基于自适应神经模糊推理系统的噪声消除方法

针对信号处理领域噪声消除的实际问题,提出了一种基于模糊推理的自适应神经网络控制方法.通过自适应神经模糊推理系统(ANFIS)对非线性系统的结构和参数进行辨识与自学习,采用混合学习算法,对前向参数和结论参数分别辨识,在提高精度的同时可加快训练收敛的速度,使控制系统具有良好动静态性和鲁棒性,实现了消除通信系统中噪声的目标,最后对基于ANFIS的噪声消除系统进行了建模和仿真,并与自适应神经网络滤波方法的结果对比,其结果证明了该方法的有效性.     

一种频域脉冲最小均方误差杂波对消算法

针对“低慢小”探测雷达杂波多普勒主瓣淹没慢速弱目标问题,该文提出了频域脉冲LMS（FPLMS）算法来对消杂波。该算法利用杂波分量在脉间的平稳性,自适应地估计各距离单元杂波的复幅度来重构杂波,实现杂波对消。仿真结果表明：FPLMS算法能够有效对消杂波,消除杂波主瓣对目标检测的影响;且具有很窄的滤波器凹口,约为MTI滤波器的1/3,对速度大于1个速度分辨单元的目标几乎无信噪比损失,适用于“低慢小”探测雷达的杂波对消。     

一种具有宽带双极化低散射特征的微带阵列天线

针对阵列天线宽带散射缩减设计进行研究,设计了一种基于无源对消技术的低散射阵列天线,该新型微带阵列天线在宽频带内具有双极化低雷达散射截面（RCS, Radar Cross Section）性能;对基于两种散射性能不同的单元组成阵列的RCS性能进行了理论研究,进行了单元的散射幅度和相位对阵列RCS的影响分析;提出了一种加载T型缝隙的新型微带天线结构,该单元结构的辐射性能与散射性能能够进行独立调控和综合优化,该单元与传统微带贴片单元具有相似的辐射特性,并可在宽频带（带内和带外）内与传统微带单元产生有效相位差;将传统微带单元和加载T型缝隙的新型微带单元组成4×4阵列天线,仿真结果表明,提出的阵列天线在3GHz～7GHz（相对带宽80%）频带内实现了同极化RCS缩减,在3.3GHz～7GHz（相对带宽71.8%）频带内实现了交叉极化RCS缩减,缩减峰值分别为16.3dB和36.3dB,带内RCS缩减均值分别为14.1dB 和17.6dB;与传统微带阵列天线相比,提出的阵列天线增益下降小于0.1dB;提出的微带阵列天线具有高效率辐射和宽频带双极化低散射性能,为低散射阵列天线设计提供了新的思路。     

量子色散消除的研究进展

非局域色散消除是量子纠缠光源的非经典效应之一,在量子信息科学中有着重要的应用。详细介绍了非局域色散消除的概念、研究意义以及近几年国内外的发展状况。对频率纠缠光源的非局域色散消除、Franson干涉仪中的非局域色散消除、Hong-Ou-Mandel干涉仪中的局域色散消除等3种情况的研究进展进行了对比分析。在此基础上,对量子色散消除的研究前景进行了展望。     

基于SIW 的多波束CTS 阵列天线设计

文中设计了一款基于基片集成波导(SIW)的毫米波高增益多波束连续横向枝节(CTS)阵列天线,它 通过切换馈电端口实现多波束功能。该天线整体结构简单,采用印刷电路板工艺实现。天线主要包含馈电喇叭、平 面波转换结构以及辐射结构三个部分,由三层基板构成。馈源为基于SIW 的馈电喇叭,并在口径处添加匹配结构以 提高其辐射性能;平面波转换结构由SIW 抛物面和渐变耦合槽组成,可将馈电喇叭辐射出的柱面波转换为幅度服从 泰勒分布的平面波进而为CTS 阵列馈电,因此天线具有低副瓣的特性;辐射结构为1×8 的CTS 阵列,通过优化缝隙 宽度以保证每个单元辐射出相等的能量。天线工作在30 GHz,通过切换馈电端口可在±20°范围内实现波束切换,天 线测试结果与仿真结果吻合,验证了设计的合理性。     

Two-step design of critical control systems using disturbance cancellation integral controllers

An efficient critical control system design is proposed in this paper. The key idea is to decompose the design problem into two simpler design steps by the technique used in the classical loop transfer recovery method (LTR). The disturbance cancellation integral controller is used as a basic controller. Since the standard loop transfer recovery method cannot be applied to the disturbance cancellation controller, the nonstandard version recently found is used for the decomposition. Exogenous inputs with constraints both on the amplitude and rate of change are considered. The majorant approach is taken to obtain the analytical sufficient matching conditions. A numerical design example is presented to illustrate the effectiveness of the proposed design.     

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.     

一种高效的QMC检测算法

基于垂直分层空时码的MIMO-OFDM系统提出一种高效的QMC检测算法,该算法对信道矩阵进行一次排序QR分解,对最先检测的信号层采用ML-OSIC算法,用M算法检测中间的信号层,逐层增加保留值M以提高算法有效性,利用串行干扰消除检测余下的信号层。与QRD-M算法相比,QMC检测算法能降低计算复杂度。仿真结果表明,该算法以更低的计算复杂度获得更接近最大似然检测的性能,取得性能与复杂度之间的折中更理想。     

基于自适应噪声抵消的CZ单晶炉炉膛温度信号处理

为滤除CZ单晶炉炉膛温度信号在单晶生长过程中存在的低频干扰,提出一种基于噪声抵消技术的滤波方法.首先利用傅立叶级数构造出低频干扰的逼近信号,然后根据炉温信号的缓变特征建立能够获取低频干扰逼近信号的抵消器误差函数,最后利用一种改进的粒子群优化算法优化误差函数获得低频干扰的逼近信号,并用该逼近信号抵消低频干扰.实验结果表明,所提出的自适应噪声抵消滤波算法能够有效滤除CZ单晶炉炉膛温度信号中的低频干扰,并优于常用的滤波方法.     

A novel associative memory approach to speech enhancement in a vehicular environment

Numerous attempts have been undertaken to apply the spectral subtraction method to cancel noise perturbations but these efforts have yet to produce an algorithm that is able to adapt well to the environmental changes in the perturbations. In addition, the variants of the spectral subtraction method so far proposed in the literature would require a non-voice activity detector (NVAD), for a single microphone system, to store the perturbation. This is used as an estimate for the reference signal. Inaccuracy in the perturbation estimates causes the cleaned speech to be corrupted by musical artifacts, which is unacceptable. Post processing of signals corrupted by the musical artifacts is very costly. This paper provides an alternative approach that employs associative memory for speech enhancement. Extensive comparison is made using the soft computing approaches for noise cancellation based on associative memories. A set of stereo microphones captures the corrupted speech in a vehicle and is used to point to the closest associative memory location. The Wiener filter approach is used to cancel the noise. The paper discusses novel examples of the associative memories using the cerebellum model for noise modeling. Experimental results show the potential of these novel soft computing architectures in generating and adapting the required Weiner filters to cancel perturbation even at signal to noise ratio (SNR) of less than −13 dB.