ICP-OES测定钒矿石中五氧化二钒的测量不确定度评定

介绍了电感耦合等离子体发射光谱法(ICP-OES)测定钒矿石中五氧化二钒测重不确定度的评定万法.建立了测量过程中各不确定度分量的数学模型,对不确定度来源进行了分析,并对不确定度分量进行量化.当钒矿石中五氧化二钒含量为0.419％时,其扩展不确定度为0.0070％(k=2).     

On the Colin de Verdière number of graphs

Let μ(G) and ω(G) be the Colin de Verdière and clique numbers of a graph G, respectively. It is well-known that μ(G)?ω(G)-1 for all graphs. Our main results include μ(G)?ω(G) for all chordal graphs; μ(G)?tw(G)+1 for all graphs (where tw is the tree-width), and a characterization of those split (⊆ chordal) graphs for which μ(G)=ω(G). The bound μ(G)?tw(G)+1 improves a result of Colin de Verdière by a factor of 2.     

Parameter dependence for a class of ordinary differential equations with measurable right‐hand side

The paper studies differential equations of the form u′(x) = f(x, u(x), λ(x)), u(x₀) = u₀, where the right‐hand side is merely measurable in x. In particular sufficient conditions for the continuous and the differentiable dependence of solution u on the data and on the parameter λ are stated. © 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim     

基于函数值的线性有理插值样条的区域控制

将插值曲线约束于给定的区域之内是插值与逼近的一个重要内容.本文讨论了一种带形状参数的线性有理插值样条的区域控制问题.给出将插值曲线约束于给定的折线及抛物线之上、之下或之间的条件.数值实例表明本文给出的条件在曲线设计中是有效的.     

Multiple limit cycle bifurcations of the FitzHugh–Nagumo neuronal model

In this paper, we complete the global qualitative analysis of the well-known FitzHugh–Nagumo neuronal model. In particular, studying global limit cycle bifurcations and applying the Wintner–Perko termination principle for multiple limit cycles, we prove that the corresponding dynamical system has at most two limit cycles.     

Efficiency measurement using independent component analysis and data envelopment analysis

Efficiency measurement is an important issue for any firm or organization. Efficiency measurement allows organizations to compare their performance with their competitors’ and then develop corresponding plans to improve performance. Various efficiency measurement tools, such as conventional statistical methods and non-parametric methods, have been successfully developed in the literature. Among these tools, the data envelopment analysis (DEA) approach is one of the most widely discussed. However, problems of discrimination between efficient and inefficient decision-making units also exist in the DEA context (Adler and Yazhemsky, 2010). In this paper, a two-stage approach of integrating independent component analysis (ICA) and data envelopment analysis (DEA) is proposed to overcome this issue. We suggest using ICA first to extract the input variables for generating independent components, then selecting the ICs representing the independent sources of input variables, and finally, inputting the selected ICs as new variables in the DEA model. A simulated dataset and a hospital dataset provided by the Office of Statistics in Taiwan’s Department of Health are used to demonstrate the validity of the proposed two-stage approach. The results show that the proposed method can not only separate performance differences between the DMUs but also improve the discriminatory capability of the DEA’s efficiency measurement.     

Parameter choice methods using minimization schemes

Regularization is typically based on the choice of some parametric family of nearby solutions, and the choice of this family is a task in itself. Then, a suitable parameter must be chosen in order to find an approximation of good quality. We focus on the second task. There exist deterministic and stochastic models for describing noise and solutions in inverse problems. We will establish a unified framework for treating different settings for the analysis of inverse problems, which allows us to prove the convergence and optimality of parameter choice schemes based on minimization in a generic way. We show that the well known quasi-optimality criterion falls in this class. Furthermore we present a new parameter choice method and prove its convergence by using this newly established tool.     

严格反馈非线性系统中参数收敛的系统化方法

研究严格反馈非线性系统中参数的收敛性.在适当的持续激励条件下,通过构造一个显式、全局的强Lyapunov函数,给出了系统参数估计收敛于真值的充分条件,且闭环信号全局一致有界,跟踪误差渐近收敛于零.仿真算例验证了设计方案的可行性和有效性.     

组合GM(1,1)幂模型及其应用

GM(1,1)幂模型是灰色Verhulst模型的推广.由于初始条件选取影响GM(1,1)幂模型的精度,将平均相对误差函数分别看成是幂指数、发展系数、灰作用量的函数,利用蚁群算法进行参数辨识,从而建立多个单项GM(1,1)幂模型.利用这些单项模型建立了线性组合GM(1,1)幂模型,组合权系数利用最大相对误差最小化原则采用粒子群算法确定.实例表明,组合GM(1,1)幂模型的建模精度高于传统GM(1,1)幂模型,同时也说明方法是有效的和可行的,具有重要的理论意义.     

一阶多参数模糊微分方程及定解问题

在单参数模糊微分方程基础上研究了一阶多参数模糊微分方程和模糊初值问题,利用刻画方程的解与刻画参数的关系给出了多参数模糊微分方程解存在的条件,最后给出了具体算例.表明,多参数模糊微分方程具有广泛的工程应用背景.