MIMO系统中基于代价函数和排序模式的MMSE SIC检测器

针对多输入多输出空间多路复用系统,提出了一种基于代价函数和排序模式的多个并行分支的最小均方误差连续干扰消除检测器;具体而言,设计了选择规则来选择代价函数性能最好的分支,并通过利用不同的检测排序模式使得每个分支中的SIC算法按照信号干扰噪声比由高到低来检测信号,从而实现完全检测分集;为了进一步降低算法的计算复杂度,还提出了一种采用递归最小二乘算法的有效自适应接收机来更新滤波器权值向量,从而获得基于递归最小二乘算法的MB-SIC接收机的自适应实现;此外,还对提出的检测器在比特差错概率性能方面进行了分析;仿真结果表明,相比于现有的检测算法,提出的算法不仅具有较低的计算复杂度,而且能获得更好的误码率性能。     

On closure properties of GapP

We study the closure properties of the function classes GapP and GapP₊. We characterize the property of GapP₊ being closed under decrement and of GapP being closed under maximum, minimum, median, or division by seemingly implausible collapses among complexity classes, thereby giving evidence that these function classes don't have the stated closure properties.We show a similar result concerning operations we callbit cancellation andbit insertion: Given a functionf GapP and a polynomialtime computable function , we ask whether the functionsf ^* (x) andf ⁺ (x) are in GapP or not, wheref ^* (x) is obtained fromf(x) by cancelling the (x)-th bit in the binary representation off(x), andf ⁺ (x) is obtained fromf(x) by inserting a bit at position (x) in the binary representation off(x). We give necessary and sufficient conditions for GapP being closed under bit cancellation and bit insertion, respectively.     

一种智能传感器射频前端的低功耗设计与实现

叙述了一种应用于智能传感器的低功耗射频前端电路,包括低噪声放大器和下混频器。智能传感器的无线通信一般基于Zigbee协议,Zigbee接收机一般采用低中频的架构以获得灵敏度和低功耗之间较好的折中。主要研究了从提高晶体管跨导效率和提高电流利用效率两个角度实现低功耗的方法,低噪声放大器采用交叉耦合输入的噪声抵消结构,增强了输入管的等效跨导,因而在较低功耗代价下获得了低噪声系数并实现50Ω阻抗匹配;下混频器采用基于电流放大器的无源混频结构,输入跨导级通过电流复用提高了电流利用效率而输出跨阻级引入跨导增强技术减少了中频电流的泄漏,这使得在同等功耗水平下可以获得更高的线性度,即节省了功耗。讨论了电路设计过程并在TSMC 0.13μm CMOS射频工艺下进行流片验证,在1.2 V电压下整个前端电路消耗5.4 mW功耗和0.12 mm2芯片面积,仿真结果表明低噪声放大器获得了2.1 dB的噪声系数和小于-30 dB的S11,混频器转换增益为27.7 dB;而芯片测试得到的前端噪声系数为5.4 dB,IIP3达到5.5 dBm,能够满足智能传感器无线通信的需要。     

基于贝叶斯网络的航班延误波及研究

在民航业内,航班延误波及问题一直是影响航班延误的一个主要因素。基于贝叶斯网络（BN）,讨论了在繁忙的枢纽机场,其航班延误的波及问题。在实验中使用的数据,皆来自国内某大型航空公司的真实记录。通过建立延误波及模型和贝叶斯网络模型,探讨了相关航班中,进港延误和航班取消对离港延误的影响。学习的结果显示了进港延误（Arrival-delay）对离港延误（Departure-Delay）的波及现象的存在;以及波及现象在不同情况下的程度不同;相应的可采取的应对方式亦不相同。其中航班取消是一种釜底抽薪的应对方法,可以在一定程度上削弱上述条件下的延误波及,其削弱程度与航班取消的架次有关。基于该研究可以在机场发生大规模延误时,提供一个基本的参考。     

用于SPR检测的自消噪光电二极管阵列驱动电路

以检测SPR现象为目的,设计了一种新型的具有自消噪功能的光电二极管阵列驱动电路.该电路可以精确检测矩形区域内的光强分布,从而确定SPR共振角.电路选用滨松光子学株式会社(Hamamatsu)生产的S3903-1024Q型光电二极管阵列线性图像传感器作为光电转换器件,并以改进型电流积分方式进行驱动,可以根据检测环境的噪声...     

Fast correction of bleed-through distortion in grayscale documents by a blind source separation technique

Ancient documents are usually degraded by the presence of strong background artifacts. These are often caused by the so-called bleed-through effect, a pattern that interferes with the main text due to seeping of ink from the reverse side. A similar effect, called show-through and due to the nonperfect opacity of the paper, may appear in scans of even modern, well-preserved documents. These degradations must be removed to improve human or automatic readability. For this purpose, when a color scan of the document is available, we have shown that a simplified linear pattern overlapping model allows us to use very fast blind source separation techniques. This approach, however, cannot be applied to grayscale scans. This is a serious limitation, since many collections in our libraries and archives are now only available as grayscale scans or microfilms. We propose here a new model for bleed-through in grayscale document images, based on the availability of the recto and verso pages, and show that blind source separation can be successfully applied in this case too. Some experiments with real-ancient documents arepresented and described. Anna Tonazzini graduated cum laude in Mathematics from the University of Pisa, Italy, in 1981. In 1984 she joined the Istituto di Scienza e Tecnologie dell'Informazione of the Italian National Research Council (CNR) in Pisa, where she is currently a researcher at the Signals and Images Laboratory. She cooperated in special programs for basic and applied research on image processing and computer vision, and is co-author of over 60 scientific papers. Her present interest is on inverse problems theory, image restoration and reconstruction, document analysis and recognition, independent component analysis, neural networks and learning. Emanuele Salerno graduated in Electronic Engineering from the University of Pisa, Italy, in 1985. In September 1987 he joined the Italian National Research Council (CNR) at the Department of Signal and Image Processing, Information Processing Institute (now Institute of Information Science and Technologies, ISTI, Signals and Images Laboratory), Pisa, Italy, where he has been working in applied inverse problems, image reconstruction and restoration, microwave nondestructive evaluation, and blind signal separation. He has been assuming different responsibilities in research programs in nondesctructive testing, robotics, numerical models for image reconstruction and computer vision, neural networks techniques in astrophysical imagery. At present, he is local scientific responsible in the framework of the European Space Agency's “Planck Surveyor Satellite” mission, and takes part in the European CRAFT project “ISyReADeT”, for document image restoration. Luigi Bedini graduated cum laude in Electronic Engineering from the University of Pisa, Italy, in 1968. Since 1970 he has been a Researcher of the Italian National Research Council, Istituto di Scienza e Tecnologie dell'Informazione, Pisa, Italy. His interests have been in modelling, identification, and parameter estimation of biological systems applied to non-invasive diagnostic techniques. At present, his research interest is in the field of digital signal processing, image reconstruction and neural networks applied to image processing. He is co-author of more than 80 scientific papers. From 1971 to 1989, he was Associate Professor of System Theory at the Computer Science Department, University of Pisa, Italy.     

基于噪声抵消与波束形成的小阵语音增强

为了提高麦克风小阵的语音增强效果,将阵列抗串扰自适应噪声抵消（ACRANC）方法与波束形成（BF）方法相结合,提出了一种效果更好的小阵语音增强方法。首先,通过生成多个ACRANC子系统,获得多路增强语音信号;然后,通过所提的自适应模式控制（AMC）算法和延迟求和（DAS）波束形成方法进一步提高多路增强语音信号的增强效果。对提出的方法进行了计算复杂度估计,验证了所提方法可以通过普通芯片实时实现。实际环境下的实验结果也表明,所提方法的语音增强效果相较ACRANC方法有所提高,具有一定的优越性。     

一种新的变步长比例仿射投影算法研究

研究比例仿射投影算法,针对自适应算法收敛速度和稳态误差之间的矛盾,提出了一种变步长的改进比例仿射投影算法( VSS- IPAPA).利用后验误差去补偿干扰信号对系统稳态性能的影响,得到了算法新的最优步长准则,根据步长准则以及先验误差与后验误差之间的联系,导出了一种适用于比例仿射投影的步长调节方法.综合了稀疏算法、数据重用方法及变步长的优点.最后通过对改进算法进行仿真,结果表明,在增加少量计算量的情况下,系统的收敛速度和稳态性能有明显的改善,证明了比例仿射投影算法的有效性.     

一种低延时双端发音检测方法

回声消除是提高通信中语音信号质量的关键技术。其主要难题是回声路径估计的自适应算法的控制逻辑。为了达到较好的回声消除效果,自适应滤波器需要在双端发音模式下缓慢更新或停止更新,而在其他模式快速学习。现有的双端发音检测算法没有考虑检测延时问题,使得滤波器在停止更新前已经发散,严重影响了回声消除的效果。针对该问题,在滤波器收敛时回声消除至少达到10 dB的假设前提下,对传统的能量比较法进行改进,提出低延时的解决方案。实验结果表明,该方法比相关比较法的检测延时减少了35毫秒以上。     

变步长比例仿射投影算法及在回声消除中的应用

针对稀疏控制算法快速收敛与低稳态失调之间的矛盾,提出了一种变步长的稀疏控制比例仿射投影算法。该算法将干扰信号对系统稳态性能的负面作用考虑进滤波器系数更新过程中,并利用后验误差对其进行补偿,建立了一个新的目标函数,根据该目标函数,导出了一种适用于比例仿射投影算法整体步长的调节方法。理论分析和计算机仿真结果表明,算法在典型的回声信道条件下,均能获得很快的收敛速度和很低的稳态失调。