LSA和MD5算法在垃圾邮件过滤系统的应用研究

随着对垃圾邮件问题的普遍关注,针对目前邮件过滤方法中存在着的语义缺失现象和处理群发型垃圾邮件低效问题,提出一种基于潜在语义分析(LSA)和信息-摘要算法5(MD5)的垃圾邮件过滤模型。利用潜在语义分析标注垃圾邮件中潜在特征词,从而在过滤技术中引入语义分析;利用MD5在LSA分析基础上,对群发型垃圾邮件生成"邮件指纹",解决过滤技术在处理群发型垃圾邮件中低效的问题。结合该模型设计了一个垃圾邮件过滤系统。采用自选数据集对文中设计的系统进行测试评估,经与Nave Bayes算法过滤器进行比较,证明该方法在垃圾邮件过滤上优于Nave Bayes方法,实验结果达到了预期的效果,验证了该方法的可行性、优越性。     

Small domain estimation by empirical bayes and kalman filtering procedures - a case study

An application of empirical Bayes and Kalman filtering tecniques is reported, using live data from Indian Statistical Institute (ISI), Calcutta . to illustrate how initial small domain estimators may be vastly improved upon. A stratified two stage sampling procedure is adopted, allowing selection of first stage units with unequal probabilities but of second stage units with equal probabilities. Standard design-based estimators for domain totals are initialized based on domain specific survey data alone. Strength is then borrowed across domains and from past surveys. The resulting gains in efficacy are numlerically demonstrated, through replicated sampling from official records.     

Identification,Estimation, and Control of Uncertain Dynamic Systems: A Nonparametric Approach

This article is devoted to a presentation of the author' practice of the non-parametric estimation theory for the estimation, filtering, and control of uncertain dynamic systems. The fundamental advantage of this approach is a weak dependency on prior modeling assumptions about uncertain dynamic components. This approach appears to be of great interest for the control of general discrete-time processes, and in particular, biotechnological processes, which are emblematic of nonlinear uncertain and partially observed systems.     

基于状态空间模型的宏观经济因素对股市流动性的建模分析

证券市场的流动性是评估一国证券市场是否健康运转的重要指标。关于流动性的各种学术研究也是金融市场微观结构理论中的热点问题。本文主要考察宏观经济因素对时变的股市流动性的影响，选取度量股票流动性的指标以及宏观经济变量，针对行业分类的面板数据提出三个动态因子模型，并引入跨行业的能够捕捉风险聚集现象的潜在因子进行建模，利用状态空间模型与Kalman滤波进行分析和样本外流动性风险预测。我们提出的新颖的带回归效应的高斯面板数据时间序列模型，结合了用主成分的方法从大量宏观经济协变量中提取出来的因子，用来分析和预测股市的流动性风险，具有较强的信息挖掘作用。在对上证A 股的实证研究中，我们发现动态的潜在因子的引入对于防止流动性估计的偏差是需要的。     

Estimating the Population Survival Function Using Additional Information Recorded Over Time: a Filter Based Approach

Survival studies often collect information about covariates. If these covariates are believed to contain information about the life-times, they may be considered when estimating the underlying life-time distribution. We propose a non-parametric estimator which uses the recorded information about the covariates. Various forms of incomplete data, e.g. right-censored data, are allowed. The estimator is the conditional mean of the true empirical survival function given the observed history, and it is derived using a general filtering formula. Feng & Kurtz (1994) showed that the estimator is the Kaplan–Meier estimator in the case of right-censoring when using the observed life-times and censoring-times as the observed history. We take the same approach as Feng & Kurtz (1994) but in addition we incorporate the recorded information about the covariates in the observed history. Two models are considered and in both cases the Kaplan–Meier estimator is a special case of the estimator. In a simulation study the estimator is compared with the Kaplan–Meier estimator in small samples.     

全息图的数字化频域滤波及数值再现研究

采用计算机对普通离轴计算全息图及博奇型修正离轴参考光计算全息图进行数字化滤波操作,可在频域将零级及孪生像消除,从而得到单一的清晰实像或虚像。利用快速傅里叶变换算法计算菲涅耳衍射积分,实现了计算全息图的设计制作、频域滤波、再现过程的全数字化,计算机数值模拟结果表明该方法具有再现图像信噪比高、操作过程简便、计算速度快、灵活性强等特点。     

Statistical Issues in Weather Forecasting*

Research and operational applications in weather forecasting are reviewed, with emphasis on statistical issues. It is argued that the deterministic approach has dominated in weather forecasting, although weather forecasting is a probabilistic problem by nature. The reason has been the successful application of numerical weather prediction techniques over the 50 years since the introduction of computers. A gradual change towards utilization of more probabilistic methods has occurred over the last decade; in particular meteorological data assimilation, ensemble forecasting and post‐processing of model output have been influenced by ideas from statistics and control theory.     

一种基于最小二乘准则的自适应滤波算法

基于最注二乘准则Ｊ（ｎ）＝　　　　　,利用最徒梯度下降法,得到一种新的梯度型自适应滤波算法．该算法避免了递推最小二乘ＲＬＳ（Ｒｅｃｕｒｓｉｖｅ　Ｌｅａｓｔ　Ｓｑｕａｒｅｓ）算法需递推估计更新自相关矩阵Ｒｘｘ（ｎ）的逆的不足,计算机模拟仿真结果表明该算法有良好的收敛性能,收敛速度快于ＬＭＳ（Ｌｅａｓｔ Ｍｅａｎ　Ｓｑｕａｒｅｓ）算法、ＮＬＭＳ（ＮｏｒｍａｌｉｚｅｄＬｅａｓｔ　Ｓｑｕａｒｅｓ）算法和ＲＬＳ算法．     

网络信息采集技术探析

利用先进的网络信息采集技术,提高网络信息采集的效率,是当前网络信息采集的一个研究热点。该文简要介绍了网络信息采集的原理、方法及技术等问题,论述了网络信息挖掘、信息抽取、信息过滤及信息推送这四种主要的网络信息采集技术,展望了网络信息采集技术的发展前景。     

自适应多波束形成的算法

论述了一种窄带和宽带多波束形成的算法,这种算法所依据的准则是在波束满足指向和振幅要求的约束条件下使阵列输出功率最小。对于 N 元阵列,可同时形成 N-1个独立波束。根据对约束条件的不同控制,利用这种算法可实现波束扫描,形成宽波束、实现干扰对消或旁瓣对消等。同时还给出了所述算法的计算机模拟结果,结果表明所述算法是很有效的。