一种改进的基于秩检测的信道有效阶数估计算法

信道阶数估计是SOS类盲辨识算法的前端步骤。针对Liavas阶数估计算法对信噪比要求高的问题,通过对接收序列自相关矩阵进行"降噪"处理和改进秩检测目标函数,提出一种改进算法,有效降低了对信噪比的要求。分析了在不同信道条件下,各种阶数估计算法的性能,阐明随着信噪比降低,阶数估计误差不可避免,该结论是进一步研究对阶数估计误差鲁棒的盲辨识算法的重要依据。     

飞机载荷谱实测数据并行统计处理算法

针对飞机载荷谱数以万亿计的实测数据,为了提高统计处理运行效率,提出了飞机载荷谱实测数据处理的并行算法。本文对载荷谱实测数据处理模型进行了多级并行化分析,在此基础上论述了粗粒度、中粒度、细粒度级并行处理方式,建立了两种并行处理算法——基于机型数据流的粗粒度与中粒度并行数据处理算法和基于某起落数据流的中粒度与细粒度并行数据处理算法。在小规模对称多处理器(Symmetrical multi-processors,SMP)集群运算平台下进行比较测试表明,可大幅地提高载荷谱数据处理运行效率,在8核运算环境下,最高能获得5.82的加速比,为飞机载荷谱实测数据处理研究领域进行大规模科学计算和提高数据处理效率提供了新的技术途径。     

基于地质统计学的多源遥感信息融合研究

在地质统计学的概念及相关理论的基础上,分析了多源遥感信息的特点及分类。将地质统计学引入遥感信息融合中,按时序获取不同传感器的观测信息并依据相关准则进行自动分析,完成了多传感器的状态估计和决策的信息处理过程。利用地质统计学的变差函数和克里金法对多源遥感信息进行空间特征的融合,提高了遥感信息的使用率,达到了准确预测和估计地质状态的目的。     

基于边缘分析和颜色统计的车牌精确定位新方法*

针对车牌的边界定位不准确和伪车牌较多的问题,提出了一种边缘分析和颜色统计相结合的车牌精确定位的新框架。该框架主要分为预处理、粗定位、精确定位和伪车牌排除四个模块。对图像作边缘检测和二值化等预处理,用投影法粗定位出候选区域,利用候选区域及其周围的边缘和颜色的信息实现车牌的精确定位。对于定位结果有多个候选区域的情况,对候选区域进行排序,再将排序结果按顺序传入字符分割模块,从而有效排除非车牌区域的影响。实验结果表明,该方法精确度和准确率高、实时性强,适用于不同的应用场合。     

科技档案管理系统的研究与实现

通过对科技档案管理的现状与特点的分析,介绍了开发科技档案管理系统,即根据当前办公自动化的发展,结合科技档案管理的特点进行了系统结构设计。并对其各部分功能和使用进行了详细地阐述。     

Development of the Local Approach to Fracture over the Past 25 years: Theory and Applications

This review paper is devoted to the local approach to fracture (LAF) for the prediction of the fracture toughness of structural steels. The LAF has been considerably developed over the past two decades, not only to provide a better understanding of the fracture behaviour of materials, in particular the failure micromechanisms, but also to deal with loading conditions which cannot easily be handled with the conventional linear elastic fracture mechanics and elastic–plastic fracture mechanics global approaches. The bases of this relatively newly developed methodology are first presented. Both ductile rupture and brittle cleavage fracture micromechanisms are considered. The ductile-to-brittle transition observed in ferritic steels is also briefly reviewed. Two types of LAF methods are presented: (i) those assuming that the material behaviour is not affected by damage (e.g. cleavage fracture), (ii) those using a coupling effect between damage and constitutive equations (e.g. ductile fracture). The micromechanisms of brittle and ductile fracture investigated in elementary volume elements are briefly presented. The emphasis is laid on cleavage fracture in ferritic steels. The role of second phase particles (carbides or inclusions) and grain boundaries is more thoroughly discussed. The distinction between nucleation and growth controlled fracture is made. Recent developments in the theory of cleavage fracture incorporating both the effect of stress state and that of plastic strain are presented. These theoretical results are applied to the crack tip situation to predict the fracture toughness. It is shown that the ductile-to-brittle transition curve can reasonably be well predicted using the LAF approach. Additional applications of the LAF approach methods are also shown, including: (i) the effect of loading rate and prestressing; (ii) the influence of residual stresses in welds; (iii) the mismatch effects in welds; (iv) the warm-prestressing effect. An attempt is also made to delineate research areas where large improvements should be made for a better understanding of the failure behaviour of structural materials.     

Structural optimization of non-linear systems under stochastic excitation

This work concentrates on the structural optimization of a class of non-linear systems with deterministic structural parameters subject to stochastic excitation. The optimization problem is formulated as the minimization of an objective function subject to constraints on the response level. The stochastic response is characterized by its first two statistical moments, which are computed by a statistical equivalent linearization technique. The implicit structural optimization problem is replaced by a sequence of explicit sub-optimization problems. The sub-problems are constructed by using a conservative first-order approximation of the objective and constraint functions. The applicability of the proposed design process is demonstrated in three numerical examples where the methodology is applied to systems with nonlinearity of hardening and hysteretic type. The effects of the nonlinearity on the general performance of the final designs are discussed. At the same time, some engineering implications of the results obtained in this work are addressed.     

Validation of models with multivariate output

This paper develops metrics for validating computational models with experimental data, considering uncertainties in both. A computational model may generate multiple response quantities and the validation experiment might yield corresponding measured values. Alternatively, a single response quantity may be predicted and observed at different spatial and temporal points. Model validation in such cases involves comparison of multiple correlated quantities. Multiple univariate comparisons may give conflicting inferences. Therefore, aggregate validation metrics are developed in this paper. Both classical and Bayesian hypothesis testing are investigated for this purpose, using multivariate analysis. Since, commonly used statistical significance tests are based on normality assumptions, appropriate transformations are investigated in the case of non-normal data. The methodology is implemented to validate an empirical model for energy dissipation in lap joints under dynamic loading.     

国民最终消费的非参数预测模型

传统的线性回归模型不能理想地捕获我国国民收入与最终消费之间的动态关系,本文基于局部线性非参数估计理论,对我国改革开放以来的年国民最终消费建立了非参数回归预测模型,并对我国2000~2004年的国民最终消费进行了预测。结果表明,相对于线性回归模型而言,非参数回归模型能够很好地解决我国国民最终消费问题,预测精度较高。     

统计过程控制在软件工程中的应用

统计过程控制已经在制造业取得了成功的应用，近年在软件工程方面的应用也不断上升。本文通过分析这些指标数据，找出软件过程中各个阶段的不确定因素，并采取适当措施来保证软件过程处于统计意义下的受控状态，从而达到保证软件质量、提高软件生产效率的目的。