基于信号包络和互相关的双端通话检测算法研究

声学回声消除(AEC)系统依赖于自适应滤波器的回声路径估计,当麦克风接收的信号存在回声和近端信号时,可能出现模拟回声路径的自适应滤波器发散,导致回声消除性能下降,严重时影响双端通话质量。一个成熟的声学回声消除器应该包含有双端通话检测算法,针对该问题,提出一种准确度高、性能稳定的基于信号包络检测(Env)和归一化互相关(NCC)估计相结合的双端通话检测(DTD)算法。该算法先使用远端信号与麦克风信号的能量包络来判断双端通话是否发生,当包络检测不能准确地判断双端通话时,再使用远端信号与麦克风信号的互相关估计对双端通话进行最终判断,保证双端通话检测的准确性。仿真实验表明,提出的算法可以准确判断双端通话的开始与结束,并且受回声路径变化的影响较小,提升了AEC系统的性能。     

变步长自适应滤波算法的统一框架及其矢量扩展

针对大量的变步长自适应滤波算法,提出了一种采用约束最优化方法描述变步长自适应滤波算法的统一框架.在该框架下,不同算法的目标函数或决策变量不同.利用该框架,将非参数变步长归一化最小均方误差(NPVSS-NLMS)算法扩展到矢量空间,导出一种新的变步长仿射投影算法.理论分析与计算机仿真表明,该算法不仅能根据输出误差自适应调整步长,而且对强相关输入信号能够保持良好的收敛速度、很小的稳态误差和很快的跟踪速度.将该算法应用于回波抵消,其稳态误差比NPVSS-NLMS算法低近5dB.     

自适应变步长正交约束盲源分离算法

将盲源分离算法通常应用到的白化预处理方法转化为权值正交约束条件下的分离算法,使得分离算法由无约束算法转变为有约束算法,消除了在估计白化矩阵时引入的误差和分离输出存在的尺度不确定性。因为算法的收敛速度和稳态误差是一对矛盾,所以结合变步长思想,提出了一种新的自适应变步长的权值正交约束盲源分离算法。该算法步长是基于分离状态的,其学习速率由信号的分离程度自适应地选取,因而能很好地解决收敛速度和稳态误差之间的矛盾。仿真实验表明,该算法比非约束算法,固定步长的权值正交约束的盲源分离算法具有更好的分离性能。     

VoIP回声消除器设计及算法研究

本文提出了一种与线性预测编解码器相结合的新声学回声消除器,由去相关可变步长的NLMS自适应算法和基于回声路径失配方差的双端通话检测算法所组成.Matlab仿真结果表明,与Gordy所提出的回声消除算法相比,本文提出的算法在双端通话和回声路径改变时判别更准确,收敛速度更快;在收敛状态时,ERLE值平均提高了15dB,失调误差平均降低了10dB,具备更好的回声消除性能.     

一种基于峭度累积量比例微分控制的盲源分离学习率

自然梯度算法由于良好的分离性能在盲源分离中占有重要的地位,但该算法基于固定步长时,无法很好兼顾收敛速度和稳态误差。本文借鉴自动化控制的PID （Proportion Integration Differentiation ）算法,提出一种与分离状态紧密结合的变步长学习率算法。由于完成分离的信号峭度累积量是一个固有值,分离过程的信号峭度累积量与固有值将有一个不断减小的误差值。该算法以指数函数值来体现该误差值。再利用该误差构成比例微分的变步长算法,其中的步长初始值就相当于控制误差的比例值,而误差的微分项则得到加速的调整值。该算法仿真实验结果与固定步长自然梯度盲源分离算法的仿真实验结果对比：对应于初始步长的一个最大值和一个最小值,该算法的两次迭代次数均低于采用固定步长算法的迭代次数,并且对于不同类型信号在两次迭代次数间的差值约10～40次,而两种算法的稳态误差是相同的。     

一种新的变步长恒模盲均衡算法

针对固定步长恒模盲均衡算法在收敛速度和稳态剩余误差之间存在的问题,在应用变步长的思想基础上,利用均方误差的变换作为控制步长的因子,提出了一种新的自适应时变步长恒模盲均衡算法(VASCMA).对新算法进行了理论分析和计算机仿真,仿真时采用两种不同的调制信号通过三种不同信道,得到两种算法的均方误差的收敛曲线和收敛后均衡器输出的星座图,仿真结果均表明,改进算法具有较快的收敛速度和较小的剩余误差.     

一种改进的变步长ELMS算法

在简单讨论基本最小均方(LMS)算法的基础上,引入了扩展的最小均方(ELMS)算法,并分析说明了该算法能达到更小的稳态MSE。改进的变步长ELMS算法是在对有用信号的预测中采用了自适应为归一化的的最小均方(NLMS)预测估计器,步长的迭代中引入遗忘因子i,利用其与误差信号的加权和来产生新的步长参与迭代。理论分析与计算机仿真结果表明,该算法有较好的收敛性能和较小的稳态失调。     

迭代变步长LMS算法及性能分析

针对固定步长LMS(Least Mean Square)算法(FXSSLMS)不能同时满足快速收敛和小稳态失调误差的问题,该文提出了迭代变步长LMS算法(IVSSLMS)。与已有的变步长LMS算法(VSSLMS)不同,该算法的步长因子不再是由输出误差信号控制,而是建立了与迭代时间的改进Logistic函数非线性关系,克服了定步长算法收敛慢及已有变步长算法抗噪声干扰能力差的问题。最后从理论上分析了算法的性能,给出了其参数取值方法。理论分析和仿真均表明,所提算法能够在快速收敛情况下获得小的稳态失调误差,在有色噪声干扰下稳态失调误差比已有算法降低了约7 dB。     

一种新型变步长CMA盲均衡算法

针对传统固定步长CMA盲均衡算法中收敛速度和剩余误差这对矛盾,提出了一种新型变步长恒模盲均衡算法,即由瑞利分布函数实施对其步长的调节,通过调整该步长公式中的两个参数以加快收敛速度和减小剩余误差,并且在此基础上对该算法进行了改进。用4QAM信号,通过典型电话信道对固定步长的CMA算法,基于瑞利步长的CMA和改进后的CMA算法进行计算机仿真。通过对仿真出的算法收敛曲线以及输出星座图进行分析,最终得出在瑞利步长算法的基础上改进后的CMA算法克服了前两种算法的缺点,即具有收敛速度更快,剩余误差更小的优点。     

α噪声环境下整体最小平均P-范数IIR自适应滤波算法

当无限冲激响应(IIR)系统输入和输出信号中都存在α稳定噪声干扰,传统的最小平均P-范数算法(LMP)的解会出现较大偏差,本文提出了一种自适应IIR滤波整体最小平均P-范数(IIR_TLMP)算法,算法中整体考虑输入和输出信号的α稳定噪声干扰,将最小化l_p范数Rayleigh商采用随机梯度法得到自适应IIR滤波方程。通过仿真首先考察了特征指数和步长因子等主要参数对TLMP算法性能的影响,最后分别在时不变和时变系统中,将TLMP算法与LMP算法的性能在进行了比较,结果显示TLMP有更快的收敛速度和更小的误差。      

Multichannel signal processing for data communications in thepresence of crosstalk

Transceiver designs for multiple coupled channels typically treat the crosstalk between adjacent twisted pairs as random noise uncorrelated with the transmitted signal. The authors propose a transmitter/receiver pair that compensates for crosstalk by treating an entire bundle of twisted pairs as a single multi-input/multi-output channel with a (slowly varying) matrix transfer function. The proposed transceiver uses multichannel adaptive FIR filters to cancel near- and far-end crosstalk, and to pre- and postprocess the input/output of the channel. Linear pre- and postprocessors that minimize mean squared error between the received and transmitted signal in the presence of both near- and far-end crosstalk are derived. The performance of an adaptive near-end crosstalk canceller using the stochastic gradient (least-mean-square) transversal algorithm is illustrated by numerical simulation. Plots of mean squared error versus time and eye diagrams are presented, assuming a standard transmission line model for the channel. A signal design algorithm that maps a vector input bit stream to a stream of channel symbol vectors is also presented and illustrated explicitly for s simple model of two coupled channels     

Measurements of crosstalk between closely-packed lossy microstrips on silicon substrates

The measured near-end and far-end crosstalks for closely-packed microstrips are reported. The near-end crosstalk is less than 10% and the far-end crosstalk is less than 5% (of the driven signal) between two microstrips with 10 mu m width and 10 mu m spacing, when the active line is driven by a fast step pulse with approximately 40 ps rise time. Based on their measurements, the authors believe that closely-packed lossy microstrips can be used for high speed digital signal transmission, without much concern of crosstalk.<>     

Adaptive echo cancellation using least mean mixed-norm algorithm

A novel algorithm for echo cancellation is presented in this work. The algorithm consists of simultaneously applying the least mean square (LMS) algorithm to the near-end section of the echo canceller and the least mean fourth (LMF) algorithm to the far-end section. This new scheme results in a substantial performance improvement over the LMS algorithm and other algorithms     

Convergence analysis of adaptive filtering algorithms with singulardata covariance matrix

The paper provides a rigorous analysis of the behavior of adaptive filtering algorithms when the covariance matrix of the filter input is singular. The analysis is done in the context of adaptive plant identification. The considered algorithms are LMS, RLS, sign (SA), and signed regressor (SRA) algorithms. Both the signal and weight behavior of the algorithms are considered. The signal behavior is evaluated in terms of the moments of the excess output error of the filter. The weight behavior is evaluated in terms of the moments of the filter weight misalignment vector. It is found that the RLS and SRA diverge when the input covariance matrix is singular. The steady-state signal behavior of the LMS and SA can be made arbitrarily fine by using sufficiently small step sizes of the algorithms. Indeed, the long-term average of the mean square excess error of the LMS is proportional to the algorithm step size. The long-term average of the mean absolute excess error of the SA is proportional to the square root of the algorithm step size. On the other hand, the steady-state weight behavior of both the LMS and SA have biases that depend on the weight initialization. The analytical results of the paper are supported by simulations     

Hybrid LMS-LMF algorithm for adaptive echo cancellation

The coefficients of an echo canceller with a near-end section and a far-end section are usually updated with the same updating scheme, such as the LMS algorithm. A novel scheme is proposed for echo cancellation that is based on the minimisation of two different cost functions, i.e. one for the near-end section and a different one for the far-end section. The approach considered leads to a substantial improvement in performance over the LMS algorithm when it is applied to both sections of the echo canceller. The convergence properties of the algorithm are derived. The proposed scheme is also shown to be robust to noise variations. Simulation results confirm the superior performance of the new algorithm     

LMS-LMF adaptive scheme for echo cancellation

The authors present a novel algorithm for echo cancellation. The algorithm consists of simultaneously applying the LMS algorithm to the near-end section of the echo canceller, and a controlled mixed LMS-LMF algorithm to the far-end section. This combination results in a substantial improvement in performance of the proposed scheme over the LMS and the LMF algorithms     

Crosstalk bandwidth and stability analysis in graphene nanoribbon interconnects

Based on transmission line modeling (TLM), and using the Nichols chart, we present a bandwidth and stability analysis, together with step time responses, for coupled multilayer graphene nanoribbon (MLGNR) interconnects that is inquired for the first time. In this analysis, the dependence of the degree of crosstalk relative stability for coupled MLGNR interconnects comprising of both capacitive and mutual-inductive couplings between adjacent MLGNR has been acquired. The obtained results show that with increasing the length or decreasing the width of the MLGNRs, the stability in near-end output increases. While, any increase in the length or width of MLGNRs, decrease the stability of far-end output. Also, by increasing capacitive coupling or decreasing inductive coupling, the near-end output becomes more stable, and the far-end output becomes less stable. Moreover, any increase in the length or capacitive coupling, decreases the bandwidth, whereas any increase in the width or inductive coupling, increases the bandwidth. Finally, transient simulations with Advanced Design System (ADS) show that the model has an excellent accuracy.     

Double-Talk-Robust Prediction Error Identification Algorithms for Acoustic Echo Cancellation

The performance of an acoustic echo canceller may be severely degraded by the presence of a near-end signal. In such a double-talk situation, the variance of the echo path estimate typically increases, resulting in slow convergence or even divergence of the adaptive filter. This problem is usually tackled by equipping the echo canceller with a double-talk detector that freezes adaptation during near-end activity. Nevertheless, there is a need for more robust adaptive algorithms since the adaptive filter's convergence may be affected considerably in the time interval needed to detect double-talk. Moreover, in some applications, near-end noise may be continuously present and then the use of a double-talk detector becomes futile. Robustness to double-talk may be established by taking into account the near-end signal characteristics, which are, however, unknown and time varying. In this paper, we show how concurrent estimation of the echo path and an autoregressive near-end signal model can be performed using prediction error (PE) identification techniques. We develop a general recursive prediction error (RPE) identification algorithm and compare it to three existing algorithms from adaptive feedback cancellation. The potential benefit of the algorithms in a double-talk situation is illustrated by means of computer simulations. It appears that especially in the stochastic gradient case a huge improvement in convergence behavior can be obtained     

Crosstalk Stability Analysis in Multilayer Graphene Nanoribbon Interconnects

In this paper a time-domain response and Nyquist stability criterion to acquire dependence of degree of crosstalk relative stability based on transmission lines modeling (TLM) is investigated for coupled multilayer graphene nanoribbon (MLGNR) interconnects. This is the first instance that such an analysis has been presented for coupled MLGNR consisting of both capacitive and mutual-inductive couplings. The near-end and far-end outputs of coupled MLGNR individually are compared in two cases, with considering both couplings and without them (single MLGNR). It is observed that the near-end output of the system together with both couplings is more stable and at its far-end output, an induced voltage is created. By increasing capacitive coupling or decreasing inductive coupling, the near-end output becomes more stable. Also, the results of changes of length and width of each ribbon show that by increasing the length and decreasing the width, the coupled MLGNR interconnects become more stable.     

Gabor expansion for adaptive echo cancellation

A good echo cancellation algorithm should have a fast convergence rate, small steady-state residual echo, and less implementation cost. The normalized least mean square (NLMS) adaptive filtering algorithm may not achieve this goal. We show that using the Gabor expansion is a way to achieve this goal. For direct digital signal processing compatibility the Gabor expansion introduced in this paper is for discrete-time signals, although the Gabor expansion also can be used for continuous-time signals. The Gabor expansion can be defined as a discrete-time signal representation in the joint time-frequency domain of a weighted sum of the collection of functions (known as the synthesis functions). There are several design issues in the echo canceller based on the Gabor expansion: the design of the analysis functions for the far-end speech, the design of the analysis functions for the near-end signal containing the echo plus the near-end speech, the design of the adaptive filters in the subsignal path, and the design of the synthesis functions. All the adaptive filters are designed using identical NLMS adaptive filtering algorithms