNRs. The FPNLMS algorithm is further simulated for a real transfer function to show its robustness compared with existing algorithms. 相似文献
19.
采用自适应滤波前馈方法对压电智能结构悬臂梁进行振动控制。分别研究了常用LMS自适应算法及其改进型NLMS算法在振动主动控制中的应用,并对两种算法的性能进行了比较。理论分析和仿真结果表明,自适应滤波前馈控制能够有效的控制悬臂梁的振动,基于NLMS算法比基于LMS算法的前馈控制具有更快的响应速度和更小的稳态误差。 相似文献