广义共同逼近问题的适定性

设C是实Banach空间X中有界闭凸子集且0是C的内点，G是X中非空闭的有界相对弱紧子集.记K(X)为X的非空紧凸子集全体并赋Hausdorff距离，KG(X)为集合｛A∈K(X)；A∩G=｝的闭包.称广义共同逼近问题minC(A,G)是适定的是指它有唯一解(x0,z0)，且它的每个极小化序列均强收敛到(x0,z0).在C是严格凸和Kadec的假定下，证明了｛A∈K(X)；minC(A，G)是适定的｝含有KG(X)中稠Gδ子集，这本质地推广和延拓了包括De Blasi,Myjak and Papini［1］、Li［2］和De Blasi and Myjak［3］等人在内的近期相应结果.     

非线性Φ 伪压缩映象不动点的具误差的迭代过程

该文的目的是要引入比重要的 强伪压缩映象更一般的Φ 伪压缩映象，并且在更一般的假设下，用具误差的 Ishikawa和 Mann迭代过程去研究这类映象不动点的迭代逼近问题。研究结果表明：Φ 伪压缩映象T的一致连续性保证了在任意实Banach空间E中，Ishikawa迭代序列强收敛于T的唯一不动点；进一步，如果E是一致光滑的则T的连续性是不必要的     

逼近Banach空间中渐近非扩张映象的不动点

设E是一致凸Banach空间,C是E的非空闭凸子集, T:C→C是具有不动点的渐近非扩张映象. 该文证明了, 在某些适当的条件下, 由下列修改了的Ishikawa迭代程序所定义的序列{x\-n},\$\$x\-\{n+1\}=t\-nT\+n(s\-nT\+nx\-n+(1-s\-n)x\-n)+(1-t\-n)x\-n,\$\$弱收敛到T的不动点, 其中{t\-n},{s\-n}是区间\[0,1\]中满足某些限制的实数列.     

K—S函数的凸性问题

本文讨论了极大熵方法中有关Ｋ－Ｓ函数的几种凸性，从而进一步拓广了极大熵方法在非线性规划等领域中的应用。     

关于增生算子方程解的带误差的Ishikawa迭代程序

该文在Banach空间中证明了，带误差的Ishikawa迭代序列强收敛到Lipschitz连续的增生算子方程的唯一解．而且，也给Ishikawa迭代序列提供了一般的收敛率估计．利用该结果还推得，带误差的Ishikawa迭代序列也强收敛到Lipschitz连续的强增生算子方程的唯一解．     

一般随机Dirichlet级数所表示的整函数

该文研究了一般随机Dirichlet级数的所表示整函数增长性和值分布，得出了重要结论：在适当条件下，任何水平带形上或水平线上增长级与全面上相同，对于ρ随机Dirichlet级数(0＜ρ＜∞)a.s.在任何宽为〖SX(〗π[]ρ〖SX)〗的水平带形内，至少有一条ρ级没有有穷例外值的Borel线。     

广义系统的Hamilton矩阵与H\-2代数Riccati方程的稳定化解

研究线性连续广义系统的Hamilton矩阵及H\-2代数Riccati方程.　提出一个标准的广义H\-2代数Riccati方程及对应的Hamilton矩阵，给出该Hamilton矩阵的几个重要性质. 在此基础上，得到该广义H\-2代数Riccati方程的稳定化解存在的一个充分条件并给出求解方法.此条件具有一般性, 主要定理是正常系统相应结果的推广.     

平衡规划问题的熵函数方法及其在混合交通流中的应用

将参变极值问题的极大熵函数方法应用到求解平衡规划问题中,通过先验分布信息和Kullback熵概念,给出了平衡规划问题基于Kullback熵表示的熵函数求解方法,并将平衡规划的极大熵函数方法应用于求解混合交通平衡分配问题．     

非Lipschitz条件下g 上鞅的非线性Doob Meyer分解

作者讨论非Lipschitz条件下g 上鞅的非线性Doob Meyer 分解.　为此讨论一类漂移系数g(s,·,·)关于(y,z)不满足Lipschitz条 件的倒向随机微分方程解的存在唯一性,运用Biharis不等式证明了一类倒向随机微分方程的比较定理以及g 上解的极限定理.     

压缩感知中信号重构的极大熵方法(英文)

本文针对压缩感知理论中BP算法的l1最优化问题,构造了一种新的信号重构的极大熵方法.极大熵方法克服了l1最优化问题的非光滑性,同时根据同伦方法构造极大熵函数的最优解序列来逼近全局最优稀疏解.数值实验表明极大熵方法是十分有效的信号重构方法.     

On the cycle maximum of birth–death processes and networks of queues

This paper considers the cycle maximum in birth–death processes as a stepping stone to characterisation of the asymptotic behaviour of the maximum number of customers in single queues and open Kelly–Whittle networks of queues. For positive recurrent birth–death processes we show that the sequence of sample maxima is stochastically compact. For transient birth–death processes we show that the sequence of sample maxima conditioned on the maximum being finite is stochastically compact.We show that the Markov chain recording the total number of customers in a Kelly–Whittle network is a birth–death process with birth and death rates determined by the normalising constants in a suitably defined sequence of closed networks. Explicit or asymptotic expressions for these normalising constants allow asymptotic evaluation of the birth and death rates, which, in turn, allows characterisation of the cycle maximum in a single busy cycle, and convergence of the sequence of sample maxima for Kelly–Whittle networks of queues.     

Limit distribution of the sum and maximum from multivariate Gaussian sequences

In this paper we study the asymptotic joint behavior of the maximum and the partial sum of a multivariate Gaussian sequence. The multivariate maximum is defined to be the coordinatewise maximum. Results extend univariate results of McCormick and Qi. We show that, under regularity conditions, if the maximum has a limiting distribution it is asymptotically independent of the partial sum. We also prove that the maximum of a stationary sequence, when normalized in a special sense which includes subtracting the sample mean, is asymptotically independent of the partial sum (again, under regularity conditions). The limiting distributions are also obtained.     

An Approximate Distribution for the Maximum Order Complexity

In this paper we give an approximate probability distribution for the maximum order complexity of a random binary sequence. This enables the development of statistical tests based on maximum order complexity for the testing of a binary sequence generator. These tests are analogous to those based on linear complexity.     

一种改进的混沌序列产生方法

根据灰度图像的二维直方图的特点,在已有的二维Arnold混沌系统的基础上,结合Bernstein形式的Bézier曲线的生成算法,给出了一种基于生成Bézier曲线的de Casteljau算法构造伪随机序列的方法,实验结果表明生成的二维序列不仅具有伪随机性,而且还具有在近似圆盘中随机分布的性质,这使得该伪随机序列更适合对灰度图像的二维灰度直方图进行基于混沌优化的图像分割.在此基础上,给出了一种基于混沌优化的二维最大熵的灰度图像分割算法,该算法对于含噪图像取得了良好的分割效果.     

The exact condition of the B-spline basis may be hard to determine

The author's conjecture concerning the knot sequence whose associated B-spline sequence has maximum max-norm condition number is disproved. Related condition numbers are explored and the corresponding conjecture concerning the “worst” knot sequence for them is further supported by numerical results.     

Maximum principle for optimal control problems involving impulse controls with nonsmooth data

This paper is concerned with the stochastic maximum principle for impulse optimal control problems of forward–backward systems, where the coefficients of the forward part are Lipschitz continuous. The domain of the regular controls is not necessarily convex. We establish a Pontryagins maximum principle for this control problem by applying Ekelands variational principle to a sequence of approximated control problems with smooth coefficients of the initial problems.     

Parametric estimation of discretely sampled Gamma-OU processes

The stationary Gamma-OU processes are recommended to be the volatility of the financial assets. A parametric estimation for the Gamma-OU processes based on the discrete observations is considered in this paper. The estimator of an intensity parameter A and its convergence result are given, and the simulations show that the estimation is quite accurate. Assuming that the parameter A is estimated, the maximum likelihood estimation of shape parameter c and scale parameter a, whose likelihood function is not explicitly computable, is considered. By means of the Gaver-Stehfest algorithm, we construct an explicit sequence of approximations to the likelihood function and show that it converges the true (but unkown) one. Maximizing the sequence results in an estimator that converges to the true maximum likelihood estimator and the approximation shares the asymptotic properties of the true maximum likelihood estimator. Some simulation experiments reveal that this method is still quite accurate in most of rational situations for the background of volatility.     

带强制工期的双机开放车间排序问题

讨论了强制工期相等的n个工件在双机开放车间加工.在允许机器空闲的条件下,寻找一个工件排序,使得最大提前完工时间最小.由于工件不允许延迟,同题可能会无可行排序.先讨论了问题的可行性.如果问题可行,找出一个可行序列作为预排序列,并提出了一个算法计算每个工件尽可能迟的开工时间.而后,提出了一个多项式时间最优算法,在预排序列的基础上,通过调整两台机器上最先加工的工件来获得最优排序.     

Advances in aliquot sequences

In this paper we describe some advances in the knowledge of the behavior of aliquot sequences starting with a number less than . For some starting values, it is shown for the first time that the sequence terminates. The current record for the maximum of a terminating sequence is located in the one starting at 4170; it converges to 1 after 869 iterations getting a maximum of 84 decimal digits at iteration 289.