轻量级内存数据库的研究

内存数据库指的是基于内存的数据库,其主拷贝或"工作版本"常驻于内存中,并将数据库保存在内存中,避免了缓冲区管理器对数据的间接访问,使虚拟内存数据库比传统的磁盘数据库系统拥有更快的响应时间和更大的吞吐量.     

头驱动句法分析中的直接插值平滑算法

在头驱动句法分析模型下,基于经典插值平滑算法,提出了以统计空间中平均事件数为基础的直接插值平滑建模原则,并应用经典的误差理论分析了该原则的合理性.基于该原则并借鉴语言模型中其他插值平滑算法对模型的零点进行假设的方法,在头驱动句法分析模型下,重新构造了4种平滑算法.实验数据显示,新平滑算法在高于经典平滑算法性能的同时,显著降低了自由参数的扰动程度,从实验的角度证明了该平滑建模原则的有效性.     

基于模糊定性趋势分析的故障诊断方法研究

趋势能够反映过程重要参数的运行状态和发展趋向;利用定性趋势分析进行故障诊断时,趋势固有的定性特性使得趋势分类的界限变得模糊,带来诊断的模糊性和规则知识库的组合爆炸等一系列问题;将模糊理论与定性趋势分析相结合,给出了趋势提取及基于模糊逻辑的趋势匹配算法,研究了一种基于模糊定性趋势分析的故障诊断方法来有效地解决这些问题;实例分析表明,基于模糊定性趋势分析的故障诊断方法能大大缩小规则知识库的规模,提高定性趋势分析故障诊断的准确性和实时性,及时发现和预测控制过程的早期故障。     

Exponential stability and exponential stabilization of singularly perturbed stochastic systems with time‐varying delay

In this paper, the problems of exponential stability and exponential stabilization for linear singularly perturbed stochastic systems with time‐varying delay are investigated. First, an appropriate Lyapunov functional is introduced to establish an improved delay‐dependent stability criterion. By applying free‐weighting matrix technique and by equivalently eliminating time‐varying delay through the idea of convex combination, a less conservative sufficient condition for exponential stability in mean square is obtained in terms of ε‐dependent linear matrix inequalities (LMIs). It is shown that if this set of LMIs for ε=0 are feasible then the system is exponentially stable in mean square for sufficiently small ε?0. Furthermore, it is shown that if a certain matrix variable in this set of LMIs is chosen to be a special form and the resulting LMIs are feasible for ε=0, then the system is ε‐uniformly exponentially stable for all sufficiently small ε?0. Based on the stability criteria, an ε‐independent state‐feedback controller that stabilizes the system for sufficiently small ε?0 is derived. Finally, numerical examples are presented, which show our results are effective and useful. Copyright © 2010 John Wiley & Sons, Ltd.     

Comparison of forecasting methods with an application to predicting excess equity premium

This paper reviews various forecast methods including combination using theoretically optimal weights and those under model selection approaches. In addition, we suggest two modified simple averaging forecast combination methods—a mean corrected and a mean and scale corrected method. We conclude that due to the fact that real data is usually subject to structural breaks, rolling forecasting scheme has a better performance than fixed window and continuously updating scheme. In addition, methods that use less information appear to perform better than methods using all the sample information about the covariance structure of the available forecasts. The mean and scale corrected simple average approach yield smaller mean squared forecast error than the three widely used regression approaches suggested by Granger and Ramanathan [11].     

基于特征组合的中文语义角色标注

提出一种基于特征组合和支持向量机(support vector machine,简称SVM)的语义角色标注(semantic role labeling,简称SRL)方法.该方法以句法成分作为基本标注单元,首先从当前基于句法分析的语义角色标注系统中选出高效特征,构成基本特征集合.然后提出一种基于统计的特征组合方法.该方法能够根据正反例中组合特征的分布状况,以类间距离和类内距离之比作为统计量来衡量组合特征对分类所产生的效果,保留分类效果较好的组合特征.最后,在Chinese PropBank(CPB)语料上利用支持向量机进行分类实验,结果表明,引入该特征组合方法后,语义角色标注整体F值达91.81%,提高了近2%.     

多用户PHPWEB空间的安全策略

本文就多用户用的PHPWEB空间的安全问题作了全面的分析,并就操作系统和PHP环境及漏洞修补等方面给出了综合解决的完整方案。     

超混沌系统自周期轨道链接式控制

基于混沌同步和周期轨道理论提出一种超混沌系统自周期轨道链接式控制法。从超混沌系统状态变量的时间序列中提取周期轨道并用于对系统的实时控制,可使混沌系统稳定运行于某一周期轨道。将提周期轨道经链接组合后用于系统控制,可得到大量的大周期轨道。对4阶蔡氏电路进行数字仿真实验,获得了满意的结果。     

Noise-robust edge detector combining isotropic and anisotropic Gaussian kernels

A new noise-robust edge detector is proposed, which combines a small-scaled isotropic Gaussian kernel and large-scaled anisotropic Gaussian kernels (ANGKs) to obtain edge maps of images. Its main advantage is that noise reduction is attained while maintaining high edge resolution. From the ANGKs, anisotropic directional derivatives (ANDDs) are derived to capture the locally directional variation of an image. The ANDD-based edge strength map (ESM) is constructed. Its noise-robustness is determined by the scale alone and its edge resolution by the ratio of the scale to the anisotropic factor. Moreover, the edge stretch effect in anisotropic smoothing is revealed. The ANDD-based ESM and the gradient-based ESM with a small-scaled isotropic Gaussian kernel are fused into a noise-robust ESM with high edge resolution and little edge stretch. Embedding the fused ESM into the routine of Canny detector, a noise-robust edge detector is developed, which includes two additional modifications: contrast equalization and noise-dependent lower threshold. The aggregate test receiver-operating-characteristic (ROC) curves and the Pratt's Figure of Merit (FOM) are used to evaluate the proposed detector by abundant experiments. The experimental results show that the proposed detector can obtain high-quality edge maps for noise-free and noisy images.