调节水床效应的双梯度有源噪声控制自适应算法*

为了使自适应反馈有源噪声控制系统能够兼顾水床效应,通过约束次级信号的能量以调节噪声放大,设计了一种双梯度算法。当次级信号满足约束,算法沿着最小化误差信号能量的梯度方向迭代,反之,则沿着最小化次级信号能量的方向迭代。在有源降噪耳机实例中的对比结果表明,该算法能调节噪声放大并保持较大的降噪带宽,且运算量没有显著增加。     

反馈有源噪声控制系统水床效应的分析与改善

本文依据反馈有源噪声控制原理分析了水床效应存在机理,以一模拟反馈有源噪声控制系统作为实例介绍了水床效应的分析方法,提出了通过展宽噪声放大频段和均匀噪声放大频段内的噪声放大量来优化反馈控制器,改善水床效应的方法。采用数字反馈控制器实现了水床效应的改善,给出了具体设计过程,并且考虑了数字时延对系统性能影响。仿真和实验表明了所提出方法的有效性。     

一种能量比调控的有源噪声控制算法

在前馈有源噪声控制系统中,建模信号与控制信号相互影响,建模信号的引入会导致系统降噪性能变差。为了减小建模信号的影响,提出一种基于能量比调控的次级通道在线建模有源噪声控制算法。利用控制过程与建模过程的误差能量比构造步长调控函数,分别调节控制过程与建模过程的步长值,从而减弱两者的相互影响。在次级通道建模过程中,对建模步长值采取分段调控的方法,并通过建模步长值的变化来调节建模信号,从而提升系统降噪性能。仿真结果表明,对于低频噪声信号的有源噪声控制,相比已有算法,提出的算法能获得较快的建模收敛速度和较高的降噪量。     

一种改进的自适应中值滤波算法

针对椒盐噪声的特点,提出了一种改进的自适应中值滤波算法。该算法通过对小窗口内非噪声点的检测来决定是增大滤波窗口还是选择输出。新算法尽可能地减小了滤波窗口,使得图像细节得到更好的保持。数值试验结果表明,新算法能够在有效抑制噪声的同时更好地保持图像细节信息,尤其在高概率密度噪声条件（〉70%）下也能取得较好的结果,比传统自...     

一种采用脉冲串的自适应有源干扰抵消器

在许多应用中，周期性干扰是由旋转的机械设备所产生的。一个周期性信号可以与一个特殊形式的周期性的脉冲串完全相干。本文提出了一种采用脉冲串的自适应有源噪声抵消器(AANC)来抵消周期性干扰，这种抵消器产生一个与干扰信号相同步的周期性的单位脉冲串作为参考输入。将这种有源噪声抵消器和Delayed-X LMS算法相结合，可以大大地减小运算量，并且也可以保证良好的收敛特性。理论分析和计算机仿真验证了本文的结果。     

基于声场复现的有源噪声控制支撑技术*

有源噪声控制是一种有广泛用途的低频噪声控制技术,目前已在部分场合取得商业化应用,然而该技术的大规模应用仍然面临诸多困难,声场复现技术为解决其中的关键问题提供了有效手段。该文论述了声场复现的两种实现方式(声场重构和声场再现)的基本原理、国内外现状及其在有源控制技术开发中的应用,尤其是基于声压匹配法的初级声场重构、基于球阵的声场再现以及电声器件布放优化设计。     

一种基于虚拟传感的无需误差传声器的自适应有源降噪方法*

该文基于虚拟传感技术引入了一种用于耳机的无需误差传声器的自适应有源降噪方法。该算法仅使用一个参考传声器实现了一种前馈和反馈自适应算法结合的有源降噪算法,提高了有源降噪稳定性,简化了耳机硬件结构。利用DSP平台实现了该文提出的方案,并通过实验验证了其良好的降噪性能和实用价值。     

应用于助听器反馈抑制的信噪比自适应滤波算法

针对基于自适应滤波器的助听器反馈抑制系统,该文提出了一种基于信噪比的归一化最小均方误差算法,采用最小值统计法估计误差信号的噪声分量,从而计算出误差信号的信噪比来计算自适应滤波系数的更新步长。当误差信号信噪比越高,语声占主要成分,信号的相关性越强,此时将滤波器的更新步长控制在较小值,减小滤波器的失调量;当信噪比越低时,噪声占主要成分,信号的相关性相对较弱,更新步长取较大值,加快滤波器的收敛速度。在仿真实验中,该文提出的基于信噪比的归一化最小均方误差算法相较于传统算法在平均稳态失调量和稳态失调范围上分别低1 dB和2 dB,其最大稳态增益提高了4 dB,同时具有更快的稳态收敛速度,验证了该文提出算法的有效性。     

应用于有源声辐射控制的一种组合次级声源

在分析多通道单极子次级源控制系统的基础上,提出一种幅度调节型组合次级声源,这种组合源由两个单极子声源构成,单极子声源的间距远小于声波的波长。文中就组合次级源在自由场中对不同初级声源辐射噪声的控制进行理论分析和实验验证,并与同等条件下的单极子次级源控制系统的降噪性能进行了比较分析。数值计算和实验结果均表明,对于不同的初级声场,在次级通道数相同的情况下,组合次级源控制系统可以得到比单极子次级源控制系统高的降噪量。     

基于听觉掩蔽效应的自适应反馈抵消

摘要当系统输入信号是有色信号时，传统的自适应反馈抵消算法会由于系统的输出和输入信号存在相关性而造成辨识反馈路径存在偏差，从而导致反馈抵消性能的降低。为了减小反馈路径的辨识偏差，本文提出在系统输出信号中加入被掩蔽噪声来降低系统的输入信号和输出信号的相关性的方法，噪声的能量由频域掩蔽阈值控制。这种基于听觉频域掩蔽效应的自适应反馈抵消算法改善了自适应反馈抵消的性能，同时加入的噪声是被掩蔽不可听的，输出语音的质量没有受到损害。     

A simplified adaptive feedback active noise control system

In the adaptive feedback active noise control system based on the internal model control (IMC) structure, the reference signal is regenerated by synthesizing the error signal and the secondary signal filtered with the estimation of the secondary path, hence more computation load and extra programming are required. Motivated by the engineering truth that the primary noise cannot be completely cancelled in most practical active noise control applications and the error signal still contains some portions of the primary noise, a simplified adaptive feedback active noise control system is proposed in this paper, which adopts the error signal directly as the reference signal in an adaptive feedforward control system and utilizes the leaky filtered-x LMS algorithm to update the controller. The convergence properties of the proposed system are investigated and its advantages are discussed by comparing with other feedback control systems as well as the weakness. Finally, simulations and experiments are carried out to demonstrate the effectiveness of the proposed system.     

On implementation of adaptive bilinear filters for nonlinear active noise control

In this technical note, the simplified diagonal-structure bilinear filtered-X least mean square (SDBFXLMS) and channel-reduced diagonal-structure bilinear filtered-X least mean square (CRDBFXLMS) algorithms are proposed. Computational complexity for each proposed algorithm is analyzed to show the significant computational reduction in comparison with the diagonal-structure bilinear FXLMS (DBFXLMS) algorithm. For L=15$L=15$ (memory length of the bilinear filter), P=2$P=2$ (the corresponding number of the diagonal channels for the SDBFXLMS algorithm is L+2P=19$L+2P=19$ and the corresponding number of the diagonal channels for the CRDBFXLMS algorithm is 2P=4)$2P=4)$, and M=64$M=64$ (memory length of the secondary path estimate), the SDBFXLMS algorithm achieves 45% and 40% reduction of multiplications and additions, respectively, while the CRDBFXLMS algorithm acquires 78% reduction of multiplications and 76% reduction of additions. Computer simulations validate the satisfied control performances of the proposed algorithms.     

Comparison of convergence characteristics of adaptive IIR and FIR filters for active noise control in a duct

There are perceived drawbacks to using adaptive IIR filters, as opposed to adaptive FIR filters, for active noise control (ANC). These include stability issues, the possible convergence of estimated parameters to biased and/or local minimum solutions and relatively slow rate of convergence. Stability issues can generally be resolved easily using well-established methods. In this Technical Note convergence rates are compared with particular reference to the active control of noise in a duct, for which the dynamics of the cancellation path are important. The characteristics of this application of ANC set it apart from usual signal processing applications of adaptive IIR filters and this has implications for the convergence properties. Various control approaches are considered: IIR least mean squares (IIR-LMS), IIR recursive least squares (IIR-RLS) with FASPIS (Fast Algorithm Secondary Path Integration Scheme) and FIR-LMS. Numerical examples are presented. It is seen that the cancellation path dynamics generally have the effect of changing the performance surface of the estimated IIR filter from bimodal to unimodal, which has consequences for improving the convergence rate of adaptive IIR filters. It is also seen that IIR-RLS has a comparable rate of convergence to FIR-LMS, with the steady-state performance being as good or better.     

Improving performance of FxRLS algorithm for active noise control of impulsive noise

Active noise control (ANC) systems employing adaptive filters suffer from stability issues in the presence of impulsive noise. New impulsive noise control algorithms based on filtered-x recursive least square (FxRLS) algorithm are presented. The FxRLS algorithm gives better convergence than the filtered-x least mean square (FxLMS) algorithm and its variants but lacks robustness in the presence of high impulsive noise. In order to improve the robustness of FxRLS algorithm for ANC of impulsive noise, two modifications are suggested. First proposed modification clips the reference and error signals while, the second modification incorporates energy of the error signal in the gain of FxRLS (MGFxRLS) algorithm. The results demonstrate improved stability and robustness of proposed modifications in the FxRLS algorithm. However, another limitation associated with the FxRLS algorithm is its computationally complex nature. In order to reduce the computational load, a hybrid algorithm based on proposed MGFxRLS and normalized step size FxLMS (NSS-FXLMS) is also developed in this paper. The proposed hybrid algorithm combines the stability of NSS-FxLMS algorithm with the fast convergence speed of the proposed MGFxRLS algorithm. The results of the proposed hybrid algorithm prove that its convergence speed is faster than that of NSS-FxLMS algorithm with computational complexity lesser than that of FxRLS algorithm.     

Adaptive Laguerre filters for active noise control

Feedforward controllers are used in many active noise control (ANC) systems to generate destructive interference in noise fields. An ideal feedforward ANC controller should have an infinite impulse response (IIR) transfer function, but most available feedforward ANC controllers have finite impulse responses (FIR) instead. The main reason is related to the adaptation algorithms of ANC systems. In general, adaptive FIR filters converge faster with guaranteed stability. In this study, the adaptive Laguerre filter is proposed and tested in an ANC application with positive experimental effects. The new ANC controller is an IIR filter, but its adaptation is similar to that of a FIR filter with fast convergence and guaranteed stability. Detailed explanations and analysis are presented in the main text.     

机车驾驶室中自适应有源降噪系统的研究

根据机车驾驶室中噪声特征的分析结果，提出了采用FIR滤波器的自适应有源降噪(ANNC)系统。为消除机车驾驶室中严重的背景噪声干扰影响，应用伪随机相关法对驾驶室中的噪声脉冲响应进行测量。通过数字仿真研究，对基于IMS算法的ANNC系统的关键参数进行了寻优。最后，在实际声场中建立了实时双通道ANNC系统并进行了相关的实验验证。仿真与实验的结果证明了本文提出的AANC系统的可行性和有效性。     

空间有源消声实验研究

本文分别在半声室和普通房间进行有源消声实验，证明了作者以前提出的算法是收敛的，稳定的，以此算法构成的多通道有源消声系统对直达声和混响声都能进行了有效的控制。     

Convex combination of nonlinear adaptive filters for active noise control

This paper proposes a nonlinear active noise control (ANC) system based on convex combination of a functional link artificial neural network (FLANN) and a Volterra filter. Simulation study reveals enhanced noise cancelation performance of the proposed ANC system over the ones based on its component filters.