一种改进的MIMO-OFDM系统频域信道估计和跟踪方案

深入研究了MIMO-OFDM系统中的频域信道估计和跟踪算法．在分析比较了现有频域信道估计算法的基础上,提出了一种有效的改进频域信道估计和跟踪方案．该方案利用基于正交训练符号的算法求得初始信道估计值,利用信道估计和信号检测的联合迭代算法来跟踪随时间变化的信道参数．在典型的室内传输环境下对三种频域信道估计和跟踪方案进行了仿真比较,结果表明,本文所提方案在较低的迭代次数下就可以带来明显的性能改善．     

稀疏信道下OFDM信号的迭代检测方法

提出了一种适用于稀疏信道环境的OFDM信号迭代检测方法。该方法采用导频进行初始化信道估计,使用数学期望最大（EM）算法迭代检测OFDM信号。该方法需要已知信道的路径时延信息、噪声方差和信道冲击响应的协方差矩阵,因此同时给出了这些参数的估计方法。仿真结果证明了这种迭代算法的有效性,而且使用估计的信道参数时的系统性能和理想参数条件下的性能接近。     

MIMO-OFDM系统中一种改进的最大似然信道估计算法*

对MIMO-OFDM系统中的信道估计进行研究,提出了一种对最大似然（ML）算法的改进,该算法首先采用ML算法获得初始估计值,然后联合检测进行迭代信道估计,充分利用上了接收端联合数据检测得到的数据信号信息与信道估计进行信息交互来提高估计性能,仿真结果表明,相对于传统估计方法,这种改进方法能够得到更好的均方误差和误码率性能,尤其是在导频数量较少时,此改进算法的性能提升将更明显。     

MIMO-OFDM系统空间相关性迭代信道估计算法

针对受到噪声干扰及多普勒效应等因素影响的多输入多输出（Multi-Input Multi-Output,MIMO）正交频分复用（Orthogonal Frequency Division Multiplexing,OFDM）无线系统信道估计问题,提出了一种有效的空间相关性迭代信道估计算法（SCICE）。SCICE利用同步符号与协议数据单元中的前置训练序列和中置训练序列,对信道的空间相关性进行估计,数据信息根据该信道相关性信息得到初始的信道估计值,接收端根据信道估计值进行数据符号检测,并将这些信息作为已知信息,以迭代的方式逐渐减小因空间相关性导致的信道估计误差,进而提高信道估计的准确性。与现有迭代信道估计算法的性能比较表明了提出的SCICE算法在瑞利衰落信道以及不同调制方式下具有更好的信道估计均方差与误码率性能。     

频率选择性衰落信道下STBC-SC-FDE系统的信道频率响应估计

本文针对频率选择性衰落信道下2发1收STBC-SC-FDE系统收发两端的信号编码与处理结构,应用系统的频率域输入—输出模型,设计了一种最小二乘信道频率响应（CFR）估计算法。对算法均方误差的分析表明,采用Chu序列作为最优训练序列不仅能够实现CFR估计的最小均方误差,而且能保证系统具有比较低的峰均功率比（PAPR）。该算法相比那些先估计信道时域响应（CIR）再转换为CFR的方法能够节省更多的计算资源。最后,Monte Carlo 仿真验证了该算法的性能。     

一种基于EM-MAP的联合CFO双选信道估计算法

针对在双选信道下OFDM系统需要同时获取精确的载波偏移和信道状态信息, 而采用贝叶斯MAP算法进行联合载波频率偏移和信道状态估计复杂度过高的问题, 提出一种基于EM-MAP的联合CFO双选信道估计算法。首先利用基扩展模型解决信道状态由于快时变带来的可辨识问题, 然后引入期望最大化(EM)算法对系统的载波频偏和信道状态信息进行联合估计, 避免大规模的矩阵求逆, 降低算法复杂度。仿真结果表明, 该方法能获取与MAP算法相当的估计性能, 且大幅度降低了复杂度, 有效地解决了双选信道下进行联合估计复杂度过高的问题, 具有很好的实用性。     

相关分块衰落信道下基于因子图EM算法的解码方法

针对相关分块衰落信道模型,提出一种基于因子图期望最大化(FGEM)算法的联合估计解码方法。在接收机中,采用因子图消息传递方法进行信道估计和迭代解码, 并引入期望最大化(EM)算法来消除因子图模型中存在环路对消息传递的影响,同时解决了消息传递中的混合高斯消息计算的问题。采用卡尔曼前后向算法代替最大化步消息更新过程,简化了消息的迭代计算,降低了联合解码和估计的复杂性。实验结果表明,与只有导频辅助方法和判决方法相比,该算法进一步提高了信道估计的准确度和接收机的解码性能。     

BICM-ID联合迭代载波相位和信道估计算法

针对16APSK信号,提出一种比特交织编码调制迭代译码(BICM-ID)联合迭代载波相位和信道估计算法。该算法基于最大似然估计算法,利用BICM-ID译码产生的硬判决信息,通过迭代的方式在相位估计、信道估计和译码之间交换信息,从而实现相位估计、信道估计和译码的联合处理。在误码率为10-4时,该算法与理想性能曲线仅相差0.5dB左右;算法能够估计的相差范围为[-20°,20°]。     

基于梯度追踪的MIMO-OFDM稀疏信道估计算法

现有的压缩感知MIMO-OFDM信道估计方法多采用正交匹配追踪算法及其改进的算法。针对该类算法重构大规模的数据存在计算复杂度高、存储量大等问题,提出了基于梯度追踪算法的MIMO-OFDM 稀疏信道估计方法。梯度追踪算法采用最速下降法对目标函数解最优解,即每步迭代时计算目标函数的搜索方向和搜索步长,并以此选择原子得到每次迭代重构值的最优解。本文使用梯度追踪算法对信道进行估计,并与传统的最小二乘估计算法、正交匹配追踪算法的性能和计算复杂度进行比较。仿真结果表明,梯度追踪算法能够保证较好的估计效果,减少了导频开销,降低了运算复杂度,提高了重构效率。     

一种基于子空间的MIMO-OFDM信道盲估计算法

论文主要讨论利用子空间算法对MIMO-OFDM信道进行盲估计.子空间算法是一种非常重要的信道估计算法,但该算法最大的缺点是要求精确估计信道阶数,对信道阶数欠估计或过估计非常敏感.针对这一点论文提出了一种联合子空间算法,该算法能够同时完成信道阶数估计和信道估计.仿真实验表明在低信噪比、观测数据较短和信道具有较小的初始和结尾系数等条件下时,该算法的信道阶数估计能力优于以前的算法,同时信道估计性能也得到较大的提高.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.     

Editorial: Special issue on recent advances in hybrid control theory and applications

正The demands of a rapidly advancing technology for faster and more accurate controllers have always had a strong influence on the progress of automatic control theory.In recent years control problems have been arising with increasing frequency in widely different areas,which cannot be addressed using conventional control techniques.The principal reason for this is the fact that a highly competitive economy is forcing systems to operate in regimes where     

Information for Authors

正Aim The Journals of Zhejiang University-SCIENCE(A/B/C)areedited by the international board of distinguished Chinese andforeign scientists,and are aimed to present the latest devel-opments and achievements in scientific research in China andoverseas to the world’s scientific circles,especially to stimulateand promote academic exchange between Chinese and for-eign scientists everywhere.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.