关于两类具有不同基函数的标准模糊系统逼近精度问题的研究

在标准模糊系统的基础上提出了以正规二次多项式和正规三角函数为基函数的两类标准模糊系统.通过采用数值分析中的余项与辅助函数方法,对这两类模糊系统进行了误差精度的分析,给出了从SISO到MISO的误差界公式.同时,对这两类模糊系统误差界进行了比较,指出了两类模糊系统的优劣.最后,通过算例验证了理论结果的正确性.     

利用模糊系统求解非线性Fredholm-Ⅱ积分方程

提出了一种利用模糊系统求解非线性Fredholm-Ⅱ积分方程解析解的方法:首先将积分方程转化为模糊系统,然后利用具有紧支集和正规性的尺度函数构造模糊基函数和积分方程的模糊解,最后构造能量误差函数,通过最小化误差函数学习模糊系统的参数.数值实验表明:用模糊系统求得的便于运算的解析解比用Galerkin方法求得的数值解精度高.     

R_O-蕴涵算子所导出的逻辑函数的特征

R_0-蕴涵算子是王国俊在2000年建立的一种新型蕴涵算子.目前,R_0-蕴涵算子在模糊控制、近似推理、模糊识别、模糊系统、计量逻辑的研究方面有着重要应用,而这些应用的共同点,是公式通过R_0-蕴涵算子所导出的逻辑函数在其中发挥着关键的作用.本文在R_0-型命题逻辑系统中,对由n个原子公式生成的公式通过R_0-蕴涵算子导出的逻辑函数的特征进行了研究,得到了函数可由R_0-型命题逻辑系统中的公式通过R_0-蕴涵算子导出的充要条件.     

模糊值函数分析学的结构元方法简介(Ⅰ)——结构元与模糊数运算

简述了模糊值函数分析学在具体工程实践应用中存在的困难和障碍,系统地介绍了模糊结构元方法在模糊值函数分析学中的应用,包括模糊结构元的概念、模糊数的模糊结构元表示形式、基于结构元表达形式的模糊数运算与隶属函数确定.模糊结构元方法将复杂的模糊数运算转化为一类单调有界函数的运算,不仅仅为模糊分析计算的简化提供了工具,同时也为模糊值函数分析学应用的研究开创了一条新的途径.     

模糊过程与模糊微分方程的解法

本文在模糊变量和动态模糊集合的基础上定义了模糊过程、构造了它的F样本函数,然后用F样本函数定义了模糊过程的a.f.s微积分,并讨论了它们的性质;在此基础上,本文提出了非齐次项是模糊过程的微分方程的基本解法,从而为分析动态系统受模糊干扰的响应提供了基础。     

非线性多时滞系统的直接自适应模糊控制

针对一类单输入单输出非线性多时滞系统,提出了一种自适应模糊跟踪控制方案.该方案结合了自适应控制和H∞控制.构建了自适应时滞模糊逻辑系统用来逼近未知时滞函数;设计了H∞补偿器来抵消模糊逼近误差和外部扰动.根据跟踪误差给出了参数调节规律.证明了误差闭环系统满足期望的H∞跟踪性能.仿真结果表明了该方案的有效性.     

模糊值函数在模糊数积分区间[(A～,B～)]上的N-L公式

文[1]给出模糊值函数在普通区间[a,b]上的N-L公式.本文在文[1]的基础上进一步给出模糊值函数在模糊数区间[(A～,B～)]上的积分.这个积分是Ⅱ型模糊集.文[3]已经指出(F2[0,1],∪,∩,c)不是软代数,但这个积分是一个特殊Ⅱ型模糊集仍具有许多良好的代数性质,并存在着N-L公式.     

基于贝塞尔曲线理论的备件需求模糊隶属度函数构建模型

用模糊理论描述备件需求是一种科学适用的方法,针对现有模糊变量隶属度函数构建方法的不足, 设计了基于贝塞尔曲线理论的备件需求模糊隶属度函数构建方法,给出了隶属度求解算法,分析了使拟合误差最小的控制点选择方法.同时通过实例验证以及与最小二乘法的对比分析,验证了贝塞尔曲线方法在构建备件需求模糊隶属度函数方面的有效性.此方法无需事先假设隶属度函数的形态,简单易用、使用灵活并且精度较高.     

同一水平下模糊规则信息熵的描述

给出了模糊知识系统及模糊决策逻辑公式的定义,在此基础上描述了模糊决策逻辑公式及模糊知识系统下模糊规则的信息熵,讨论了模糊规则信息熵的相关性质;其次,利用模糊规则信息熵对模糊规则进行了分类、评价,从而为建立合理的模糊系统提供了一种有效的判定方法;最后,通过实例验证了所提出理论的正确性.     

模糊牛顿插值及模糊样条函数的表示

本文在模糊Ｌａｇｒａｎｇｅ插值的基础上，引进了模糊牛顿插值公式及其适定性定理和求法。并针对“非结点”型边界条件给出了模糊样条函数的具体表示。     

Approximation by fuzzy B-spline series

We study properties concerning approximation of fuzzy-number-valued functions by fuzzy B-spline series. Error bounds in approximation by fuzzy B-spine series are obtained in terms of the modulus of continuity. Particularly simple error bounds are obtained for fuzzy splines of Schoenberg type. We compare fuzzy B-spline series with existing fuzzy concepts of splines.     

Willis环状脑动脉瘤系统的自适应模糊控制

针对不确定非线性生物系统—W illis环状脑动脉瘤系统,利用高斯型模糊逻辑系统的逼近能力及新构造的Lyapunov函数,基于模糊建模提出了一种自适应模糊控制器设计的新方案.该方案把逼近误差引入到控制器设计条件中用以改善系统的动态性能.不但设计简单还保证了控制方法的鲁棒性与稳定性.通过反向传播算法调整模糊基函数参数及递归最小二乘法调整参数向量,θ更新控制律,实现了理想跟踪.从理论上研究了脑动脉瘤内血流速度的非线性行为及控制,具有实际意义.仿真结果表明该控制方法的有效性.     

Approximating Gradients with Continuous Piecewise Polynomial Functions

Motivated by conforming finite element methods for elliptic problems of second order, we analyze the approximation of the gradient of a target function by continuous piecewise polynomial functions over a simplicial mesh. The main result is that the global best approximation error is equivalent to an appropriate sum in terms of the local best approximation errors on elements. Thus, requiring continuity does not downgrade local approximation capability and discontinuous piecewise polynomials essentially do not offer additional approximation power, even for a fixed mesh. This result implies error bounds in terms of piecewise regularity over the whole admissible smoothness range. Moreover, it allows for simple local error functionals in adaptive tree approximation of gradients.     

Monotone Approximation of Random Functions with Multivariate Domains in Respect of Lattice Semi-Norms

Consider the problem of approximating a random function which is defined on a compact and convex subset of a topological vector space. For monotone approximation procedures, global and local error bounds with respect to lattice semi-norms are established.     

A fractional version of the peano-sard theorem

Sard's classical generalization of the Peano kernel theorem provides an extremely useful method for expressing and calculating sharp bounds for approximation errors. The error is expressed in terms of a derivative of the underlying function. However, we can apply the theorem only if the approximation is exact on a certain set of polynomials.

In this paper, we extend the Peano-Sard theorem to the case that the approximation is exact for a class of generalized polynomials (with non-integer exponents). As a result, we obtain an expression for the remainder in terms of a fractional derivative of the function under consideration. This expression permits us to give sharp error bounds as in the classical situation. An application of our results to the classical functional (vanishing on polynomials) gives error bounds of a new type involving weighted Sobolev-type spaces. In this way, we may state estimates for functions with weaker smoothness properties than usual.

The standard version of the Peano-Sard theory is contained in our results as a special case.     

Error Bounds of Constrained Quadratic Functions and Piecewise Affine Inequality Systems

We consider the error bounds for a piecewise affine inequality system and present a necessary and sufficient condition for this system to have an error bound, which generalizes the Hoffman result. Moreover, we study the error bounds of the system determined by a quadratic function and an abstract constraint.     

改进Lagrange插值多项式误差上界的系数

当用Lagrange插值多项式逼近函数时,重要的是要了解误差项的性态.本文研究具有等距节点的Lagrange插值多项式,估计了Lagrange插值多项式逼近函数误差项的上界,改进了小于5次Lagrange插值多项式逼近函数误差界的系数.     

一个最优的模糊逼近器

In a dot product space with the reproducing kernel (r. k. S. ) ,a fuzzy system with the estimation approximation errors is proposed ,which overcomes the defect that the existing fuzzy control system is difficult to estimate the errors of approximation for a desired function,and keeps the characteristics of fuzzy system as an inference approach. The structure of the new fuzzy approximator benefits a course got by other means.     

On the application of the residual method for the correction of inconsistent problems of convex programming

For the correction of a convex programming problem with potentially inconsistent constraint system (an improper problem), we apply the residual method, which is a standard regularization procedure for ill-posed optimization models. A problem statement typical for the residual method is reduced to a minimization problem for an appropriate penalty function. We apply two classical penalty functions: the quadratic penalty function and the exact Eremin-Zangwill penalty function. For each of the approaches, we establish convergence conditions and bounds for the approximation error.