Constrained adaptation for feedback cancellation in hearing aids.

In feedback cancellation in hearing aids, an adaptive filter is used to model the feedback path. The output of the adaptive filter is subtracted from the microphone signal to cancel the acoustic and mechanical feedback picked up by the microphone, thus allowing more gain in the hearing aid. In general, the feedback-cancellation filter adapts on the hearing-aid input signal, and signal cancellation and coloration artifacts can occur for a narrow-band input. In this paper, two procedures for LMS adaptation with a constraint on the magnitude of the adaptive weight vector are derived. The constraints greatly reduce the probability that the adaptive filter will cancel a narrow-band input. Simulation results are used to demonstrate the efficacy of the constrained adaptation.     

Robust modeling of acoustic paths using a sparse adaptive algorithm

Acoustic impulse response functions are generally sparse in nature and traditionally these are modeled by adaptive finite impulse response (FIR) filters trained using a least mean square (LMS) algorithm. The conventional LMS algorithm is not effective in modeling sparse systems and sparse LMS algorithms have been recently developed to improve the modeling in such scenarios. However, the traditional sparse LMS algorithms are not robust to disturbances at the error sensor and may diverge in some scenarios. With an objective to overcome this limitation of conventional sparse adaptive algorithm, this paper presents a robust sparse adaptive algorithm. The new algorithm has been shown to effectively model sparse systems in a robust manner. In addition, the algorithm has been successfully applied in modeling the acoustic feedback path in a behind the ear digital hearing aid.     

Adaptive feedback cancellation in hearing aids with clipping in the feedback path

Adaptive linear filtering algorithms are commonly used to cancel feedback in hearing aids. The use of these algorithms is based on the assumption that the feedback path is linear, so nonlinearities in the feedback path may affect performance. This study investigated the effect on feedback canceller performance of clipping of the feedback signal arriving at the microphone, as well as the benefit of applying identical clipping to the cancellation signal so that the cancellation path modeled the nonlinearity of the feedback path. Feedback signal clipping limited the amount of added stable gain that the feedback canceller could provide, and caused misadjustment in response to high-level inputs, by biasing adaptive filter coefficients toward lower magnitudes. Cancellation signal clipping mitigated these negative effects, permitting higher amounts of added stable gain and less misadjustment in response to high-level inputs, but the benefit was reduced in the presence of the highest-level inputs.     

Room reverberation effects in hearing aid feedback cancellation

Room reverberation can affect feedback cancellation in hearing aids, with the strength of the effects depending on the acoustical conditions. These effects were studied using a behind the ear (BTE) hearing aid mounted on a dummy head and coupled to the ear canal via an open fitting. The hearing aid impulse response was measured for the dummy head placed at eight closely spaced locations in a typical office. The feedback cancellation in the hearing aid used a set of filter coefficients that were initialized for one location within the room, and then allowed to adapt to the feedback path measured at the same or to a different location. The maximum stable gain for the hearing aid was then estimated without feedback cancellation, for the initial set of feedback cancellation filter coefficients prior to adaptation, and for the feedback cancellation filter after adaptation. A low-order ARMA model combining a fixed set of poles with an adaptive FIR filter is shown to be effective in representing the feedback path exclusive of reverberation. Increasing the adaptive filter length has only a small benefit in improving the feedback cancellation performance due to the inability of the system to model the room reverberation. The mismatch between the modeled and actual feedback paths limits the headroom increase that can be achieved when using feedback cancellation, and varies with the location within the room.     

应用于声反馈抑制的变步长归一化子带自适应滤波算法*

针对自适应滤波算法中稳态失调量和收敛速度之间的矛盾,提出了一种新的变步长归一化子带自适应滤波算法。该算法在系统噪声抵消原理的基础上,用迭代收缩的方法估计得到无噪先验子带误差的功率,对每个子带步长进行更新。对所提出的算法进行数学分析,可以得出该算法是稳定的和收敛的。在长回声路径和短回声路径两种情况下,将该算法应用于助听器声反馈抑制系统中。相对于其他归一化子带自适应滤波算法,仿真实验表明,所提算法实现了更快的收敛速度,获得了更低的失调量。     

Experimental evaluation of leaky least-mean-square algorithms for active noise reduction in communication headsets

An adaptive leaky normalized least-mean-square (NLMS) algorithm has been developed to optimize stability and performance of active noise cancellation systems. The research addresses LMS filter performance issues related to insufficient excitation, nonstationary noise fields, and time-varying signal-to-noise ratio. The adaptive leaky NLMS algorithm is based on a Lyapunov tuning approach in which three candidate algorithms, each of which is a function of the instantaneous measured reference input, measurement noise variance, and filter length, are shown to provide varying degrees of tradeoff between stability and noise reduction performance. Each algorithm is evaluated experimentally for reduction of low frequency noise in communication headsets, and stability and noise reduction performance are compared with that of traditional NLMS and fixed-leakage NLMS algorithms. Acoustic measurements are made in a specially designed acoustic test cell which is based on the original work of Ryan et al. ["Enclosure for low frequency assessment of active noise reducing circumaural headsets and hearing protection," Can. Acoust. 21, 19-20 (1993)] and which provides a highly controlled and uniform acoustic environment. The stability and performance of the active noise reduction system, including a prototype communication headset, are investigated for a variety of noise sources ranging from stationary tonal noise to highly nonstationary measured F-16 aircraft noise over a 20 dB dynamic range. Results demonstrate significant improvements in stability of Lyapunov-tuned LMS algorithms over traditional leaky or nonleaky normalized algorithms, while providing noise reduction performance equivalent to that of the NLMS algorithm for idealized noise fields.     

Design and analysis of a BLPC vocoder-based adaptive feedback cancellation with probe noise

The band-limited linear predictive coding (BLPC) vocoder-based adaptive feedback cancellation (AFC) removes the high-frequency bias, while the low frequency bias persists between the desired input signal and the loudspeaker signal in the estimate of the feedback path. In this paper, we present a BLPC vocoder-based adaptive feedback canceller with probe noise with an objective of reducing the low-frequency bias in digital hearing-aids. A step-wise mathematical analysis of the proposed feedback canceller is presented employing the recursive least square and normalized least mean square adaptive algorithms. It is observed that the optimal solution of the feedback path is unbiased for an unshaped probe noise, but is biased for a shaped probe signal; the bias term does not consist of correlation between the desired input and the loudspeaker output. The identifiability conditions are analysed and it is shown that a delay, greater than or equal to the length of the adaptive filter, must be introduced in the forward path to achieve an unbiased feedback path estimate. Algorithm analysis and computer simulations presented in this paper justify the reason for selecting the proposed design over the existing BLPC vocoder-based feedback cancellation algorithm.     

啸叫快速抑制的助听器回声抵消算法

针对助听器回声路径快速变化下易产生啸叫的问题,本文提出一种变步长标准最小均方差-陷波器(Variable Step Normalized least mean square-Notch Filter,VSN-NF)算法。在回声路径相对稳定时,提出一种基于状态分类的变步长标准最小均方差算法来估计回声信号。算法根据滤波器系数能量的长时平均值和短时平均值,将滤波器当前状态分为收敛态、过渡态与稳态,并根据不同状态选择不同的步长。在路径突然变化并产生啸叫时,算法通过关闭变步长NLMS算法来稳定啸叫频点,然后基于ZoomFFT算法动态生成陷波器来进行啸叫抑制;当啸叫抑制后,再开启变步长NLMS进行回声估计。针对易产生多频点啸叫的回声路径,VSN-NF算法还引入不同频带的两个陷波器来进行双频点啸叫抑制。同其它助听器回声抵消算法的对比实验显示,VSN-NF算法的回波抵消性能最好,尤其具有快速啸叫抑制能力。此外,算法生成的语音质量较高,实时性能好,适合于像助听器类的低功耗、小体积产品。      

Lattice form adaptive infinite impulse response filtering algorithm for active noise control

In some situations of active noise control, infinite impulse response (IIR) filters are more suitable than finite impulse response (FIR) filters owing to the poles in the transfer function. A number of algorithms have been derived for applying IIR filters in active noise control; however, most of them use the direct form IIR filter structure, which faces the difficulties of checking stability and relatively slow convergence speed for noise composed of narrow-band components with large power disparity. To overcome these difficulties along with using the direct form IIR filters, a new adaptive algorithm is proposed in this paper, which uses and updates the lattice form adaptive IIR filter in an active noise control system. Full mathematical derivations of the proposed algorithm are presented, and the comparison between the proposed algorithm and the commonly used filtered-u LMS and filtered-v LMS algorithms shows the superiority of the proposed algorithm.     

基于干扰对消的红外焦平面非均匀性校正算法

红外焦平面器件的非均匀性产生机理复杂,难以准确拟合探测元响应曲线。提出了一种基于相关干扰抵消的非均匀性校正算法,以预先采集到的一帧黑体面源图像做为自适应干扰对消器的参考输入图像,自适应滤波器由参考输入图像迭代计算出待校正红外图像的空间噪声的最佳估计,实现从空间噪声中提取真实图像信号。自适应滤波算法采用变步长最小均方误差算法,减少了算法的运算量,提高了算法的收敛速度。理论分析以及针对实际红外图像的仿真结果表明,提出的算法校正效果好,收敛速度快,更易于工程实现。     

IMPLEMENTATION OF A BROADBAND DUCT ANC SYSTEM USING ADAPTIVE SPATIALLY FEEDFORWARD STRUCTURE

An adaptive spatially feedforward algorithm is proposed for broadband attenuation of noise in ducts. Acoustic feedback generally exists in this active noise control structure. Munjal and Eriksson (1988 Journal of Acoustical Society of America84, 1086-1093) derived an ideal controller for the spatially feedforward structure. The ideal controller can be partitioned into two parts. The first part represents a repetitive controller that can be implemented by an infinite impulse response (IIR) filter, whereas the second part represents the dynamics of transducer that can be implemented by a finite impulse response (FIR) filter. In the paper, the IIR filter is merged with the original plant. The FIR filter is adaptively updated by the least-mean-square (LMS) algorithm to accommodate perturbations and uncertainties in the system. The proposed algorithm is implemented via a floating point digital signal processor and compared with other commonly used algorithms such as the Filtered-X LMS algorithm, the feedback neutralization algorithm, and the Filtered-U LMS algorithm. Experimental results show that the system has attained 15·7 dB maximal attenuation in the frequency band 200-600 Hz.     

Variable step-size based method for acoustic feedback modeling and neutralization in active noise control systems

This paper investigates the issue of the acoustic feedback during online operation of active noise control (ANC) systems. In the existing approach, two FIR filters are used for this task: adaptive for feedback path modeling (FBPM) and fixed for feedback neutralization (FBN). Previously, a simplified method is proposed where these two tasks of modeling and neutralization have been combined into one feedback path modeling and neutralization (FBPMN) adaptive filter. Here we introduce an intuition based variable step size (VSS) parameter, for LMS equation of FBPMN filter. This VSS is motivated from the fact that the error signal of FBPMN filter contains a disturbance-component that is decreasing in nature. The computer simulations are carried out for single-channel and multichannel ANC systems. It is demonstrated that the proposed method achieves better performance than the existing methods.     

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.     

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。     

Hybrid feedforward-feedback active noise reduction for hearing protection and communication

A hybrid active noise reduction (ANR) architecture is presented and validated for a circumaural earcup and a communication earplug. The hybrid system combines source-independent feedback ANR with a Lyapunov-tuned leaky LMS filter (LyLMS) improving gain stability margins over feedforward ANR alone. In flat plate testing, the earcup demonstrates an overall C-weighted total noise reduction of 40 dB and 30-32 dB, respectively, for 50-800 Hz sum-of-tones noise and for aircraft or helicopter cockpit noise, improving low frequency (<100 Hz) performance by up to 15 dB over either control component acting individually. For the earplug, a filtered-X implementation of the LyLMS accommodates its nonconstant cancellation path gain. A fast time-domain identification method provides a high-fidelity, computationally efficient, infinite impulse response cancellation path model, which is used for both the filtered-X implementation and communication feedthrough. Insertion loss measurements made with a manikin show overall C-weighted total noise reduction provided by the ANR earplug of 46-48 dB for sum-of-tones 80-2000 Hz and 40-41 dB from 63 to 3000 Hz for UH-60 helicopter noise, with negligible degradation in attenuation during speech communication. For both hearing protectors, a stability metric improves by a factor of 2 to several orders of magnitude through hybrid ANR.     

改进的多重网格法重建含遮拦物的干涉波前

阐述了由单张干涉图求取相位主值图像及最小二乘相位恢复。推导出基于梯度拟合的泊松方程及其离散化形成后,详细讨论了多重网格法对此方程求解的原理和过程。结合路径无关与路径相关算法的优点,设计了自适应最优路径法作为多重网格法的预处理,改进迭代的初始条件,提高了重建精度,同时大大加快了收敛速度。实验结果证明改进的多重网格法对含遮挡物的干涉图能获得很好的波前重建效果。     

Performance analysis of Wilcoxon-based machine learning nonlinear equalizers for coherent optical OFDM

In the recent research on the mitigation of nonlinearities in CO-OFDM systems, it has been seen that various types of non-robust algorithms (based on minimization of least square error principle) are used for learning of nonlinear equalizer. Moreover, it is well known that performance of nonlinear equalizer learned by robust algorithms is not easily affected by the outliers. In this paper, some robust algorithms such as Wilcoxon Multilayer Perceptron (WMLP), Wilcoxon Generalized Radial Basis function (WGRBF) and Wilcoxon Robust Extreme Learning Machine (WRELM) for the performance enhancement of CO-OFDM system have been analyzed. Subsequently, the performance enhancement capability of both the algorithms i.e., robust and non-robust has been compared in this study. It has been observed that the nonlinear equalizers trained with Wilcoxon approach based learning algorithm offer improved performance in terms of Q-Factor as compared to non-robust algorithms. In this study K-means machine learning based training algorithm is used to cluster the points at their desired locations. From obtained numerical results, it has been observed that the improvement in Q-Factor with Wilcoxon multilayer perceptron algorithm w.r.t its non-robust solution is?~?0.65 dB which is significantly higher than the value?~?0.2 dB with both the other mentioned robust algorithms w.r.t their non-robust counterparts. From the comparison of robust algorithms performance on the basis of convergence rate, it has been professed that the WRELM converges 100 and 7 times faster than WMLP and WGRBF respectively.     

基于变步长自适应滤波器在激光多普勒测量中的去噪研究

提出了一种自适应滤波算法应用于激光多普勒测量中的去噪方法,根据变步长自适应滤波算法的步长调整原则,分析了变步长最小均方算法的步长与误差关系曲线特点.研究表明,通过变步长自适应滤算法可有效地消除激光多普勒测量中由于声光调制、电光调制等引入的多频率噪音干扰.该算法简单、收敛性能强,仿真验证了该算法的优越性.     

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.     

存在声反馈的前馈有源噪声控制系统性能分析

在一些应用场合,前馈有源噪声控制系统中次级源产生的声信号会反馈至参考传声器,影响参考信号质量和系统稳定,导致控制性能下降。引入了等效次级路径的概念,并通过等效次级路径与实际路径的相位偏差分析存在声反馈时的收敛性能。若某些频率的相位偏差大于90°,则这些频率附近将较难收敛,降噪性能下降,甚至导致系统不稳定。通过仿真和实验对单指向传声器声学方法、自适应滤波u型最小均方差(FuLMS)算法、反馈中和算法和在线建模算法共4种解决声反馈问题的方法的性能进行了比较。结果表明,4种方法都能提高存在声反馈时的前馈有源噪声控制系统的性能,有效解决声反馈引起的问题,但各有优缺点。单指向传声器方法最为方便,但低频指向性较差。FuLMS算法运算量较低,但不能保证收敛。反馈中和算法性能最好,但当系统时变时鲁棒性较差。在线建模算法不需要额外滤波器,但由于参数调节复杂,降噪性能稍差。