共查询到19条相似文献,搜索用时 484 毫秒
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基于数字地面电视广播(Digital Terrestrial Television Broadcasting,DTTB)同频直放站的回波干扰抑制,提出了一种变步长块LMS(Variable Step- size Block Normalized Least Mean Square,VSSBNLMS)自适应算法.此算法的目的是为了提高传统回波干扰抑制的自适应算法的收敛速度和降低计算复杂度.其将输入信号分为长度相等的块,在每一个数据块内,权值向量只更新一次,有效地降低了计算复杂度.另外,该算法通过输出误差控制更新步长的变化,与传统的归一化LMS(NLMS)和块LMS(BLMS)算法相比,提高了收敛速度.仿真结果表明,该算法具有良好的收敛速度和回波干扰抑制性能. 相似文献
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采用部分更新最小均方(LMS)算法和重叠保留的块信号频域处理结构,针对现场可编程门阵列(FPGA)的硬件实现平台,提出了时频混合部分更新块LMS和周期性块部分更新LMS均衡算法结构。2种新结构均能有效降低均衡算法的实现复杂度。步长收敛条件分析和数值仿真结果表明,新结构能够在适当调整更新步长的情况下,有效跟踪缓变信道的变化,实现与完整块LMS算法相当的性能,能够有效解决高速数据传输中的均衡复杂度过高的问题。 相似文献
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针对LMS自适应滤波算法在输入信号高度相关时.收敛速度下降导致性能下降,本文从基本的块LMS算法开始,简要介绍了块LMS算法的实现方法,在此基础上重点分析了在变步长块LMS算法中,影响步长因子的要素.提出了一种新的变步长因子迭代算法(SVBLMS),该迭代算法充分考虑输入信号和误差信号对变步长因子的影响.并且迭代的结构简单,计算量小.通过Matlab仿真.仿真结果表明.该迭代算法较其它块LMS算法有更快的收敛速度,更稳定的收敛过程.当输入为有色信号或输入噪声较大时,本算法都能保持良好的性能. 相似文献
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提出了一种基于最小Rayleigh熵的盲波束形成算法。该算法根据最小Rayleigh熵的原理对恒模算法的代价函数进行改进,其基本思想就是在寻找最优权矢量时把恒模信号的幅值归并到协方差矩阵里去考虑,以得到最小代价函数的闭式解,从而得到初始权值,最后再用最小二乘恒模算法(LSCMA)算法进行更新迭代。这种算法属于块处理,不存在算法收敛局部极小点和收敛速度慢的问题,所以具有较强的优越性。仿真结果证实了算法的有效性。 相似文献
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针对部分空时自适应(STAP)处理的特征值分解(EVD)影响杂波抑制的实时处理性能,提出了基于改进快速子空间迭代跟踪(PAST)的部分自适应STAP算法.该方法首先在PAST处理的基础上,对正交PAST方法进行改进,得到改进后的PAST(MPAST)方法;然后将MPAST方法应用于计算部分自适应STAP算法的特征子空间,从而有效提高STAP算法的收敛速度和降低自适应权矢量计算的运算量.仿真数据和MCARM实测数据分析表明,该方法能有效抑制待检测距离单元的杂波,并能在低计算复杂度下显著提高STAP处理的收敛速度. 相似文献
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为有效克服导向矢量大失配误差对自适应波束形成器的影响,该文提出了一种迭代对角加载采样矩阵求逆鲁棒自适应波束形成算法。该算法对传统对角加载算法进行了迭代运算,基于Capon波束形成器的最优权矢量与假定导向矢量的基本关系,将每一步得到的权矢量,对应反解出一个比导向矢量假定值更为准确的导向矢量,并替代假定值,最终逼近真实的期望信号导向矢量。提出的方法在迭代过程中只需一步递推,无需对导向矢量建立不确定集,避免了在每步迭代中运用拉格朗日数值法或凸优化法,且明显提高了波束形成器的输出信干噪比。仿真结果验证了算法的正确性和有效性。 相似文献
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二阶Volterra数据块LMS算法利用当前时刻及其以前时刻更多输入信号和误差信号的信息提高了算法的收敛速度,但由于其固定数据块长取值的不同导致了算法的收敛速度和稳态误差此消彼长。针对这个问题,本文提出一种二阶Volterra变数据块长LMS算法,通过时刻改变输入信号数据块长度提高算法性能。本算法首先采用两个并行的二阶Volterra滤波器,其输入信号数据块长差值始终保持一个单位;然后将其各自的输出误差信号同时输入到数据块长判决器,通过判决器得到下一时刻各个滤波器输入信号的数据块长度;最后以第1个二阶Volterra滤波器的输出作为整个滤波系统的输出,从而改善了算法性能。将本算法应用于非线性系统辨识,计算机仿真结果表明,高斯噪声背景下本算法的收敛速度和稳态性能都得到了明显的提高。 相似文献
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Conditioning of LMS algorithms with fast sampling 总被引:1,自引:0,他引:1
The LMS algorithm is very commonly used in signal processing. Its convergence properties depend primarily on the step size chosen and the condition number of an information matrix associated with the system. In most applications today, the LMS uses a regression vector based on the shift operator (including the ubiquitous tapped delay line). We demonstrate that generically, when fast sampling is employed, these regression vectors lead to poorly conditioned LMS. By comparison, delta operator based regression vectors lend with rapid sampling to improved condition numbers, hence, to better performance 相似文献
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This paper presents a modified version of the two-step least-mean-square (LMS)-type adaptive algorithm motivated by the work of Gazor. We describe the nonstationary adaptation characteristics of this modified two-step LMS (MG-LMS) algorithm for the system identification problem. It ensures stable behavior during convergence as well as improved tracking performance in the smoothly time-varying environments. The estimated weight increment vector is used for the prediction of weight vector for the next iteration. The proposed modification includes the use of a control parameter to scale the estimated weight increment vector in addition to a smoothing parameter used in the two-step LMS (G-LMS) algorithm, which controls the initial oscillatory behavior of the algorithm. The analysis focuses on the effects of these parameters on the lag-misadjustment in the tracking process. The mathematical analysis for a nonstationary case, where the plant coefficients are assumed to follow a first-order Markov process, shows that the MG-LMS algorithm contributes less lag-misadjustment than the conventional LMS and G-LMS algorithms. Further, the stability criterion imposes upper bound on the value of the control parameter. These derived analytical results are verified and demonstrated with simulation examples, which clearly show that the lag-misadjustment reduces with increasing values of the smoothing and control parameters under permissible limits. 相似文献
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等和值块扩展最近邻搜索算法(EBNNS)是一种快速矢量量化码字搜索算法,该算法首先将码书按和值大小排序分块,编码时查找与输入矢量和值距离最近的码书块中间码字,并将它作为初始匹配码字.然后在该码字附近上下扩展搜索相邻码字中距输入矢量最近的码字,最后将搜索到的最匹配码字在码书中的地址输出.同时本文对该算法进行了FPGA设计.设计时采用串并结合和流水线结构,折中考虑了硬件面积和速度.结果表明针对所用FPGA器件Xilinx xc2v1000,整个系统最大时钟频率可达88.36MHz,图像处理速度约为2.2 MPixel/s. 相似文献
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Xue Xiangyang Wu Lide 《电子科学学刊(英文版)》1998,15(1):22-28
A modified block matching algorithm (BMA) with motion correlation constraint (MCCBMA) is proposed at first. Then a novel motion compensation algorithm (INTPMC) which computes motion vector for each pixel by interpolating motion vectors is presented. In order to increase interframe prediction performance and decrease the computational complexity, an optimizing algorithm for partial motion vectors is described at last. Experimental results show that the proposed algorithm can improve the prediction performance obviously with a moderately increased complexity compared with the conventional full search block matching algorithm (FSBMA). 相似文献
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An efficient scheme is presented for implementing the LMS-based transversal adaptive filter in block floating-point (BFP) format, which permits processing of data over a wide dynamic range, at temporal and hardware complexities significantly less than that of a floating-point processor. Appropriate BFP formats for both the data and the filter coefficients are adopted, taking care so that they remain invariant to interblock transition and weight updating operation, respectively. Care is also taken to prevent overflow during filtering, as well as weight updating processes jointly, by using a dynamic scaling of the data and a slightly reduced range for the step size, with the latter having only marginal effect on convergence speed. Extensions of the proposed scheme to the sign-sign LMS and the signed regressor LMS algorithms are taken up next, in order to reduce the processing time further. Finally, a roundoff error analysis of the proposed scheme under finite precision is carried out. It is shown that in the steady state, the quantization noise component in the output mean-square error depends on the step size both linearly and inversely. An optimum step size that minimizes this error is also found out. 相似文献
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该文提出了一种新的快速块匹配运动估计方法,分级筛选法。该方法将搜索最佳匹配块的过程 分为若干个筛选级别,在初始的级别中用很少的运算代价通过简单的特征匹配先淘汰一部分候选块;然后在上一级剩余的候选块中,逐级用更加细致的特征继续筛选;直至找到最佳匹配块。实验结果表明,在估计精度非常相近的前提下,该文方法的速度是全搜索方法的12~14倍,而且该方法有很好的稳定性。 相似文献