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为了避免单个滤波器在收敛速度与稳态误差上相互制约,从而导致系统性能降低的问题,本文采用凸组合最小均方算法(Combined Least Mean Square ,CLMS ),将快速滤波器和慢速滤波器并联使用,同时为进一步改善CLMS算法的性能,对已有的变步长凸组合最小均方算法(Variable Step-size Convex Combination of LMS ,VSCLMS )做出改进,提出了一种新的VSCLMS算法。在该算法中,对快速滤波器选用以最小均方权值偏差(Minimization of Mean Square Weight Error ,MMSWE)为准则的按步分析的变步长滤波器;对慢速滤波器采用以稳态最小均方误差(Least Mean Square , LMS )为准则的固定步长滤波器。通过理论分析与仿真实验表明,该算法能够在噪声、时变以及非平稳的环境下保持较好的随动性能,且在各个阶段均保持良好的收敛性,与传统的CLMS、VSCLMS算法相比,不仅具有更快的收敛速度,而且拥有稳定的均方性能和较优的跟踪性能,为自适应滤波算法的研究提供了一条可行途径。 相似文献
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多用户检测技术在实际应用中,难以解决的问题是在减少计算复杂度的同时又提高系统性能。本文针对空时CDMA系统设计了一种多用户检测算法,即附带噪声梯度的最速下降算法。此算法利用变步长迭代的思想实现多用户检测,避免了最小均方误差(MMSE)多用户检测庞大而复杂的求逆运算和固定步长收敛速度较慢的问题。计算机仿真结果表明,在空时CDMA系统中使用本文算法,收敛速度大大增加,同时在保持系统性能的前提下能够容纳较多的用户。 相似文献
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从数据重用因子出发,得到了基于部分更新仿射投影算法(SR-APA)的改进算法。该算法通过加权改变了SR-APA的数据筛选规律,从而降低了等效数据重用因子,并且通过对未加权原始数据的重新利用巧妙地避免了加权带来的条件数增加问题,最终达到了降低稳态均方误差(MSE)的效果。仿真结果表明,该算法不仅MSE比SR-APA低,收敛速度也比SR-APA快。在收敛速度相同时,该算法计算量只有SR-APA计算量的50%左右。 相似文献
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一种改进的变步长ELMS算法 总被引:2,自引:0,他引:2
在简单讨论基本最小均方(LMS)算法的基础上,引入了扩展的最小均方(ELMS)算法,并分析说明了该算法能达到更小的稳态MSE。改进的变步长ELMS算法是在对有用信号的预测中采用了自适应为归一化的的最小均方(NLMS)预测估计器,步长的迭代中引入遗忘因子i,利用其与误差信号的加权和来产生新的步长参与迭代。理论分析与计算机仿真结果表明,该算法有较好的收敛性能和较小的稳态失调。 相似文献
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对于基于梯度自适应的盲源分离算法,认真选择步长参数以达到好的分离性能是非常必要的。如果为加快收敛速度而增大步长因子,将会导致大的稳态误差,甚至引起算法发散,因此固定步长因子无法解决收敛速度和稳态误差之间的矛盾。本文为EASI算法提出了一种变步长的解决方案。通过建立步长因子与分离矩阵相互差异之间的非线性关系,加快了收敛速度,减小了失调误差。计算机仿真结果与理论分析相一致,证实了该算法明显优于传统的EASI算法。 相似文献
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为对如何提高自适应陷波器频率估计精度提供参考,通过评估自适应陷波器频率估计方法性能,对基于均方误差函数的自适应陷波器频率估计方法进行了统计性能分析。首先,根据误差函数的不同,将自适应陷波器划分为自适应FIR陷波器和自适应IIR陷波器。然后,将自适应FIR陷波器看作自适应IIR陷波器的特例,重点分析了自适应陷波器的误差函数及稳态下的频率估计统计性能,讨论了自适应陷波器参数对正弦信号频率估计精度和收敛速度的影响。最后,给出正弦信号的频率估计计算结果。结果表明,实际计算结果同理论计算结果一致,证明了统计性能分析的正确性。 相似文献
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An efficient bi-state stochastic gradient is proposed for spontaneous constrained time delay estimation. The quantized stochastic gradient is an approximation of the polarity of the instantaneous delay estimation error. It is adjusted in such a way that it has a much higher probability to move in the correct direction at each iteration so as to enable a speed-up in the delay estimate to converge to global minimum in steady state. The performance of the delay estimator is evaluated statistically and an analytical solution for its convergence behavior is established. It is demonstrated that the proposed algorithm has at least a two-fold improvement in convergence speed when compared with the conventional approach, and this is verified by extensive simulation results. 相似文献
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现有的自适应陷波滤波器(ANF)受误差函数所限,导致其自适应频率估计方法收敛速度较慢,对初始迭代频率值设定范围要求较高,特别针对频率接近于0或π的信号,还存在频率估计精度不高、算法稳定性差的问题,为此,提出一种ANF频率估计新方法.首先,分析现有ANF方法估计信号频率时存在精度低、速度慢、稳定性差的原因,提出一种新误差函数以提升ANF收敛速度;然后,根据ANF估计信号频率时偏差产生的机理,通过偏差补偿方式,降低噪声对ANF的影响,以获得近似无偏的频率估计结果,提高ANF频率估计精度,同时与离散卡尔曼滤波相结合,以改善算法的稳定性,并对该方法进行稳态条件下的性能分析;最后,给出了ANF频率估计结果,并讨论了ANF各参数对频率估计精度的影响,给出了具体计算结果.计算表明本文方法的有效性与正确性. 相似文献
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Random waypoint (RWP) mobility model is widely used in ad hoc network simulation. The model suffers from speed decay as the simulation progresses and may not reach the steady state in terms of instantaneous average node speed. Furthermore, the convergence of the average speed to its steady state value is delayed. This usually leads to inaccurate results in protocol validation of mobile ad hoc networks modeling. Moreover, the probability distributions of speed vary over the simulation time, such that the node speed distribution at the initial state is different from the corresponding distribution at the end of the simulation. In order to overcome these problems, this paper proposes a modified RWP mobility model with a more precise distribution of the nodes' speed. In the modified model, the speeds of nodes are sampled from gamma distribution. The results obtained from both analysis and simulation experiments of the average speed and the density of nodes' speed indicate that the proposed gamma random waypoint mobility model outperforms the existing RWP mobility models. It is shown that a significant performance improvement in achieving higher steady state speed values that closely model the pre‐assumed average speeds are possible with the proposed model. Additionally, the model allows faster convergence to the steady state, and probability distribution of speed is steady over the simulation time. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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Mean squared error (MSE) has been the dominant criterion in adaptive filter theory. A major drawback of the MSE criterion in linear filter adaptation is the parameter bias in the Wiener solution when the input data are contaminated with noise. We propose and analyze a new augmented MSE criterion called the Error Whitening Criterion (EWC). EWC is able to eliminate this bias when the noise is white. We will determine the analytical solution of the EWC, discuss some interesting properties, and develop stochastic gradient and other fast algorithms to calculate the EWC solution in an online fashion. The stochastic algorithms are locally computable and have structures and complexities similar to their MSE-based counterparts (LMS and NLMS). Convergence of the stochastic gradient algorithm is established with mild assumptions, and upper bounds on the step sizes are deduced for guaranteed convergence. We will briefly discuss an RLS-like Recursive Error Whitening (REW) algorithm and a minor components analysis (MCA) based EWC-total least squares (TLS) algorithm and further draw parallels between the REW algorithm and the Instrumental Variables (IV) method for system identification. Finally, we will demonstrate the noise-rejection capability of the EWC by comparing the performance with MSE criterion and TLS. 相似文献
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提出了一种基于改进抖动符号误差恒模算法(Modified Dithered Sign—Error Constant Modulus Algorithm,MDSE—CMA)的盲多用户检测算法。抖动符号误差恒模算法(Dithered Sign—Error Constant Modulus Algorithm,DSE—CMA)稳态性能好,但其过量的均方误差使得收敛速度较慢。MDSE—CMA算法通过引入符合正弦概率密度分布的抖动信号来减少均方误差。基于该算法的多用户检测方法与DSE—CMA算法相比,收敛速度加快。仿真证明,提出的方法在码分多址(Code Division Multiple Aceess,CDMA)异步多径信道下可有效地抑制多址干扰和克服多径衰落。 相似文献
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Wei-Lung Mao Wann-Jiun Ma Ying-Ren Chien Chia-Hao Ku 《Circuits, Systems, and Signal Processing》2011,30(3):527-542
The global positioning system (GPS), which provides accurate positioning and timing information, has become a commonly used
navigation instrument for many applications. The application of a new adaptive all-pass based notch filter (ANFA) for narrowband/FM
interference suppression and frequency estimation in GPS receivers is proposed. An ANFA structure that achieves better unbiased
characteristics with its coefficients is employed to accurately estimate the narrowband interfering signals in online fashion.
A variable convergence factor that optimizes the maximal mean square error (MSE) reduction in each iteration is applied in
a modified adaptive Gaussian–Newton (MAGN) algorithm. The proposed MAGN algorithm can lead to both faster convergence speed
and higher estimation accuracy. Simulation results show that the ANFA offers a better performance than conventional linear
predictors in terms of the SNR improvement and the mean output power (MOP) under the interference environments of interest. 相似文献