The First Intramolecular Charge Transfer Transition Based on 2-Ureido-4[1H]-pyrimidinone Binding Module

The first intramolecular charge transfer transition based on 2-ureido-4[1H]-pyrimidinone binding module was reported.     

The Isoelectric Point and the Points of Zero Charge of Fe-Al-Mg Hydrotalcite-like Compounds

The relation of the isoelectric point (IEP) and the point of zero net charge (PZNC) of the hydrotalcite-like compounds was discussed. It was found that the IEP does not equal to the PZNC and the IEP is higher than the PZNC. The structural positive charges existing in the HTlc,which cause the difference between the IEP and the PZNC. The effects of the structural positive charges of the HTlc on its IEP and PZNC are the same as the specific adsorption of metal cations.     

美式期权定价中非局部问题的有限元方法

在本文中 ,我们关心的是美式期权的有限元方法 .首先 ,根据 [4 ]我们对所讨论的问题引进一个新奇的实用的方法 ,它涉及到对原问题重新形成准确的数学公式 ,使得数值解的计算可以在非常小的区域上进行 ,从而该算法计算速度快精度高 .进而 ,我们利用超逼近分析技术得到了有限元解关于 L2 -模的最优估计 .     

全景图像几何畸变校正的算法研究及其软件实现

对于360°视场的全景图像,本文提出了分别对其进行切向和径向畸变校正的处理算法,并用插值处理提高处理精度。达到了将全景图像恢复为常规视场平面像的目的。它是进一步图像分析的前期工作。     

技术进步中性假定的一般性

本在分析经济增长的技术进步因素的希克期中性假定的基础上，利用势分析方法提出了中性假定的一般性，并计算了我国改革开放以来技术进步对经济增长贡献率。     

单调全局最优化问题的凸化外逼近算法

单调优化是指目标函数与约束函数均为单调函数的全局优化问题．本文提出一种新的凸化变换方法把单调函数化为凸函数，进而把单调优化问题化为等价的凸极大或凹极小问题，然后采用Hoffman的外逼近方法来求得问题的全局最优解．我们把这种凸化方法同Tuy的Polyblock外逼近方法作了比较，通过数值比较可以看出本文提出的凸化的方法在收敛速度上明显优于Polyblock方法．     

非线性陀螺系统的稳定准则

本文根据Ляпунов的稳定性理论,研究了陀螺系统在非线性耗散力与非线性保守力作用下的稳定性问题,得到了非线性陀螺系统的稳定准则.结果表明:线性系统的稳定准则也同样适用于非线性系统,从而推广了KTC定理的应用范围.     

非负矩阵与有向图的谱半径

本文给出非负矩阵的谱半径的上界、下界,由此给出有向图的谱半径的界.     

Local Prediction of Chaotic Time Series Based on Support Vector Machine

Based on phase space delay-coordinate reconstruction of a chaotic dynamics system, we propose a local prediction of chaotic time series using a support vector machine （SVM） to overcome the shortcomings of traditional local prediction methods. The simulation results show that the performance of this proposed predictor for making onestep and multi-step prediction is superior to that of the traditional local linear prediction method and global SVM method. In addition, it is significant that its prediction performance is insensitive to the selection of embedding dimension and the number of nearest neighbours, so the satisfying results can be achieved even if we do not know the optimal embedding dimension and how to select the number of nearest neighbours.