非线性Lipschitz连续算子的定量性质(Ⅲ)──glb-Lipschitz数

本文引进非线性Ｌｉｐｓｃｈｉｔｚ算子Ｔ的ｇｌｂ－Ｌｉｐｓｃｈｉｔｚ数ｌ（Ｔ）,并证明：ｌ（Ｔ）定量刻画非线性Ｌｉｐｓｃｈｉｔｚ连续算子全体所构成的赋半范算子空间中可逆算子Ｔ保持可逆的最大扰动半径,因而具有特别重要意义。所获结果被应用来建立“非线性扰动引理”、非线性算子条件数、推广线性算子逼近理论和建立与矩阵理论中Ｇｅｒｓｃｈｇｏｒｉｎ圆盘定理对应的非线性Ｌｉｐｓｃｈｉｔｚ连续算子谱集的包含域。     

一类广义Lipschitz非线性算子的带误差的Ishikawa迭代程序

借助于周海云和陈东青［４］新近引入的广义Ｌｉｐｓｃｈｉｔｚ概念,研究了实Ｂａｎａｃｈ空间中广义Ｌｉｐｓｃｈｉｔｚ　 －强伪压缩算子的不动点和广义Ｌｉｐｓｃｈｉｔｚ －强增算子方程解的迭代逼近问题,所得结果改进和扩展了近期许多相关的结果,并部分地回答了周海云［３］提出的一个问题．     

动力系统中的Lipschitz稳定性

本文讨论动力系统的Ｌｉｐｓｃｈｉｔｚ稳定性与吸引性之间的关系．给出动力系统中弱吸引性、吸引性和强吸引性这三个概念相互等价的条件，在一定的条件下证明了（弱、强）吸引子与全局（弱、强）吸引子是一致的．本文还讨论了度量Ｌｙａｐｕｎｏｖ稳定性和拓扑Ｌｙａｐｕｎｏｖ稳定性及它们与Ｌｉｐｓｃｈｉｔｚ稳定性之间的关系．     

奇异半线性发展方程的局部Cauchy问题

本文在Ｂａｎａｃｈ空间Ｅ中讨论如下问题ｄｕｄｔ＋１ｔσＡｕ＝Ｊ（ｕ），０＜ｔＴ，ｌｉｍｔ→０＋ｕ（ｔ）＝０，其中ｕ：（０，Ｔ］Ｅ，Ａ是与ｔ无关的线性算子．（－Ａ）是Ｅ上Ｃ０半群｛Ｔ（ｔ）｝ｔ０的无穷小生成元，常数σ１，Ｊ是一个非线性映射ＥＪ→Ｅ．它满足局部Ｌｉｐｓｃｈｉｔｚ条件．我们证明了当其Ｌｉｐｓｃｈｉｔｚ常数ｌ（ｒ）满足一定条件时．问题（Ｓ）有局部解，且在某函类中解唯一．设Ｊ（ｕ）＝｜ｕ｜γ－１ｕ＋ｆ（ｘ）（γ＞１），Ｅ＝Ｌｐ，ＥＪ＝Ｌｐγ时得到了与Ｗｅｉｓｌｅｒ［２］在非奇异情形类似的结果．     

Banach空间中渐近正则的Lipschitz半群的不动点定理

本文首先定义了渐近正则的Ｌｉｐｓｃｈｉｔｚ半群的概念．其次，证明了ｐ一致凸Ｂａｎａｃｈ空间中渐近正则的Ｌｉｐｓｃｈｉｔｚ半群的不动点定理．同时也证明了具有正规结构系数的一致凸Ｅａｎａｃｈ空间中的渐近正则的Ｌｉｐｓｃｈｉｔｚ半群的一个新的不动点定理．     

非线性Lipschitz算子的Lipschitz对偶算子及其应用

在文山中我们对非线性Ｌｉｐｓｃｈｉｔｚ算子定义了其Ｌｉｐｓｃｈｉｔｚ对偶算子，并证明了任意非线性Ｌｉｐｓｃｈｉｔｚ算子的Ｌｉｐｓｃｈｉｔｚ对偶算子是一个定义在Ｌｉｐｓｃｈｉｔｚ对偶空间上的有界线性算子．本文还进一步证明：设Ｃ为 Ｂａｎａｃｈ空间 Ｘ的闭子集，Ｃ＊Ｌ为Ｃ的 Ｌｉｐｓｃｈｉｔｚ对偶空间，Ｕ为 Ｃ＊Ｌ上的有界线性算子，则当且仅当 Ｕ为 ｗ＊－ｗ＊连续的同态变换时，存在Ｌｉｐｓｃｈｉｔｚ连续算子Ｔ，使Ｕ为Ｔ的Ｌｉｐｓｃｈｉｔｚ对偶算子．这一结论的理论意义在于：它表明一个非线性Ｌｉｐｓｃｈｉｔｚ算子的可逆性问题可转化为有界线性算子的可逆性问题．作为应用，通过引入一个新概念──ＰＸ－对偶算子，在一般框架下给出了非线性算子半群的生成定理．     

局部凸空间上的泛函的非光滑分析及多目标规划

该文对定义于局部凸线性拓扑空间Ｘ上的泛函引入广义方向导数、广义梯度及满足Ｌｉｐｓ－ｃｈｉｔｚ条件等概念,证明了它们的几个重要性质,并举例说明这里满足Ｌｉｐｓｃｈｉｔｚ条件的概念是Ｂａ－ｎａｃｈ空间情形的严格推广．最后,作为上述结论及方法的应用,讨论定义于Ｘ的多目标数学规划,得出若干关于弱有效解的最优性条件．     

Banach空间中关于Lipschitz φ-半压缩映象的带误差项的Ishikawa迭代过程

本文在任意Ｂａｎａｃｈ空间中研究了Ｌｉｐｓｃｈｉｔｚ φ－半压缩映象与φ－强拟增生映象的带误差项的Ｉｓｈｉｋａｗａ迭代过程,使用新的分析技巧建立了几个强收敛定理．     

非线性Lipschitz-α算子的若干性质

本文引入并研究Ｌｉｐｓｃｈｉｔｚ－α算子（简称Ｌｉｐ－α算子）我们首先给出这类算子的定义及其基本性质;然后,讨论Ｌｉｐ－α算子的可逆性并引入它的α－阶条件数,并给出其在研究非线性算子方程扰动问题中的一个应用;其次,还研究了Ｌｉｐ－α算子列的收敛性,引入并研究了Ｌｉｐ－α极限与Ｌｉｐ－α　Ｃａｕｃｈｙ列,证明过零Ｌｉｐ－α算子空间是一个Ｂａｎａｃｈ空间．     

Lipschitz常数缩减的散乱数据插值

在计算机辅助设计几何中，变差缩减是一个非常重要的概念，本文分析了函数的变差和Ｌｉｐｓｃｈｉｔｚ常数的关系，指出可以用Ｌｉｐｓｃｈｉｔｚ常数来控制变差，由于变差的概念只限于一维的情形，而Ｌｉｐｓｃｈｉｔｚ常数适用于任意维，这样在高维时就可用Ｌｉｐｓｃｈｉｔｚ常数缩减的概念来代替变差缩减的概念，文中构造性地证明了Ｌｉｐｓｃｈｉｔｚ常数缩减的散乱数据插值函数的存在性，并且对这类函数的性质及光滑性条件进行了讨论．     

LIPSCHITZ STABILITY OF GENERAL CONTROL SYSTEMS Ⅱ.IN TERMS OF TWO MEASURES

1IntroductionStabilityintermsoftwomeasures,thisconceptenableustounifyava-rietyofstabilityconceptsandtoofferageneralandunifiedframeworkforinvestigationofstabilitytheory.AndtheoriginalLiapunovtheoremshavebeenextended,generalizedandweakenedinvariousaspects[3…     

广义控制系统在两种尺度意义下的稳定性

本文将两尺度稳定性理论引入了广义控制系统，并用类Ｌｉａｐｕｎｏｖ函数给出稳定和渐近稳定的充要条件。这些准则推广了关于广义控制系统和两尺度稳定性的已有结果，使我们能在一个统一的框架内研究广义控制系统稳定性。     

LIPSCHITZ STABILITY OF DYNAMICAL SYSTEMS IN TERMS OF TWO MEASURES

ＬＩＰＳＣＨＩＴＺＳＴＡＢＩＬＩＴＹＯＦＤＹＮＡＭＩＣＡＬＳＹＳＴＥＭＳＩＮＴＥＲＭＳＯＦＴＷＯＭＥＡＳＵＲＥＳ（金淦）广东石油化工高等专科学校，邮编：５２５０００ＪｉｎＧａｎ（ＧｕａｎｇｄｏｎｇＰｅｔｒｏ－ＣｈｅｍｉｃａｌＣｏｌｌｅｇｅ）Ａｂｓｔｒ...     

LIPSCHITZ SEMISTABILITY OF GENERAL CONTROL SYSTEMS IN TERMS OF TWO MEASURES

1 IntroductionLipschitz semistability of dynamical systems in terms of two measures andLipschitz semistability of general control systems have already been,t.di.d[llt12].In this papers semistability considerations will be extended to a variety of nonlinear systems utilizing the same versatile tools, namely, Liapunov--like functions. The notions of (ho, h)-Lipschitz (weak) semistability of general controlsystems are introduced, and the necessary and sufficient conditions are given.2 Prelimina…     

A linearization framework for unconstrained quadratic (0-1) problems

In this paper, we are interested in linearization techniques for the exact solution of the Unconstrained Quadratic (0-1) Problem. Our purpose is to propose “economical” linear formulations. We first extend current techniques in a general linearization framework containing many other schemes and propose a new linear formulation. Numerical results comparing classical, Glover’s and the new linearization are reported.     

Tightening concise linear reformulations of 0-1 cubic programs

A common strategy for solving 0-1 cubic programs is to reformulate the non-linear problem into an equivalent linear representation, which can then be submitted directly to a standard mixed-integer programming solver. Both the size and the strength of the continuous relaxation of the reformulation determine the success of this method. One of the most compact linear representations of 0-1 cubic programs is based on a repeated application of the linearization technique for 0-1 quadratic programs introduced by Glover. In this paper, we develop a pre-processing step that serves to strengthen the linear programming bound provided by this concise linear form of a 0-1 cubic program. The proposed scheme involves using optimal dual multipliers of a partial level-2 RLT formulation to rewrite the objective function of the cubic program before applying the linearization. We perform extensive computational tests on the 0-1 cubic multidimensional knapsack problem to show the advantage of our approach.     

广义R0-代数

给出一种基于左连续的广义t-模的代数——广义R0-代数的定义和若干性质。     

Analytic solutions of the (2 + 1)-dimensional nonlinear evolution equations using the sine-cosine method

In this paper, we establish exact solutions for (2 + 1)-dimensional nonlinear evolution equations. The sine-cosine method is used to construct exact periodic and soliton solutions of (2 + 1)-dimensional nonlinear evolution equations. Many new families of exact traveling wave solutions of the (2 + 1)-dimensional Boussinesq, breaking soliton and BKP equations are successfully obtained. These solutions may be important of significance for the explanation of some practical physical problems. It is shown that the sine-cosine method provides a powerful mathematical tool for solving a great many nonlinear partial differential equations in mathematical physics.     

实数完备性的另一个刻划及其应用——从实分析非绝对积分理论中的δ-精细分法说起

闭区间上δ-精细的分法是实分析非绝对积分理论中使用极为频繁的概念之一 .但是该概念的实质究竟是什么 ,本文指出 :“对任何 δ( x) >0 ,闭区间上存在 δ-精细的分法”,其实质就是实数的完备性 ;并利用该结论对数学分析中闭区间上连续函数的整体性质给出了简单证明 .     

A new linearization technique for multi-quadratic 0-1 programming problems

We consider the reduction of multi-quadratic 0-1 programming problems to linear mixed 0-1 programming problems. In this reduction, the number of additional continuous variables is O(kn) (n is the number of initial 0-1 variables and k is the number of quadratic constraints). The number of 0-1 variables remains the same.