关于非线性共同逼近的强唯一性

本文首先指出文献［１］中的一个错误，举例说明弱拟凸集的最佳逼近未必具有广义强唯一性，进而讨论两类共同逼近的强唯一性，在空间是一致凸、逼近集是共同太阳集的条件下，证明了最佳共同逼近具有广义强唯一性     

Banach 空间中非线性最佳逼近的广义强唯一性

设X是一致凸空间,G为X中太阳集,R．Smarzewski[1]证明了g∈G对x∈的最佳逼近具有广义强唯一性,本文讨论其逆,在最佳逼近是广义强唯一的条件下,研究了空间的凸性和逼近集的太阳性．     

取值为Banach空间的集值映射的非线性逼近

本文研究了取值为Ｂａｎａｃｈ空间中的集的集值映射的非线性逼近问题．给出集值映射的最佳逼近的特征和唯一性定理，并刻划了使其特征定理成立的非线性类的特征．     

复赋范空间中复RS集的最佳同时逼近

研究了复赋范空间中具限制系数的广义多项式集G对无穷序列的最佳同时逼近问题,得到了特征定理;当G是复RS集时还得到了惟一性定理．     

Banach空间中太阳集对无穷序列的最佳同时逼近

本文研究太阳集对一列无穷序列的最佳同时逼近问题，建立了特征及唯一性结果．     

复赋范空间中的同时太阳集的最佳逼近

研究了复赋范空间中的同时太阳集对无穷序列的最佳逼近问题，得到了特征及唯一性定理．     

联合最佳逼近

本文研究了二元函数用紧Hausdorff空间上的连续函数集的联合逼近问题,建立了包括特征定理、唯一性定理、强唯一性定理和dela Vallée Poussin定理在内的Chebyshev逼近理论。给出了求解最佳逼近元的Remes型第一算法和两种一般的简化方法。     

线性空间中的共逼近

本文研究了在局部凸空间和赋范线性空间中的（f-）共逼近和强（f-）共逼近的一些性质,给出了f-共逼近、强f-共逼近和强f-Kolmogorov集的特征定理.并举例说明G.S.Rao的两主要定理是不正确的,同时作了相应的更正.所得的结果中的部分推广和改进了Song、Rao和Narang等人的相应结果.     

单隐层神经网络与最佳多项式逼近

研究单隐层神经网络逼近问题．以最佳多项式逼近为度量,用构造性方法估计单隐层神经网络逼近连续函数的速度．所获结果表明:对定义在紧集上的任何连续函数,均可以构造一个单隐层神经网络逼近该函数,并且其逼近速度不超过该函数的最佳多项式逼近的二倍．     

有界线性算子空间中的太阳集

本文刻划有界线性算子空间中的太阳集的特征，从而给出了有界线性算子空间中非线性最佳逼近的特征定理．     

强拟闭集与强拟连续

利用半闭集引入强拟闭集概念,研究了半开集、强拟开集、强拟闭集概念之间的关系,得到了强拟闭集是连续闭映射下的不变量及其相关性质;最后给出强拟连续概念并得到其等价刻画.     

Strongly internal sets and generalized smooth functions

Based on a refinement of the notion of internal sets in Colombeau's theory, so-called strongly internal sets, we introduce the space of generalized smooth functions, a maximal extension of Colombeau generalized functions. Generalized smooth functions as morphisms between sets of generalized points form a sub-category of the category of topological spaces. In particular, they can be composed unrestrictedly.     

A minimal set-valued strong derivative for vector-valued Lipschitz functions

A set-valued derivative for a function at a point is a set of linear transformations whichapproximates the function near the point. This is stated precisely, and it is shown that, in general, there is not a unique minimal set-valued derivative for functions in the family of closed convex sets of linear transformations. For Lipschitz functions, a construction is given for a specific set-valued derivative, which reduces to the usual derivative when the function is strongly differentiable, and which is shown to be the unique minimal set-valued derivative within a certain subfamily of the family of closed convex sets of linear transformations. It is shown that this constructed set may be larger than Clarke's and Pourciau's set-valued derivatives, but that no irregularity is introduced.The author would like to thank Professor H. Halkin for numerous discussions of the material contained here.     

A note on submodular set cover on matroids

We consider a problem related to the submodular set cover on polymatroids, when the ground set is the family of independent sets of a matroid. The achievement here is getting a strongly polynomial running time with respect to the ground set of the matroid even though the family of independent sets has exponential size. We also address the optimization problem of the maximization of submodular set functions on the independent sets of a matroid.     

Priority assignment: A conditioned sets approach

The author suggests how conditioned sets of fuzzy variables may be used to provide priority weights. A case is presented where the conditioned sets approach is contrasted with the prioritization information generated by the Eigenvalue Priority Assignment Model.     

Strong Unicity of Restricted p-Centers

Given a continuous seminorm p on a separated locally convex linear topological space X, we study in this paper strong uniqueness of the so-called restricted p-centers of sets. First we explore finite extremal characterizations of strongly unique restricted p-centers of subsets of X from its finite dimensional subspaces. Our main goal here is to investigate strong uniqueness of restricted p-centers of certain sets from the so-called p-RS sets, which are defined as closed convex sets that are obtained by imposing convex side constraints arising from boundedness of coefficients on translates of certain subspaces of X.     

Improved upper and lower bounds on the feedback vertex numbers of grids and butterflies

We improve upon the best known upper and lower bounds on the sizes of minimal feedback vertex sets in butterflies. Also, we construct new feedback vertex sets in grids so that for a large number of pairs (n,m), the size of our feedback vertex set in the grid M_n,m matches the best known lower bound, and for all other pairs it differs from this lower bound by at most 2.     

An adjustable approach to intuitionistic fuzzy soft sets based decision making

Molodtsov initiated the concept of soft set theory, which can be used as a generic mathematical tool for dealing with uncertainty. There has been some progress concerning practical applications of soft set theory, especially the use of soft sets in decision making. In this paper we generalize the adjustable approach to fuzzy soft sets based decision making. Concretely, we present an adjustable approach to intuitionistic fuzzy soft sets based decision making by using level soft sets of intuitionistic fuzzy soft sets and give some illustrative examples. The properties of level soft sets are presented and discussed. Moreover, we also introduce the weighted intuitionistic fuzzy soft sets and investigate its application to decision making.     

Zero sets and uniqueness sets with one cluster point for the Dirichlet space

Zero sets and uniqueness sets of the Dirichlet space are not completely characterized yet. There are sufficient conditions for zero sets and necessary conditions for uniqueness sets and there is a gap in between. Our goal is to take some preliminary steps to fill this gap.