Banach空间中拟非扩展映象的不动点的迭代逼近

研究了严格凸Banach空间中非空间凸子集上拟非扩展映象的不动点的迭代逼近问题,主要证明了:设E是严格凸Banach空间,K为E的闭凸子集,T:K→K为连续拟非扩展映象。进一步假设T(K)包含于K的一个紧子集之中,迭代地定义序列{xn}∞n=1如下:(IS)yn=(1-βn)xn+βnTxn,n≥1,xn+1=(1-αn)xn+αnTyn,n≥1,其中{αn}和{βn}满足一定的条件,则{xn}强收敛于T的某个不动点。     

关于Reich的公开问题

设E是具有一致G -可微范数的实Banach空间 ,D是E的非空闭凸子集 ,T :D→D是非扩张映象 ,F(T)非空。设 {αn} ,{ βn}是 [0 ,1]中满足一定条件的两个序列 ,定义压缩映象St:D→D为 :St(z) =(1-t)x tTz , x ,z∈D , n≥ 1,t∈ (0 ,1) .设zt 是St 的唯一不动点 ,若当t→ 1-时 ,{zt}强收敛于某点z∈F(T) .那么 ,Reich序列 {xn}强收敛于某点z∈F(T) .     

Banach空间中含Lipschitz强增生 算子的算子方程之构造可解性

设X为实一致光滑Banach空间 ,A :X→X为Lipschitz强增生算子 ,设L≥ 1和k∈( 0 ,1)分别为A的Lipschitz常数与强增生常数。设 {tn}n≥ 0 为 ( 0 ,1]中的实数列满足条件 :(i)tn→ 0 (n→∞ ) ;(ii)∑∞n =0 tn=∞ , f∈X , x0 ∈X ,迭代地定义序列 {xn}n≥ 0如下 :( )　　xn 1 =xn-tn(Axn- f) ,n≥ 0 .则 {xn}n≥ 0 强收敛于方程Ax =f的唯一解 ,而且对充分大的n≥n0 ,‖Axn- f‖ ≤ exp{-k∑n- 1j=n0tj}‖Axn0 - f‖　　一个相关的结果研究含强伪压缩映象的方程Tx =x的构造可解性。     

集值拟终下鞅的收敛性与Riesz分解

本文在X^＊可分的条件下证明了集值拟终下鞅在弱收敛意义下的收敛定理,同时给出了如下集值拟终下鞅的Riesz分解定理：设{Fn,n≥1}包含Lc（X）为集值拟终下鞅,且满足（i）E｜｜Fτ｜｜I（τ〈∞）〈∞,偏dτ∈T,（ii）{｜｜Fn｜｜,n≥1}一致可积,则以下两条等价：（1）{Fn,n≥1}可Riesz分解; （2）Vn≥1,Fn关于E（F｜Bn）（n≥1）位似,其中Fn→w F。     

模糊随机过程的可分性与可测性

本文证明了一个模糊随机过程{_t(ω)t∈T}必存在一个与之等价的可分模糊随机过程{_t(ω)t∈T};且若模糊随机过程{_t(ω)t∈T}随机连续,则它存在等价的,可分且可测的模糊随机过程{■_t(ω)t∈T}。     

关于强增生算子的Mann迭代序列收敛的充要条件

设Z是一致光滑Banach空间,T：X→X是次连续强增生算子,｛an｝、｛βn｝是两个实数列且满足0≤an≤1,及an→0（n→∞）,令Mann迭代序列｛Xn｝定义为证明了迭代序列｛xn｝强收敛于S的不动点q的充要条件是｜｜Txn｜｜有界。     

台海上空的6大“贼眼”——美国对台出售的E-2T型空中预警机

E—2T型预警机 1993年3月,美国政府同意售台4架E—2T型空中预警机,金额9亿美元。同年3月美台签订合约。1995年5月9日,首架E-2T在美国诺斯洛普-格鲁曼公司正式交机,前两架E—2T在1995年9月3日运回台湾。后两架则在9月23日返抵台湾。1995年11月22日,台湾当局煞费苦心向美国订购的4架E—2T型预警机正式服役。1999年7月,台湾当局又获准购买两架E—2T“鹰眼”2000E型预警机。此次美对台军售还包括两部APS—145型雷达、4台T56—A—427型发动机、两套0E—335/A型天线、两套改进型任务计     

母爱无声儿有志

l=G中速深情壮美地 词曲:王武强 (经习l:闯忆五丘11仁T今幼.6一,6.11 4 3 12一17迄}2尽,杯爬一)J 3·泛}6、U}2丛卜心}赎}丝}3及{6~远丝{3一}3·泛}6.U} 夕阳拉长了母亲身影,那是遥望远方游子的造型。小溪流淌着 边关哨卡的平凡岗位,我用责任警醒敏锐的眼睛。科技练兵的 2重}1 21贝巧}3·丘{巡2}1·2叮率{断万咨一}牡迎! 串申乡音,那是母亲牵肠挂肚的叮泞。繁星传递 攻关平台,我用智慧浇注创新的激情。暴风骤雨 3.旦}丘之叠卫}3一}吞二辱址1”足立』}5.丘}3一t东元}1一I 着母亲的眼神,那是为儿指路引航的明灯。大地 的危急关头,…     

一类差分方程的三点边值问题的正解

研究了一类离散型三点边值问题:Δ2y(k-1) a(k)f(k,y(k))=0,k∈N={1,2,…,T},Δy(0)=0,y(T 1)=βy(l),式中:f是变号的,l∈N1={2,3,…,T-1},T∈{3,4,…}。应用双锥上的不动点定理,得到了至少存在两个正解的充分条件,并给出了上述边值问题的Green函数。     

两类特殊广义簇

引进了两类特殊的广义簇:W=UWn,V=UVn,其中 Wn=[xyzt=xzyt,xyn 1=xn 1y=xy],Vn=[xyzt=xzyt,xn 1yn 1=xy],得出了它们的两条良好的性质。     

Inequalities involving the lifetime of series and parallel systems

Let {Xⁱ} be independent HNBUE (Harmonic New Better Than Used in Expectation) random variables and let {Yⁱ} be independent exponential random variables such that E{Xⁱ}=E{Yⁱ} It is shown that \documentclass{article}\pagestyle{empty}\begin{document}$ E\left[{u\left({\mathop {\min \,X_i}\limits_{l \le i \le n}} \right)} \right] \ge E\left[{u\left({\mathop {\min \,Y_i}\limits_{l \le i \le n}} \right)} \right] $\end{document} for all increasing and concave u. This generalizes a result of Kubat. When comparing two series systems with components of equal cost, one with lifetimes {Xⁱ} and the other with lifetimes {Yⁱ}, it is shown that a risk-averse decision-maker will prefer the HNBUE system. Similar results are obtained for parallel systems.     

Gabor框架的稳定性研究

对于Hilbert空间中的Gabor框架,定义A=inf x∈[0,a][∑n∈Z｜f（x-na）｜^2-∑k≠0｜∑n∈Zf（x-na）f^-（x-na-k/b｜]〉0,B=supx∈[0,a]∑n∈Z｜∑n∈Zf（x-naf^-（x-na-k/b）｜〈∞,通过算子放缩证明的方法,可知{Mb^mSa^nf}m,n∈Z构成L^2（R）的框架,且框架界为A/b,B/b.     

The hnbue and hnwue classes of life distributions

Different properties of the HNBUE (HNWUE) class of life distributions (i.e.), for which \documentclass{article}\pagestyle{empty}\begin{document}$\int_t^\infty {\,\,\,\mathop F\limits^-(x)\,dx\, \le \,(\ge)\,\mu }\]$\end{document} exp(?t/μ) for t ≥ 0, where μ = \documentclass{article}\pagestyle{empty}\begin{document}$\int_t^\infty {\,\,\,\mathop F\limits^-(x)\,dx}$\end{document} are presented. For instance we characterize the HNBUE (HNWUE) property by using the Laplace transform and present some bounds on the survival function of a HNBUE (HNWUE) life distribution. We also examine whether the HNBUE (HNWUE) property is preserved under the reliability operations (i) formation of coherent structure, (ii) convolution and (iii) mixture. The class of distributions with the discrete HNBUE (discrete HNWUE) property (i.e.), for which \documentclass{article}\pagestyle{empty}\begin{document}$\sum\limits_{j=k}^\infty {\mathop{\mathop P\limits^-_{j\,\,\,}\, \le(\ge)\,\mu(1 - 1/\mu)^{^k }}\limits^{}} $\end{document} for k = 0, 1, 2, ?, where μ =\documentclass{article}\pagestyle{empty}\begin{document}$\sum\limits_{j=0}^\infty {\mathop {\mathop P\limits^- _{j\,\,\,\,\,}and\mathop P\limits^ - _{j\,\,\,\,\,}=}\limits^{}}\,\,\sum\limits_{k=j+1}^\infty {P_k)}$\end{document} is also studied.     

Computing equilibria via nonconvex programming

The problem of determining a vector that places a system in a state of equilibrium is studied with the aid of mathematical programming. The approach derives from the logical equivalence between the general equilibrium problem and the complementarity problem, the latter being explicitly concerned with finding a point in the set S = {x: < x, g(x)> = 0, g(x) ≦ 0, x ≧ 0}. An associated nonconvex program, min{? < x, g(x) > : g(x) ≦ 0, x ≧ 0}, is proposed whose solution set coincides with S. When the excess demand function g(x) meets certain separability conditions, equilibrium solutions are obtained by using an established branch and bound algorithm. Because the best upper bound is known at the outset, an independent check for convergence can be made at each iteration of the algorithm, thereby greatly increasing its efficiency. A number of examples drawn from economic and network theory are presented in order to demonstrate the computational aspects of the approach. The results appear promising for a wide range of problem sizes and types, with solutions occurring in a relatively small number of iterations.     

Estimating a survival curve when new is better than used with respect to a distinguished set

Hollander, Park, and Proschan define a survival function S of a positive random variable X to be new better than used at age t₀ (NBU-{t₀}) if S satisfies $ \begin{array}{*{20}c} {\frac{{S(x + t_0)}}{{S\left({t_0} \right)}} \le S\left(x \right),} & {{\rm for}\,{\rm all}\,x\, \ge \,0,} \\ \end{array}$ where S(x) = P(X > x). The NBU-{t₀} class is a special case of the NBU-A family of survival distributions, where A is a subset of [0, ∞). These families introduce a variety of modeling possibilities for use in reliability studies. We treat problems of nonparametric estimation of survival functions from these classes by estimators which are themselves members of the classes of interest. For a number of such classes, a recursive estimation technique is shown to produce closed-form estimators which are strongly consistent and converge to the true survival distribution at optimal rates. For other classes, additional assumptions are required to guarantee the consistency of recursive estimators. As an example of the latter case, we demonstrate the consistency of a recursive estimator for S ∈ NBU-[t₀, ∞) based on lifetime data from items surviving a preliminary “burn-in” test. The relative precision of the empirical survival curve and several recursive estimators of S are investigated via simulation; the results provide support for the claim that recursive estimators are superior to the empirical survival curve in restricted nonparametric estimation problems of the type studied here.     

具有正交(g,f)-因子分解的子图

设G是一个图 ,g (x)和f (x)是定义在V (G)上的整数值函数 ,且对任意的x∈V (G) ,设g (x)≤f (x) ,H是G的一个子图 ,F ={F1,F2 ,… ,Ft}是G的一个因子分解 ,如果对任意的 1≤i≤t,|E (H)∩E (Fi) |=1 ,则称F与H正交。闫桂英和潘教峰在文 [3]中提出如下猜想 :设G是一个 (mg+k,mf-k) -图 ,1≤k相似文献   

非平稳高斯序列最大值的几乎处处中心极限定理

在较弱的条件下,研究了一类非平稳高斯序列的几乎处处中心极限定理.设{Xa,n≥1}为一非平稳高斯序列,记其协方差为rij=Cov(Xi,Xj).假设该序列满足如下条件:对充分大的n,若存在0<α<1当|i-j|>nα时,rijlog|j-i|(l0glog|j-i|)1+ε一致有界.在这一条件下,通过利用概率极限理论,...     

Readiness and the optimal redeployment of resources

This paper considers the problem of the optimal redeployment of a resource among different geographical locations. Initially, it is assumed that at each location i, i = 1,…, n, the level of availability of the resource is given by a₁ ≧ 0. At time t > 0, requirements R_f(t) ≧ 0 are imposed on each location which, in general, will differ from the a₁. The resource can be transported from any one location to any other in magnitudes which will depend on t and the distance between these locations. It is assumed that ΣR_j > Σa_t The objective function consideis, in addition to transportation costs incurred by reallocation, the degree to which the resource availabilities after redeployment differ from the requirements. We shall associate the unavailabilities at the locations with the unreadiness of the system and discuss the optimal redeployment in terms of the minimization of the following functional forms: \documentclass{article}\pagestyle{empty}\begin{document}$ \sum\limits_{j = 1}^n {kj(Rj - yj) + } $\end{document} transportation costs, Max \documentclass{article}\pagestyle{empty}\begin{document}$ \mathop {Max}\limits_j \,[kj(Rj - yj)] + $\end{document} transportation costs, and \documentclass{article}\pagestyle{empty}\begin{document}$ \sum\limits_{j = 1}^n {kj(Rj - yj)^2 + } $\end{document} transportation costs. The variables y_j represent the final amount of the resource available at location j. No benefits are assumed to accrue at any location if y_j > R_j. A numerical three location example is given and solved for the linear objective.     

Scheduling data transmission under an {si; o} policy

This paper discusses scheduling of data transmission when data can only be transmitted in one direction at a time. A common policy used is the so-called alternating priority policy. In this paper we select a more general class of policies named the {S_i; O} policy. We show how to determine the optimal parameters of the {S_i; O} policy for given system parameters. We also give a simple example to show that {S_i; O} policy is, in fact, better then alternating priority policy.     

Testing fit with nuisance location and scale parameters

For each n, X₁(n),…, X_n(n) are independent and identically distributed random variables, each with cumulative distribution function F(x) which is known to be absolutely continuous but is otherwise unknown. The problem is to test the hypothesis that \documentclass{article}\pagestyle{empty}\begin{document}$ F(x) = G\left( {{\textstyle{{x - \theta _1 } \over {\theta _2 }}}} \right) $\end{document}, where the cumulative distribution function G_x is completely specified and satisfies certain regularity conditions, and the parameters θ₁, θ₂ are unknown and unspecified, except that the scale parameter θ₂, is positive. Y₁ (n) ≦ Y₂ (n) ≦ … ≦ Y_n (n)are the ordered values of X₁(n),…, X_n(n). A test based on a certain subset of {Y_i(n)} is proposed, is shown to have asymptotically a normal distribution when the hypothesis is true, and is shown to be consistent against all alternatives satisfying a mild regularity condition.