数字用户环路中回波消除的研究及实现

在语音和数据通信中都存在回波现象,回波影响通信的质量。文章详细介绍了自适应回波抵消器的一种具体实现方法,从而为解决目前程控交换机中回波抵消器电路复杂、收敛速度慢和精度差等问题提供了一种有效途径。     

自适应语音消噪算法的研究与仿真

针对语音通信中的噪声问题,对最小均方误差(LMS)算法进行研究。研究发现,该算法在收敛速度与稳态误差之间始终存在着矛盾,为此在F-LMS算法的基础上,提出一种改进的LMS算法,该算法通过引入误差加权累加的平均值的方法来更好地解决两者之间的矛盾,并通过计算机仿真证实了该算法具有良好的收敛性能和稳态性能,最后利用传统的LMS算法、F-LMS算法和改进的LMS算法对带有噪声的信号进行了消噪处理,结果表明:在三种算法中,改进的LMS算法的噪声消除效果最好。     

自适应最小均方算法的本质

本文指出最小均方算法并不能使均方误差最小,证明了最小均方算法实际上是一种加权最小二乘算法。     

基于改进NLMS算法的自适应滤波算法

最小均方算法是应用最广泛的自适应算法之一,但其收敛速度欠佳。在传统NLMS算法的基础上,提出了重复调整归一化最小均方算法(DRNLMS)即在相邻两输入信号样本的间隔时间进行额外调整运算,以提高算法的收敛性,并通过计算机仿真实现该算法。     

雪深超声回波信号的自适应滤波建模方法

针对现阶段获取积雪数据准确度不高的问题,根据超声回波信号特征并结合建模方法和现代数字信号处理技术,提出一种积雪超声回波信号的自适应滤波建模方法,利用包络检波算法和曲线拟合对回波信号包络中的确定性信号进行拟合并结合自适应滤波算法,在误差信号的反馈下通过迭代使输入信号逼近参考信号,改变输入信号幅值和频率也可以稳定地收敛。通过这种方法可以合成积雪回波信号,准确描述雪盖的层理结构,有效地降低了噪声干扰,拟合匹配度得到提高。     

带有时变非线性预处理的立体声回波消除方法研究

就立体声回波消除问题提出了两种新的信号非线性预处理方法，并给出了相应的自适应算法。新的预处理方法比Benesty(1997)及Joncour(1998)的方法对信号的非线性处理部分要少，因而对语音信号的质量影响有所下降。仿真结果表明，新的预处理方法与其实现算法相结合应用于立体声回波消除时，比Benesty(1997)及Joncour(1998) 所提方法的效果更好。     

基于LMS算法的自适应滤波器在声学回声消除中的应用

阐述了自适应滤波器的基本原理,在介绍LMS自适应滤波算法的基础上,利用TMS320VC5402 DSK的软、硬件平台,进行LMS自适应滤波器的设计仿真,并对语音回声进行消除。实验表明,该算法在应用中具有良好的滤波性能,达到了较好的回波消除效果。     

基于最小均方误差的串扰消除多用户检测算法

在存在强多址干扰的直接序列扩频码分多址(DS-CDMA)系统中对传统串行干扰消除检测器的优点及缺陷进行分析,提出一种基于最小均方误差的串行干扰消除多用户检测算法。该算法能够对时变信道环境进行有效跟踪,避免判决误差扩散。仿真结果表明,在加性高斯白噪声环境中一个同步DS-CDMA系统中对于信号功率弱的用户,该算法相比传统串行干扰消除算法及迫零算法的检测性能有较大的改善,在消除原有检测算法检测精度不稳定的同时能提高算法的误码性能。     

呼叫中心系统中回声抵消算法的研究与实现

针对IP呼叫中心系统中的回声问题,对算法LMS（Least Mean Square）进行了研究。经研究发现,回声消除算法LMS在收敛速度与稳态误差之间始终存在着矛盾,即加快收敛速度,则稳态误差随之加大;减小稳态误差,则收敛速度随之减慢。研究的目的就是能够使两者之间的矛盾得到改善,能够更好地消除回声。研究的方法是在现有算法的基础上,提出了一种改进的LMS算法,通过计算机对该算法进行了仿真,以及利用DSP进行了回声消除,结论表明该算法具有良好的收敛性能和稳态性能,更好地改善了收敛速度与稳态误差之间的矛盾,消除效果较好。     

一种新的自适应算法在天线系统中的应用研究

研究了天线系统中一种新的自适应算法,为了显示新算法的优点,和传统的自适应算法以天线系统为背景做了比较.算法在LMS算法的基础上作了一定的修改,通过在干扰来向设置零点来达到抑制干扰的目的.在几种干扰条件下对新算法和传统算法进行了仿真实验,通过分析仿真结果,可以看出,随着干扰的加强,天线对干扰来向的零陷会逐渐加深,从而达到干扰抑制的目的;新算法克服了传统算法在应用上的不足,突破了传统算法在应用上面的局限性.在应用中,从一定程度上弥补了传统算法的不足.新的算法具有很好的实用价值和研究价值.     

An improved new error estimation algorithm for optimal filter lengths for stereophonic acoustic echo cancellation

In this paper, we propose an new error estimate algorithm (NEEA) for stereophonic acoustic echo cancellation (SAEC) that is based on the error estimation algorithm (EEA) in [Nguyen-Ky T, Leis J, Xiang W. An improved error estimate algorithm for stereophonic acoustic echo cancellation system. In: International conference on signal processing and communication systems, ICSPCS’2007, Australia; December 2007]. In the EEA and NEEA, with the minimum error signal fixed, we compute the filter lengths so that the error signal may approximate the minimum error signal. When the echo paths change, the adaptive filter automatically adjusts the filter lengths to the optimum values. We also investigate the difference between the adaptive filter lengths. In contrast with the conclusions in [Khong AWH, Naylor PA. Stereophonic acoustic echo cancellation employing selective-tap adaptive algorithms. IEEE Trans Audio, Speech, Lang Process 2006;14(3):785-96, Gansler T, Benesty J. Stereophonic acoustic echo cancellation and two channel adaptive filtering: an overview. Int J Adapt Control Signal Process 2000;4:565-86, Benesty J, Gansler T. A multichannel acoustic echo canceler double-talk detector based on a normalized cross-correlation matrix. Acoust Echo Noise Control 2002;13(2):95-101, Gansler T, Benesty J. A frequency-domain double-talk detector based on a normalized cross-correlation vector. Signal Process 2001;81:1783-7, Eneroth P, Gay SL, Gansler T, Benesty J. A real-time implementation of a stereophonic acoustic echo canceler. IEEE Trans. Speech Audio Process 2001;9(5):513-23, Gansler T, Benesty J. New insights into the stereophonic acoustic echo cancellation problem and an adaptive nonlinearity solution. IEEE Trans. Speech Audio Process 2002; 10(5):257-67, Benesty J, Gansler T, Morgan DR, Sondhi MM, Gay SL. Advances in network and acoustic echo cancellation. Berlin: Springer-Verlag; 2001], our simulation results have shown that the filter lengths can be different. Our simulation results also confirm that the NEEA is better than EEA and SM-NLMS algorithm in terms of echo return loss enhancement.     

基于声回波抵消两路算法的改进更新逻辑

声回波抵消两路算法被广泛用来检测系统双向通话;基于声回波抵消两路算法,提出了一种改进的控制更新逻辑。此更新逻辑通过比较滤波器的回波返回损失(ERLE),判断是否对滤波器进行更新。此改进更新逻辑能正确检测系统双向通话,避免滤波器的错误更新,并提高两路算法的收敛速度,减小存储器资源和计算量。仿真结果证实了此更新逻辑的有效性。     

改进自适应对消算法在工业噪声处理中的应用

分析了工业环境噪声的特点,将自适应噪声对消算法应用到工业噪声的处理当中.在传统最小均方(LMS)算法及基于Lorentzian函数的变步长LMS算法的基础上进一步进行约束稳定性条件处理,提出了一种约束稳定性变步长LMS算法,并在Matlab平台上进行了仿真验证.结果表明:算法具有更快的收敛速度以及更小的稳态误差,并且能有效地降低梯度噪声对算法性能的影响.     

Improved variable step-size NLMS adaptive filtering algorithm for acoustic echo cancellation

Acoustic echo canceller (AEC) is used in communication and teleconferencing systems to reduce undesirable echoes resulting from the coupling between the loudspeaker and the microphone. In this paper, we propose an improved variable step-size normalized least mean square (VSS-NLMS) algorithm for acoustic echo cancellation applications based on adaptive filtering. The steady-state error of the NLMS algorithm with a fixed step-size (FSS-NLMS) is very large for a non-stationary input. Variable step-size (VSS) algorithms can be used to decrease this error. The proposed algorithm, named MESVSS-NLMS (mean error sigmoid VSS-NLMS), combines the generalized sigmoid variable step-size NLMS (GSVSS-NLMS) with the ratio of the estimation error to the mean history of the estimation error values. It is shown from single-talk and double-talk scenarios using speech signals from TIMIT database that the proposed algorithm achieves a better performance, more than 3 dB of attenuation in the misalignment evaluation compared to GSVSS-NLMS, non-parametric VSS-NLMS (NPVSS-NLMS) and standard NLMS algorithms for a non-stationary input in noisy environments.     

一种改进的声测定位时延估计算法

研究了时延估计算法在被动声测定位中的应用,提出了一种改进的基于最大似然(ML)权函数的广义互相关时延估计算法。改进的算法采用加窗法和最小均方差（LMS)滤波法,弥补了原算法计算量大及无法消除回响干扰的不足。仿真结果表明,改进的算法计算复杂度明显降低,能够有效地消除回响干扰,具有较高的时延估计精度和鲁棒性。     

Low complexity LMS-type adaptive algorithm with selective coefficient update for stereophonic acoustic echo cancellation

Stereophonic acoustic echo cancellation (SAEC) has brought up recently much attention and found a viable place in a number of hands-free applications. In this paper, we propose an LMS-type algorithm for SAEC based on decomposing the long adaptive filter of each channel of the SAEC system into smaller subfilters. We further reduce the complexity of the algorithm by employing the selective coefficient update (SCU) method in each subfilter. This leads to a significant improvement in the convergence rate of the algorithm with low computational overhead. However, the algorithm has a high final mean-square error (MSE) at steady-state that increases as number of subfilters increases. A combined-error algorithm is presented that achieves fast convergence without compromising the steady state error level. Simulations demonstrate the convergence speed advantages of the combined-error algorithm.     

Packet based echo cancellation for VoIP networks

In today’s modern telephony network, VoIP is fast emerging as one of the main communication techniques. However, the performance and the quality of VoIP are affected by echo. Packet Based Echo Canceller (PBEC) is introduced, as a solution to cancel echo in the VoIP network. PBEC can replace the current echo cancellers, which are located in the Public Switched Telephony Network (PSTN) central switches. The operating principle of the PBEC is explained and its advantages are highlighted. The performance of the PBEC using different speech codecs is also studied. Using the PBEC, a maximum Echo Return Loss Enhancement (ERLE) of 37.39 dB has been achieved when used with the Pulse Code Modulation (PCM) based speech codec. From the simulation results, it can be seen that the performance of the Adaptive Differential Pulse Code Modulation (ADPCM) clearly matches the performance of the PCM based speech codec. The other major problem affecting the VoIP network is the issue of packet loss. This issue of packet loss has been successfully addressed in this paper by the insertion of random values. With the insertion of random values, the ERLE increases by 4.81 dB compared to when there is no insertion of random value. The PBEC with the utilization of random values would make the VoIP a better communication tool.     

A new robust double-talk detector based on the Stockwell transform for acoustic echo cancellation

Despite great developments in the field of acoustic echo cancellation (AEC), the presence of double-talk remains difficult problem. The main role of double-talk detection (DTD) is to control adaptation of the filter coefficients by halting their update in double-talk situations. In this paper, we propose a new method of DTD based on a time–frequency analysis that uses the Stockwell transform (ST).The ST is a time–frequency spectral localization method that combines the characteristics of the short-time Fourier transform and the wavelet transform. This method provides better time–frequency resolution, especially for non-stationary signals. In the experimental tests, the normalized least mean squares (NLMS) algorithm is used to update the filter coefficients along with speech signals taken from the TIMIT database. The obtained results show better performance compared to existing methods in terms of misalignment convergence and speech intelligibility enhancement.     

频率捷变的全双工数字自干扰抑制方法

针对极端频谱环境中强干扰对全双工系统性能的影响,提出了一种适用于频率捷变的全双工数字自干扰抑制方法。通过离线运算获取工作频带范围内的误差补偿模型,并利用该模型实时生成捷变频点的自干扰信道参数以重建自干扰信号并完成数字对消。数值仿真结果表明该方法在系统工作频带范围内可将自干扰抑制到噪底以下,并在整个频带具有较高一致性和良好的收敛性。