Correlation LMS algorithm and its application to double-talk echocancelling

In echo cancellers for teleconference systems, the serious problem of double-talk still exists. The authors propose a new algorithm where, for tap adaptation, the gradient is searched by the input correlation functions. A computer simulation of the proposed CLMS algorithm shows robust performance in double-talk situations     

A frequency-weighted block LMS algorithm and its application to speech processing

In this letter, we propose a frequency-weighted block LMS (FWBLMS) algorithm that is based on minimization of the frequency-weighted block mean-squared error. The FWBLMS algorithm has an important advantage over the time-domain LMS algorithm in that it can be designed with different frequency weighting on error signal depending on the relative significance of various frequency bands. Application of the FWBLMS algorithm in adaptive linear prediction of speech is discussed.     

部分更新块LMS均衡算法分析及应用

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。     

用逐级消除平均误差的LMS自适应算法检测瞬态信号

瞬态信号由于短时性、宽频带和相关性强之特点,实际的检测往往比较困难.本文是在LMS算法的基础上,以逐级消除平均误差为准则,对算法进行修正,并根据权向量的收敛过程和权向量误差的有关分析理论基础上,提出了反向滤波的方法.实验表明该滤波算法能有效地提高精度,反向滤波方法能有效地克服了正向滤波权向量不收敛现象.     

Generalized sliding FFT and its application to implementation ofblock LMS adaptive filters

This paper has two contributions. First, the concept of the generalized sliding fast Fourier transform (GSFFT) as an efficient implementation of the hopping FFT is introduced. Application of the GSFFT is broad and not limited to what has been considered in this paper. The frequency domain block LMS (FBLMS) adaptive filters are then revised, and their implementations for block lengths less than the length of the adaptive filter are studied. The GSFFT and the available pruned FFTs are used to give an efficient implementation of these filters. In the particular case of the block length equal to one, where the FBLMS algorithm reduces to the frequency domain LMS (FLMS) algorithm, it is shown that the latter can be implemented with the order of M complexity, where M is the length of the adaptive filter     

Hybrid filtered error LMS algorithm: another alternative to filtered-x LMS

The filtered-error LMS (FELMS) algorithms are widely used in multi-input and multi-output control (MIMO) active noise control (ANC) systems as an alternative to the filtered-x LMS (FXLMS) algorithms to reduce the computational complexity and memory requirements. However, the available FELMS algorithms introduce significant delays in updating the adaptive filter coefficients that slow the convergence rate. In this paper, we introduce a novel algorithm called the hybrid filtered-error LMS algorithm (HFELMS) which, while still a form of the FELMS algorithm, allows users to have some freedom to construct the error filter that guarantees its convergence with a sufficiently small step size. Without increasing the computational complexity, the proposed algorithm can improve the control system performance in one of several ways: 1) increasing the convergence rate without extra computation cost; 2) reducing the remaining noise mean square error (MSE); or 3) shaping the excess noise power. Simulation results show the effectiveness of the proposed method.     

Analysis of constrained LMS algorithm with application to adaptive beamforming using perturbation sequences

Adaptive antenna array processing employing a constrained least mean square (LMS) algorithm requires an unbiased estimate of the gradient of the output power with respect to the array weights. There are a number of schemes for obtaining an unbiased estimate of this gradient. Though in each case the estimated gradient is unbiased, the covariance of the estimated gradient with each method is different and thus the transient and the steady state behavior of the constrained algorithm is different in each case. The transient and the steady state behavior of the weight covariancc matrix is analyzed, exact expressions for the misadjustment are derived, and a comparison of the performance of the algorithm is presented when the required gradient is estimated by different schemes. The schemes considered include gradient estimation when all the array signals are accessible as well as gradient estimation using perturbation sequences for eases when the array signals are inaccessible. The necessary and the sufficient condition for the diagonlization of the weight covarience matrix is also derived.     

基于LMS算法的自适应控制在稳定回路中的应用

成像器稳定跟踪平台的稳定回路设计是一种高精度、高动态响应的伺服回路设计,为实现较好的控制特性,提出了一种基于LMS算法的Adaline网络参数自适应控制方法,根据被控对象的参数变化,实时调整控制器的参数,由于算法相对简单,满足实际工程应用的要求。为了避免自适应算法运算对系统响应快速性的影响,设计了基于常规控制和自适应控制的双模态控制器结构,根据实际工作条件,进行控制策略的实时切换,既保证了系统响应的快速性,又保证了控制精度。实验结果表明,采用该方法实现的稳定回路具有良好的动态和静态特性。     

Bursting in the LMS algorithm

The least mean square (LMS) algorithm is known to converge in the mean and in the mean square. However, during short time periods, the error sequence can blow up and cause severe disturbances, especially for non-Gaussian processes. The paper discusses potential short time unstable behavior of the LMS algorithm for spherically invariant random processes (SIRP) like Gaussian, Laplacian, and K₀. The result of this investigation is that the probability for bursting decreases with the step size. However, since a smaller step size also causes a slower convergence rate, one has to choose a tradeoff between convergence speed and the frequence of bursting     

LUDWIG算法的改进与应用

Ludwig积分在雷达散射截面(RCS)计算中被广泛应用.传统的Ludwig积分针对基于三角形面元的模型剖分技术,因此主要用于平面片积分.三角形面片由于是平面片,因此无法对复杂模型准确建模.本文改进了Ludwig积分,并将其用于基于NURBS(非均匀有理B样条)技术的曲面积分.通过计算实例可以看出改进后的Ludwig积分形式适用于基于曲面建模技术的物理光学(PO)算法.     

Stability of the quantized LMS algorithm

The least mean square (LMS) algorithm is investigated for stability when implemented with two's complement quantization. The study is restricted to algorithms with periodically varying inputs. Such inputs are common in a variety of applications, and for system identification, they can always be generated as shown with an example. It is shown that the quantized LMS algorithm is just a special case of a quantized periodically shift-varying (PSV) filter. Two different sufficient conditions are obtained for the bounded input bounded output (BIBO) stability of the PSV filter. When the filter is BIBO stable, two different bounds on the filter output are also derived. These conditions and bounds are then applied to the quantized LMS algorithm. The results are illustrated with examples.     

Robust design of the LMS algorithm

A method to optimize the step size of the LMS algorithm when it is used to identify a time-varying system is proposed. The formulation allows uncertain specifications of the input excitation and the plant variation. The method is robust in that it minimizes the mean square error for the worst-case data of these variables     

Multiplaten Z-buffer algorithm and its application to multiplescattering

The authors present a new algorithm: the multiplaten Z-buffer algorithm. By employing a geometry based on this algorithm we can speed up the process of ray tracing, which is used to calculate the multiple scattering of a complex object. Comparison with the experimental results shows this algorithm to be effective     

Analysis of the Error Signal of the LMS Algorithm

An analysis of the error signal of the Least-Mean-Square (LMS) algorithm is conducted from the robust control theory viewpoint. The difference equation that relates the input of the LMS algorithm and the error signal is presented. This equation is used to build the matrix ${bf S}$ that maps the input vector to the error vector. It is shown that ${bf S}$ has at least one singular value greater than 1. Therefore, the system may amplify noise at high frequencies. Nevertheless, the tap-weight vector may be chosen to prevent that noise amplification and improve the disturbance rejection performance of the LMS algorithm.      

误差通道建模误差对多误差LMS算法性能的影响

本文证明了，在多通道自适应宽带有源噪声控制中，由于误差通道建模误差的存在，多误差LMS算法是条件收敛的，并推导了保证算法收敛的条件，还证明了，算法收敛后，得到自适应滤波器权值一般只是理论上最优值的有偏估计，计算机仿真结果验证了所得结论．     

Analysis of the frequency-domain block LMS algorithm

We present a new analysis of the frequency-domain block least-mean-square (FBLMS) algorithm. An earlier analysis uses a mapping of the frequency-domain information to the time-domain before proceeding with the analysis of the algorithm. We present a direct analysis of the FBLMS algorithm in the frequency domain. As compared with the previous analysis, the new analysis is easier to follow. It is also more rigorous than the previous works and gives a better insight to the effect of various processing components in the algorithm structure on its convergence behavior. In particular, we show how the transformation of input samples to the frequency domain, combined with the effect of the involved windowing matrices, and step-normalization affect the convergence behavior of both constrained and unconstrained versions of the FBLMS algorithm. We also report a procedure for derivation of misadjustment equations of various versions of the FBLMS algorithm     

Almost-sure convergence of the continuous-time LMS algorithm

The authors consider the stability properties of the conventional continuous-time least mean square algorithm. The algorithm for the case of stationary ergodic inputs is investigated and a necessary and sufficient condition for exponential almost-sure convergence is presented. This condition is shown to be less restrictive than the well-known persistency of excitation condition. Also, the authors point out and clarify an apparently common error regarding the connections between persistency of excitation and positive definite autocorrelation in stationary ergodic vector waveforms     

A stable subgridding algorithm and its application to eigenvalueproblems

In this paper, a new and stable subgridding algorithm is proposed for three-dimensional problems which provides subgridding in both space and time. The concept of an equivalent-circuit representation and a novel leapfrog time integration scheme is used to ensure that the algorithm is stable and efficient. Practical applications of this algorithm in the characterization of arbitrarily filled dielectric resonators are reported     

基于频域块LMS算法的实时虚拟暗室测试方法

针对电磁辐射现场测试被测设备信号和干扰未知的情况,提出了一种基于频域块最小均方算法的实时虚拟暗室测试方法。该方法采用双通道接收机,根据测试通道和背景通道中干扰信号的相关性设计自适应滤波器,在频域对背景通道信号滤波以趋近测试通道中的干扰分量,采用瞬时双通道信号迭代更新滤波器系数,滤波器系数收敛后系统输出中只有被测设备信号。仿真与分析表明,该方法在背景通道有无被测设备信号泄露的情况下都能有效抑制干扰,与基于时域最小均方算法的方法相比,在滤波器长度相同的情况下其计算复杂度更低,适用于实时现场测试。