带有弹性碰撞的离散的凝结方程

带有弹性碰撞的离散的凝结方程是反映粒子增长动力学的数学模型，它刻划了这样一种粒子反应系统；系统中任意两个粒子碰撞后一定的概率或者凝结成为更大的粒子，或者发生弹性碰撞．本文研究了这一系统发生冻肢的可能性，并给出了一个充分条件．     

二阶三点半正边值问题正解的存在性

利用锥的Krasnosel'skill不动点定理建立了二阶三点半正边值问题u″+λf(t,u)+δg(t,u)=0, t∈(0,1),u(0)=0, αu(η)=u(1).其中,λ,δ＞0, 0＜η＜1, 0＜αη＜1正解的存在性,这里,非线性项不需要是非负的.     

THE ASYMPTOTIC SOLUTION FOR A CLASS OF SINGULARLY PERTURBED PROBLEM FOR SEMILINEAR SINGULAR EQUATION

The singularly perturbed boundary value problem for a class of semilinearsingular equation is considered. Using a simple and special method the asym-ptotic behavior of solution is studied.     

关于有限Abel群直接因子的平均数

对于有限Ａｂｅｌ群Ｇ，ｔ（Ｇ）定义为其直接因子的个数，在［５］中，Ｅ．Ｋｒａｔｚｅｌ对于和式得到一渐近公式，对应余项为△＿１（ｘ）．本文利用Ｅ．Ｆｏｕｖｒｙ和Ｈ　．Ｉｗａｎｉｅｃ的方法，得到了关于△＿１（ｘ）的一个新的估计，改进了Ｈ．Ｍｅｎｚｅｒ等人的结果．     

Operator Matrix Forms of Positive Operators

If a 3-tuple (A:H1→H1,B:H2→H1,C:H2→H2）of operators on Hibert spaces is given,we proved that the operator ～↑A:=(↑A ↓B^*↑B ↓C) on H=H1 H2 is ≥0 is and only if A≥0,R(B)∪→R（A^1/2) and C≥B^* A^ b,where A^ is the generalized inverse of A.In general,A^ is a closed operator,but since R(B)∪→R(A^1/2,B^* A^ B is bounded yet.     

EXPONENTIAL STABILITY AND PERIODIC SOLUTION OF HYBRID BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH DISCRETE DELAYS

In this paper, we study the existence, uniqueness, and the global exponential stability of the periodic solution and equilibrium of hybrid bidirectional associative memory neural networks with discrete delays. By ingeniously importing real parameters di > 0 (i = 1,2, …, n) which can be adjusted, making use of the Lyapunov functional method and some analysis techniques, some new sufficient conditions are established. Our results generalize and improve the related results in [9]. These conditions can be used both to design globally exponentially stable and periodical oscillatory hybrid bidirectional associative neural networks with discrete delays, and to enlarge the area of designing neural networks. Our work has important significance in related theory and its application.     

R.S.Singh的一个猜想的证明:离散情形

本文讨论了一维离散指数族在平方误差损失下的经验Bayes估计问题.证明了其参数的任何经验Bayes估计的渐近最优收敛速度都不可能达到O(n^-1),即使参数空间被限定于一个有限区间.这意味着,Singh(对Lebesgue指数族情形提出)的一个猜想,在离散指数族情形,被证明是正确的.     

关于图的全着色—一个综述

本文简要地综述了图的全着色的进展,给出了一些尚未解决的问题。     

模糊数序列的收敛性

探讨L-R型模糊数序列的S-和问题，定义关于模糊数的模糊小于的概念，在此基础上探讨模糊数的有序性，模糊数的截集函数的连续性，模糊数的格结构以及模糊数序列的收敛性等重要性质。