基于最大熵谱估计的机载雷达杂波抑制技术

在讨论机载雷达地面杂波的基础上，利用最大熵估计法对机载雷达杂波进行抑制，并引入了ｃｈｏｌｃｓｋｙ分解快速算法求解最大熵谱的ＡＲ模型参数。计算机模拟表明，基于最大熵谱估计的机载雷达杂波抑制技术有很高的谱分辨率，不仅能跟踪主杂波的频率位置而且能跟踪其谱宽度，因而具有较为满意的杂波对消化与改善因子。     

SHOULD WE ESTIMATE THE PROBABILITY OF CORRECT SELECTION?

Various authors, given k location parameters, have considered lower confidence bounds on (standardized) dserences between the largest and each of the other k - 1 parameters. They have then used these bounds to put lower confidence bounds on the probability of correct selection (PCS) in the same experiment (as was used for finding the lower bounds on differences). It is pointed out that this is an inappropriate inference procedure. Moreover, if the PCS refers to some later experiment it is shown that if a non-trivial confidence bound is possible then it is already possible to conclude, with greater confidence, that correct selection has occurred in the first experiment. The short answer to the question in the title is therefore ‘No’, but this should be qualified in the case of a Bayesian analysis.     

项目管理:基于生命周期和基于职能活动的管理

对应着项目的"一次性"和"多项活动复合性"的本质特征,项目管理有两种基本模式,即基于生命周期的项目管理和基于职能活动的项目管理,二者的内容体系不同,各有优劣,模式的选用要综合考虑项目的具体性质和企业的发展现状.     

海峡两岸司法协助模式新探

区际司法协助,是中国恢复对香港和澳门行使主权后最迫切需要解决的问题之一。现今在我国区际司法协助实践中已经出现了"安排模式",这种模式初步解决了我国的区际司法协助问题,但还不能说是我国开展区际司法协助的唯一模式。而海峡两岸区际冲突法的独特性和复杂性,使示范立法模式有其运用的空间。     

人才生态环境建构研究

人才成长、培养和使用的环境是否和谐,是否有利于人才的发展和转化,直接决定人才成长的速度、人才培养的质量和人才使用的价值。人才生态环境系统是一个可持续发展的能量交换体,人才在其中能够与人才群体、人才组织、人才社会各生态要素相互联系、相互影响和相互作用,以至形成综合的具有核心竞争能力的生态系统,最终促使人才自我价值的实现,从而有效提升人才的使用价值和社会价值。     

Bayesian validation assessment of multivariate computational models

Multivariate model validation is a complex decision-making problem involving comparison of multiple correlated quantities, based upon the available information and prior knowledge. This paper presents a Bayesian risk-based decision method for validation assessment of multivariate predictive models under uncertainty. A generalized likelihood ratio is derived as a quantitative validation metric based on Bayes’ theorem and Gaussian distribution assumption of errors between validation data and model prediction. The multivariate model is then assessed based on the comparison of the likelihood ratio with a Bayesian decision threshold, a function of the decision costs and prior of each hypothesis. The probability density function of the likelihood ratio is constructed using the statistics of multiple response quantities and Monte Carlo simulation. The proposed methodology is implemented in the validation of a transient heat conduction model, using a multivariate data set from experiments. The Bayesian methodology provides a quantitative approach to facilitate rational decisions in multivariate model assessment under uncertainty.     

基于视觉模型的双正交小波图像水印算法

提出了一种基于人类视觉系统模型的双正交小波多分辨图像水印算法,该算法充分利用小波多分辨的优点及人眼视觉系统的特性,保证了水印的不可见性及鲁棒性,同时在检测水印时也不需要原始图像,仅需涉及到相关的几个细节子图。实验表明该水印算法对于中值滤波、叠加加性噪声、JPEG有损压缩三种图像处理都是鲁棒的。检测算法还有计算量小,检测速度快的特点。     

Optimal sampling for repeated binary measurements

The authors consider the optimal design of sampling schedules for binary sequence data. They propose an approach which allows a variety of goals to be reflected in the utility function by including deterministic sampling cost, a term related to prediction, and if relevant, a term related to learning about a treatment effect To this end, they use a nonparametric probability model relying on a minimal number of assumptions. They show how their assumption of partial exchangeability for the binary sequence of data allows the sampling distribution to be written as a mixture of homogeneous Markov chains of order k. The implementation follows the approach of Quintana & Müller (2004), which uses a Dirichlet process prior for the mixture.     

经济法教学实践性模式探讨

现行高校经济法教学模式一般只注重向学生传授基本的经济法学原理和相关法律知识,却忽视对学生实践能力、操作能力和思考能力的培养,造成教学和现实的脱节,同时也面临着学科自身发展瓶颈与学生就业前景暗淡的尴尬.针对经济法课程新、专、广的特点,本着培养学生经济法法律意识和法律实践能力的目的,从教学环节入手,以实践性理念为指导来设定教学目标、安排教学内容、运用多样化的教学方法和手段,构建经济法教学的实践性模式,不失为一条出路.     

ELICITING A DIRECTED ACYCLIC GRAPH FOR A MULTIVARIATE TIME SERIES OF VEHICLE COUNTS IN A TRAFFIC NETWORK

The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynamic linear models. The conditional independence and causal structure in the time series can be represented by a directed acyclic graph (DAG). The DAG not only gives a useful pictorial representation of the multivariate structure, but it is also used to build the LMDM. Therefore, eliciting a DAG which gives a realistic representation of the series is a crucial part of the modelling process. A DAG is elicited for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a DAG for the time series suitable for use with an LMDM.