基于截断正态概率模型的改进目标跟踪算法

在应用NIFPAT算法对机动目标跟踪时存在计算量大和要求网络训练两个弱点。分析了截断正态概率模型和NIFPAT算法后 ,把截断正态概率模型与NIFPAT算法思想相结合 ,提出了基于截断正态概率模型的改进目标跟踪算法。该算法根据目标机动情况自动调整系统方差 ,在附加较小计算量的情况下 ,能取得较好的跟踪效果。仿真实验表明 ,该算法能有效地提高对机动目标的跟踪精度。     

矿物质粉体对砂浆及混凝土Cl-渗透性的影响

研究了不同水胶比、不同矿物质粉体掺量的砂浆和混凝土，经标准养护至56天、90天时的导电量。在相同水胶比和相同矿物质粉体掺量下，混凝土的导电量远低于砂浆的导电量。含矿物质粉体的砂浆及混凝土的导电量均低于基准砂浆及混凝土的导电量。导电量随水胶比的降低而降低，也随龄期的增长而降低。     

对农户生产职能与经营职能分工的超边际分析——对农业产业化的新兴古典范式分析

以报酬递增为前提，刻画农户生产职能与经营职能专业化的分工经济，运用超边际分析方法求解农户职能分工的一般均衡结构，认为农户职能专业化产生的分工经济是农业产业化发展的基本动力，降低交易费用是农业产业化兴起的基本经济条件。     

一类特殊的奇异级数

讨论了华林问题中一类特殊的奇异级数，在分析的范围内用代数数论的方法对它的下界作出一个估计，从而改进了Vaughan的结果。     

Radar Imaging Based on Iterative Algorithms

It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.     

反应条件及添加惰性物质对三聚甲醛合成反应的影响

研究了三聚甲醛合成过程进料浓度、催化剂用量等对副产物（特别是甲酸）生成行为的影响。结果表明，该体系副产物的生成强烈地依赖于反应时间和催化剂硫酸的用量，而与原料浓度的波动无关。在反应－精馏过程的反应器中添加惰性高沸有机物，可有效地缩短反应物的停留时间，提高三聚甲酸的选择性，大大降低快速反应－精馏过程对反应器的设计要求。     

大型喷浆机器人的灵巧度分析

灵巧度是衡量机器人运动失真程度的重要参数。对机器人灵巧度评价指标进行了对比研究 ,结合大型喷浆机器人自由度较多的特点 ,用雅可比矩阵的条件数对喷浆机器人的灵巧度进行了分析。结果表明 ,大型喷浆机器人在不同形位下的条件数都很小 ,具有较好的运动灵巧度。     

Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-     

Evolutionary Computation and its Application

On Mar.23,2006,a project in the Major Program of NSFC-"Evolutionary computation and its application",managed by Prof.Licheng Jiao,Prof.Lishan Kang,Prof.Zhenya He,and Prof.Tao Xie,passed its Final Qualification Process and was evaluated as Excellent.