关于多部图Kn(t)的{K4-e,S3}-强制分解

设n,t为正整数,以K_n(t)表示基于顶点集X=■X_i上的完全n部图。文章证明了(Kn(t),｛K4-e,S3｝)—强制分解存在当且仅当n≥3且(n,t)≠(3,2)。     

预处理迭代的性质及其应用

区域分裂并行计算的效率主要归结为解决并行过程中子区域间的信息传递问题．预处理方法是一种改善信息传递的重要手段．文中讨论了预处理迭代的一些性质，提出构造较优预处理的一类方法．在构造预处理的过程中运用参数来讨论条件数的改善情况，还对参数范围作了讨论。     

Network Decomposition and Maximum Independent Set Part Ⅱ：Application Research

According to the researches on theoretic basis in part I of the paper，the spanning tree algorithms solving the maximum independent set both in even network and in odd network have been developed in this part，part Ⅱ of the paper．The algorithms trans form first the general network into the pair sets network，and then decompose the pair sets network into a series of pair subsets by use of the characteristic of maximum flow passing through the pair sets network．As for the even network，the algorithm requires only one time of trans formation and decomposition，the maximum independent set can be gained without any iteration processes，and the time complexity of the algorithm is within the bound of O(｜V｜^3)．However，as for the odd network，the algorithm consists of two stages．In the first stage，the general odd network is transformed and decomposed into the pseudo-negative envelope graphs and generalized reverse pseudo-negative envelope graphs alternately distributed at first；then the algorithm turns to the second stage，searching for the negative envelope graphs within the pseudo-negative envelope graphs only．Each time as a negative envelope graphhas been found．renew the pair sets network by iteration at once．and then tum back to the first stage．So both stages form a circulation process up to the optimum．Two available methods，the adjusting search and the picking-off search are specially developed to deal with the problems resulted from the odd network．Both of them link up with each other harmoniously and are embedded together in the algorithm．Analysis and study indicate that the time complexity of this algorithm is within the bound of O(｜V｜^5)．     

AN EXPERIMENTAL STUDY ON REMOVAL OF NOx IN FLUE GAS AT THENONEQUILIBRIUM PLASMA

Removal of nitrogen oxides (NOx) in flue gas by means of nonequilibrium plasma technology is a very prospect and attractive method. As the nonequilibrium plasma micro discharges can generate a powerful energy flux, imparted to the flue gas, the molecules and atoms of pollutants are motivated and decomposed, and then NOx in the flue gas are decomposed and conversed in the particular conditions. Based on nonequilibrium plasma in combination with catalytic principle, an experimental investigation on NOx decomposition and conversion with AI2 03 catalysts was carriedout and the NOx removal rate up to 95% was obtained. The NOx decomposition and conversion principle with AI2O3 catalysts was also discussed.     

运行模态分析技术在桥梁状态评估中的应用

在输出功率谱的基础上建立了桥梁运行模态分析方法——频域分解法。该方法利用来往车辆激励的响应测量数据,进行无偏功率谱分析,然后对响应谱矩阵进行奇异值分解来识别桥梁的模态参数。该方法保留了传统频域法快速简便的特点,还可以解决传统频域法不能识别近频和重频模态的问题。通过实桥测试,证明该方法可用于桥梁承载力和使用状况评估。     

噪声背景下提取调制信息的改进奇异值分解技术

在介绍现有奇异值分离技术基本原理及其在故障诊断中的应用的基础上，研究了利用信号时间序列重构的吸引子轨迹矩阵奇异值分布特征与信号特征的关系，引入自相关函数定量计算重构矩阵的延时步长，改进了现有算法，使得吸引子轨迹矩阵的重构更加合理。研究表明该方法能在强噪声背景下提取出所需的调制信号，并成功用于齿轮箱调制故障信号的提取。     

基于小波变换的图像融合算法研究

提出了一种新的基于小波多尺度分解的分层图像融合方法；总结出基于小波分解子图像面积比和低频系数均方根误差2个标准，来确定最佳小波分解层数的方法。通过仿真实验，对分解层数、区域大小对该融合方法的性能影响进行了比较分析，并得出融合结果，将其与金字塔算法融合结果进行了比较。实验结果表明，该融合方法是十分有效的。     

人脸非线性视角流形建模方法

针对线性子空间不足以描述头部视角空间非线性变化等因素影响人脸视角流形的精确建模问题,提出一种新的视角流形建模方法,并从理论上将该方法与经典的流形学习建模方法及概念驱动的视角流形建模方法进行比较,通过基于非线性张量分解的人脸及视角识别实验比较视角流形对识别结果的影响,从而给出视角流形的有效性比较.实验结果表明,本文提出的视角流形建模方法比概念驱动的视角流形和TensorFace中的线性视角系数均有更好的识别效果.     

斜风作用下风-车-桥非线性分析系统建立

为了从风作用方向的三维模拟和系统非线性2个角度实现风-车-桥系统的全三维高真实度模拟,首先建立斜风荷载处理方法,采用平均风分解理论对桥梁斜风进行分解,形成桥梁斜风荷载,把桥梁风作用方向模拟域由垂直于桥梁纵轴线的二维平面扩展到三维空间;采用矢量合成法则和线性插值方法,依据车辆位置函数确定桥上车辆任意位置和时刻的合成风速,并基于风洞试验获取车辆气动力系数,形成车辆斜风荷载。然后基于已建立的非线性分析系统,融合斜风荷载处理方法,构建斜风作用下的风-车-桥全三维非线性分析系统,并实现动态可视化。最后采用建立的分析系统,对系列风偏角工况下的桥梁空间动力响应和车辆安全进行分析和评价。结果表明：斜风作用下,桥上车辆事故指标值及桥梁位移响应随着风偏角增大总体上均呈现先减小后增大趋势,且极值均出现在非90°的锐角区;基于风向垂直于桥跨方向的假定所进行的桥梁设计和车辆安全性评价结果偏于不安全。     

基于滤波器分解的图像插值算法

本文研究了一种空域中的图像分解技术，进而利用改种分解方法，探讨了图像插值算法。本文提出的图像分解方法的主要思想是：利用类型确定的滤波器（如低通）对原始图像滤波，将图像分解为高频和低频两部分，并对分解得到的低频或高频成分进行处理，图像可分解成不同频率分量的图层之和，进而在各个图层一L进行相应的插值处理，最后利用逆变换得到最终的结果。