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。     

工矿企业能量平衡通用模式的研究

提出了适用于工矿企业能量平衡的一种通用模式，将与ＧＢ３４８４－８３《企业能量平衡通则》再增加“一表两图”──“企业能量平衡表”、“企业能源网络图”和“企业能流图”的效果相一致，能更加科学、合理地反映企业能量平衡的结果。     

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-     

镁改型蛭石对铵离子的交换性能

对经人工改型所得的镁型蛭石进行了铵离子交换性能的研究．在不同pH值下测定了镁型蛭石对NHr的全交换容量，在不同温度下测定了样品的平衡等温线．结果表明，镁型蛭石对NH4^ 的交换总量随pH值的变化而波动，在pH值为7时其交换总量为59．32mmol／100g，其选择性随温度的降低而升高，这为蛭石作为一种新型填料提供了一定的理论依据。     

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.     

用于图像目标识别的神经网络方法

本文提出了一种全局最优的神经网络（ＦｕｌｌＤｏｍａｉｎＯｐｔｉｍｕｍＮｅｕｒａｌＮｅｔｗｏｒｋ）模型用于目标识别。通常所设计的神经网络不能保证全局最优，使得网络不一定收敛到期望样本点上。本文的模型采用了先设计稳定点、再构造吸引域的方法，提高了网络的识别正确率及速度。针对图像识别中矢量维数大的实际，提出了一种不变性方法，使得样本维数下降而分类距离保持不变。同时又证明了网络的收敛性、收敛速度及映射保距等。计算机模拟结果表明，网络对噪声或缺损图均能正确识别。     

格序半群同余格LC（S）的完全分配性

本文首先引入值和正则Ｌ－同余的概念并讨论了正则Ｌ－同余的基本性质，在此基础上，给出了格ＬＣ（Ｓ）是完全分配格的几个等价刻化。