A Probe Method of Gradient Projection Type

§１．　ＩｎｔｒｏｄｕｃｔｉｏｎＷｅｃｏｎｓｉｄｅｒｔｈｅｆｏｌｌｏｗｉｎｇｏｐｔｉｍｉｚａｔｉｏｎｐｒｏｂｌｅｍ：（Ｐ）　　ｍｉｎｘ∈Ｘｆ（ｘ）（１）ｗｈｅｒｅＸ＝｛ｘ｜ｘ∈Ｅｎ,ｇｊ（ｘ）≤０,ｊ＝１,２,…,ｍ;ｇｊ（ｘ）＝０,ｊ＝ｍ＋１,…,ｍ＋ｌ｝,ｌｅｔＩ＝｛１,２,…,ｍ｝,Ｌ＝｛ｍ＋１,…,ｍ＋ｌ｝．Ｆｏｒｔｈｅｐｒｏｂｌｅｍ（Ｐ）ｗｉｔｈＬ＝,ｍａｎｙｅｆｆｉｃｉｅｎｔｐｒｏｊｅｃｔｉｏｎｔｙｐｅａｌｇｏｒｉｔｈｍｓ［１－１１］ｈａｖｅｂｅｅｎｐｒｏｐｏｓｅｄ．Ｉｎ［１２］,…     

一类序保持系统解的收敛性

本文研究微分方程组ｘｉ＝Ｆｉ（ｘ１，…ｘｎ）（ｘ∈Ｒｎ＋）解的收敛性．如果该系统满足下列条件：（ｉ）Ｆ（Ｏ）Ｏ；（ｉ）Ｆｉ（ｘ１，…ｘｎ）关于ｘｋ是单调增的（ｋ≠ｉ）；（ｉｉ）Ｆ（ｘ＊ｇ（ｓ））ｈ（ｓ）＊Ｆ（ｘ）（０ｓ１），这里ｘ＊ｙ＝（ｘ１ｙ１，…ｘｎｙｎ），ｇ，ｈ：［０，１］→［０，１］ｎ满足ｇｉ（０）＝ｈｉ（０）＝Ｏ，ｇｉ（１）＝ｈｉ（１）＝１，Ｏ＜ｇｉ（ｓ），ｈｉ（ｓ）＜１，ｓ∈（０，１）；（ｉｖ）系统的每个解在Ｒｎ＋中有界，则每个解收敛于奇点．本文还把这一结果推广到离散的序保持动力系统．     

抽象算子在偏微分方程中的应用(Ⅱ)

Ｔｈｅｏｒｅｍ１　Ｌｅｔｍ∈Ｎａｎｄｍ１,Ｐ（ｘ）ｂｅａｎａｒｂｉｔｒａｒｙｏｒｄｅｒｐａｒｔｉａｌｄｉｆｆｅｒｅｎｔｉａｌｏｐｅｒａ－ｔｏｒ．Ｔｈｅｎｆ（ｘ,ｔ）,φｊ（ｘ）∈Ｊ．（ＷｈｅｒｅＪｓｔａｎｄｆｏｒｔｈｅｓｅｔｏｆａｎａｌｙｔｉｃｆｕｎｃｔｉｏｎｉｎｔｈｉｓｐａｐｅｒ）ｔ＋Ｐ（ｘ）ｍｕ＝ｆ（ｘ,ｔ）ｊｕｔｊｔ＝０＝φｊ（ｘ）　　ｘ∈Ｒｎ,ｔ∈Ｒ１ｊ＝０,１,２,…,ｍ－１．ｕ（ｘ,ｔ）＝∫ｔ０（ｔ－τ）ｍ－１（ｍ－１）！ｅ－（ｔ－τ）Ｐ（ｘ）ｆ（ｘ,τ）ｄτ＋ｅ－…     

齐型空间上的Lipschitz函数与Littlewood－Paley g－函数

在θ阶正规齐型空间上，如果算子列｛Ｓｋ｝ｋ∈Ｚ是恒等逼近，Ｄｋ＝Ｓｋ－Ｓｋ－１；本文给出一个用｛Ｄｋ｝ｋ∈Ｚ表达的ｆ∈Ｌｉｐα（Ｌｉｐｓｃｈｉｔｚ函数类，０＜α＜θ）的充分必要条件．作为其推论得到，对于ｆ∈ＬＩｐα，其Ｌｉｔｔｌｅｗｏｏｄ－Ｐａｌｅｙｇ函数ｇ（ｆ）（Ｘ）或者处处为无穷大，或者在Ｌｉｐα上有界．     

齐型空间上的Lipschitz函数与Littlewood－Paley g－函数

在θ阶正规齐型空间上，如果算子列｛Ｓｋ｝ｋ∈Ｚ是恒等逼近，Ｄｋ＝Ｓｋ－Ｓｋ－１；本文给出一个用｛Ｄｋ｝ｋ∈Ｚ表达的ｆ∈Ｌｉｐα（Ｌｉｐｓｃｈｉｔｚ函数类，０＜α＜θ）的充分必要条件．作为其推论得到，对于ｆ∈ＬＩｐα，其Ｌｉｔｔｌｅｗｏｏｄ－Ｐａｌｅｙｇ函数ｇ（ｆ）（Ｘ）或者处处为无穷大，或者在Ｌｉｐα上有界．     

相依样本下非参数回归函数递推型核估计的渐近分布

设（Ｘｉ，Ｙｉ）１≤ｉ≤ｎ为来自二元总体（Ｘ，Ｙ）的平稳，φ－混合样本，记ｍ（ｘ）△Ｅ（Ｙ│Ｘ＝ｘ），ｍ（ｘ）的一种递推型核估计为ｍｎ（ｘ）＝ｎ∑ｉ＝１ｈｉ＾－１Ｙｉｋ（（ｘ－Ｘｉ）／ｈｉ）／ｎ∑ｊ＝１ｈ＾－１ｊｋ（ｘ－Ｘｊ）／ｈｊ）。本文在一定的条件下证明了（ｎ／（ｎ∑ｊ＝１ｈ＾－１ｊ）＾１／２）（ｍｎ（ｘ１）－ｍ（ｘ１），ｍｎ（ｘ２）－ｍ（ｘ２），．．．ｍｎ（ｘｒ０）－ｍ（ｘｒ０））′依分布收     

一个二维整数瓶颈问题及其算法

本文讨论了数学模型：ｍａｘ｛ｆ（ｘ）│ｆ（ｘ）＝ｍｉｎ（１≤ｊ≤ｎ）〔ｃ１ｊｘ１ｊ＋ｃ２ｊｘ２ｊ〕，ｘ∈Ｄ｝，其中Ｄ＝｛ｘ│ｘ＝｛ｘｉｊ｝，ｎΣ（ｊ＝１）ｘｉｊ＝ａ，ｉ＝１，２，ｘｉｊ≥０且为整数｝，并给出了一个拟多项式算法。     

一类不可微优化的极大熵方法的收敛性

本文对求解如下问题的极大熵方法的收敛性质进行了研究：（Ｐ）ｍｉｎｆ（ｘ）＝ｍａｘ｛ｆｉ（ｘ）｝,ｓ,ｔ。ｘ∈Ω＝｛ｘ∈Ｒ＾ｎ│ｇｊ（ｘ）≤０,ｊ＝１,…,ｌ｝。其中ｍ≥１,ｌ≥０为整数;若ｌ＝０,规定Ω＝Ｒ＾ｎ。     

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．     

向量值马氏决策规划的线性加权解法

类似［１－４］,折扣向量值马氏决策规划（ＤＶＭＤＰ）描述为： ｛Ｓ,（Ａ（ｉ）,ｉ∈Ｓ）,ｑ,ｒ,Ｖβ｝,（１）其中Ｓ为可数状态集,Ａ（ｉ）是有限决策集,ｑ（ｊ｜ｉ,ａ）是转移概率,ｒ＝ｒ（ｉ,ｊ,ａ）＝（ｒ１（ｉ,ｊ,ａ）,ｒ２（ｉ,ｊ,ａ）,…,ｒｐ（ｉ,ｊ,ａ））是状态ｉ处使用决策ａ于下一步转移到状态ｊ时所获的ｐ维报酬向量,ｒ（ｉ,ｊ,ａ）对ｉ,ｊ,ａ一致有界,Ｖβ是β折扣目标． 以Π表一般策略集,若　π　∈Π有 Ｖβ（π）≤ Ｖβ（π*）,则称π* 为ＤＶＭＤＰ的“强有效策略”,Ｖβ（π*）为“…     

ON A THEOREM OF A.A. LYAPUNOV

Abstract

In this note we obtain some extensions and an approximation of the Lyapunov convexity theorem by means of the bilinear integration of a set-valued function. The integration is performed successively with respect to a non-atomic, a direct sum and a Darboux vector measure. The necessary counterexamples are provided.     

A Priori and A Posteriori: A Bootstrapping Relationship

The distinction between a priori and a posteriori knowledge has been the subject of an enormous amount of discussion, but the literature is biased against recognizing the intimate relationship between these forms of knowledge. For instance, it seems to be almost impossible to find a sample of pure a priori or a posteriori knowledge. In this paper, it will be suggested that distinguishing between a priori and a posteriori is more problematic than is often suggested, and that a priori and a posteriori resources are in fact used in parallel. We will define this relationship between a priori and a posteriori knowledge as the bootstrapping relationship. As we will see, this relationship gives us reasons to seek for an altogether novel definition of a priori and a posteriori knowledge. Specifically, we will have to analyse the relationship between a priori knowledge and a priori reasoning, and it will be suggested that the latter serves as a more promising starting point for the analysis of aprioricity. We will also analyse a number of examples from the natural sciences and consider the role of a priori reasoning in these examples. The focus of this paper is the analysis of the concepts of a priori and a posteriori knowledge rather than the epistemic domain of a posteriori and a priori justification.     

NAMING A COLUMN ON A SPREADSHEET

Spreadsheets use a meaningful algebra-like notation which, research suggests, can support pupils in developing an understanding of variables. This paper discusses the activity of Year 8 pupils who were taught to name a column on a spreadsheet, and who were asked to reflect upon their activity in a stimulated recall interview. More specifically, it considers the pupils' understanding of notation, such as 'A2' and 'm', which they used when constructing spreadsheet formulae. It is suggested that experience of naming columns may help pupils to develop a clearer sense of the notation as a variable, and to make links between their spreadsheet activity and use of standard algebraic notation [1].     

A REMARK ON A BMO MARTINGALE

Let M = (Mt,Ft) be a uniformly integrable continuous martingale with MO = 0. For1 5 p < cot we setIIMllBMO. = '3p II[E[IMoo ~ MTIplFT]]'/Pll.,where the supremum is taken over all stopping times T.Set BMO. = {M: IIMllBMO. < co}. It is well known that BMO. = BMO, (VI S p 5 q).F'urthermore, all 11.llBMO. norms are equivalent andIIi ~~if;llMllBMO. = SUP T P(T < co)i'where the supremum is taken over all stopping times T satisfying P(T < co) > 0. In the laterwe shall simply …     

有限群的一个类函数的模构造

本文研究了有限群上的一个类函数.通过计算它和不可约特征标的内积,证明了它是特征标并且通过复群代数的中心的正则表示给出了它的一个模构造.     

A new characterization of A 5

Let G be a group and τ _e (G) the set of numbers of elements of G of the same order. In this paper, by τ _e (G), we give a new characterization of A ₅, where A ₅ is the alternating group of degree 5. We get the theorem following: Theorem. Let G be a group, ${G\cong A_5}$ if and only if τ _e (G) = τ _e (A ₅) = {1, 15, 20, 24}.