非线性递归数列的极限

探讨了形如Fn+p=pΣ1=1α1Fbin+i,≥1的非线性递归数列{Fn)的极限问题,给出了在满足一定条件时,数列{Fn}极限存在且与初始值无关.     

利用Fibonacci数列解题

Fibonacci数列本身就有很大的魅力 ,吸引着许多数学爱好者去学习和研究 .这里我们将视角定位在如何利用该数列去解决一些数学竞赛中的问题 .Fibonacci数列是指由下面的递推式定义的数列 {Fn}:F0 =F1 =1,Fn + 2 =Fn+ 1 +Fn ,n =0 ,1,2 ,…可以利用特征方程的方法求出其通项公式 ,也可以用数学归纳法证出其许许多多的性质 .但在这里我们更多的是用到其本身 ,而不是它的性质 .例 1(第 5 2届波兰数学竞赛试题 )　考虑数列 {xn}:x1 =a ,x2 =b ,xn + 2 =xn + 1 +xn,n =1,2 ,… ,这里a ,b∈R .对任意c∈R ,如果存在k ,l∈N ,k≠l ,使得xk =xl=…     

我为高考设计题目

题83已知数列{an}为等差数列,数列{bn}为等比数列.(1)若a1+a2+a3=-12,b1·b2·b3=27,且a1+b1,a2+b2,a3+b3是各项均为正整数的等比数列的前3项,求数列{an},{bn}的通项;     

依概率收敛与依分布收敛的关系

本探讨了随机变量序列依概率收敛与依分布收敛的关系,并给出了一个依分布收敛能保证依概率收敛的最弱的条件,即：设分布函数列{Fn（x）}弱收敛于连续的分布函数F(x),则存在随机变量序列{ξn}和随机变量ξ,它们分别以{Fn（x）}和F（x）为其对应的分布函数和分面函数,且{ξn}依概率收敛于ξ。     

放缩的方法探究

<正>考题(2014年新课标全国卷Ⅱ第17题)已知数列{an}满足a1=1,an+1=3an+1.(1)证明:{an+1/2}是等比数列,并求{an}的通项公式;(2)证明:1/a1+1/a2+...+1/an<3/2.不难证得(1)数列{an+1/2}是以3/2为首项,     

依概率收敛与依分布收敛的关系

本文探讨了随机变量序列依概率收敛与依分布收敛的关系 ,并给出了一个依分布收敛能保证依概率收敛的最弱的条件 ,即 :设分布函数列 { Fn(x) }弱收敛于连续的分布函数 F(x) ,则存在随机变量序列{ξn}和随机变量ξ,它们分别以 { Fn(x) }和 F(x)为其对应的分布函数列和分布函数 ,且 {ξn}依概率收敛于ξ.     

正Fibonacci数的标准分解式中因子2的指数

Fibonacci数列 {Fn}定义如下 :F0 =0 ,F1 =1,Fn + 1 =Fn +Fn -1 (n =1,2 ,… ) ,我们把 {Fn}中每一项Fn 叫做一个Fibonacci数 ,当n≥ 1时 ,称Fn 为正Fibonacci数 .关于正Fibonacci数的奇偶性及其中偶Fibonacci数中因子 2的指数 ,笔者在文 [1]中已有部分结果 (见下文中引理 1) ,即正Fibonacci数Fn 的奇偶性 ,由其下标n是否含因子 3来确定 ,且当n是一个奇数的 3倍时 ,Fn 的标准分解式中 ,因子 2的指数确定为1.本文所做的工作 ,是利用同余的知识 ,对于n是一个正偶数的 3倍时 ,Fn 的标准分解式中因子 2的指数给出一个准确的结果 .定理 1…     

Fibonacci数的一组整除特征

Fibonacci数列 {Fn}定义如下 :F0 =0 ,F1=1 ,Fn +1=Fn+Fn - 1(n =1 ,2 ,… ,) ,我们把{Fn}中每一项Fn 叫做一个Fibonacci数 .本文将讨论Fibonacci数Fn 被某些整数整除的特征 .在其证明过程中所用到的关于整除、最大公约数、最小公倍数以及同余的一些简单性质 ,恕不一一列作引理 .此外 ,证明过程中还用到下列数据 :F0 =0 ,F1=1 ,F3=2 ,F4 =3,F5=5,F9=34,F10 =55,F15=6 1 0 ,F16 =987,F2 7=1 96 41 8,F2 8=31 781 1 ,等等 ,这些数据 ,都不难利用Fibonacci数列的定义直接计算得到 .以下的引理是后面定理的证明过程所必须的 .引理 1 […     

广义Fibonacci序列的有限和

通过定义广义的Fibonacci序列{Hn,m}:Hn,m=p1Hn-1,m+p2Hn-2,m+…+pmHn-m,m,其中H1,m=a1,H2,m=a2,…,Hm,m=am,n≥m+1,m 2.给出了序列{Hn,m}一些有限和Un,m=∑ni=1Hi,m、U′n,m=∑ni=1(-1)iHi,m、Vn,m=∑ni=1iHi,m、Vn′,m=∑ni=1(-1)iiHi,m的计算公式.     

我为高考设计题目

题93在数列{an}中,a1=1,且对任意的k∈N*,a2k-1,a2k,a2k+1成等比数列,其公比为qk.(1)若qk=2(k∈N*),求a1+a3+a5+…+a2k-1.(2)若对任意的k∈N*,a2k,a2k+1,a2k+2成等差数列,其公差为dk,设bk=1/qk-1.①求证:{bn}成等差数列,并指出其公差;②若d1=2,试求数列{dk}的前k项和Dk.     

Two General Extension Theorems

Suppose {Mn} is a sequence of pairwise disjoint, nowhere dense closed subsets of [0, 1] and {Fn} is a sequence of continuous functions. We show that there exists a continuous function F which has the same derivate structure as Fn at each point of Mn. In addition, F can be made BV if n=1 V(Fn, Mn), the sum of the variation of Fn|Mn, is finite. A well-known and very useful theorem of Laczkovich and Petruska as well as many classical examples follow readily from our results.     

集值终上鞅的一个收敛定理

it In this paper, the properties of set-valued Eventual Supermartingle are dis-cussed. The main result is that suppose {Fn, n≥1} L1fc(X) be set-valued Eventual Supermaxtingle, if sup E(d(0, Fr)) < ∞, then Fn→F and S1F≠Φ, here T is the sets of all bounded stopping times.     

渐近非扩张非自映射的收敛定理(英文)

设E是实的一致凸Banach空间,K是E的一个非空闭凸集,P是E到K上的非扩张的保核收缩映射.设T1,T2,T3:K→E分别是具有数列{hn},{ln},{kn}[1,∞)的渐近非扩张非自映射,使得sum (hn-1) from n=1 to ∞<∞,sum ((ln-1)) from n=1 to ∞<∞及sum (n=1(kn-1) from n=1 to ∞<∞,且F=F(T1)∩F(T2)∩F(T3)={x∈K:T1x=T2x=T3x}≠Ф.定义迭代序列{xn}:x1∈K,xn+1=P((1-αn)xn+αnT1(PT1)n-1yn),yn=P((1-βn)xn+βnT2(PT2)n-1zn),zn=P((1-γn)xn+γnT3(PT3)n-1xn),其中{αn},{βn},{γn}[ε,1-ε],ε是大于零的实数.(i)如果T1,T2,T3中有一个是全连续的或者半紧的,则{xn}强收敛于某一点q∈F;(ii)如果E具有Frechet可微范数或者满足Opial’s条件或者E的对偶空间E~*具有Kadec-Klee性质,则{xn}弱收敛于某一点q∈F.     

一类马尔可夫序列最大值的极限律

主要研究一类马尔可夫序列{Xn,n≥0}的最大值的极限分布.导出了这类序列最大值和最小值的分布表达式,利用经典极值理论,建立了规范化最大值max{X0,X1,…,Xn}与i.i.d序列{ξn,n≥1}的规范化最大值max{1ξ,2ξ,…,ξn+1}具有相同极限律的条件.     

A critical case of stability of one quasilinear difference equation of the second order

We obtain sufficient conditions for the Perron stability of the trivial solution of a real difference equation of the form

An Inertial Proximal Algorithm with Dry Friction: Finite Convergence Results

Let H be a Hilbert space and A, B: H ⇉ H two maximal monotone operators. In this paper, we investigate the properties of the following proximal type algorithm:

Limit theorems for the maximum likelihood estimate under general multiply Type II censoring

Assume n items are put on a life-time test, however for various reasons we have only observed the r ₁-th,..., r _k-th failure times % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXafv3ySLgzGmvETj2BSbqefm0B1jxALjhiov2D% aebbfv3ySLgzGueE0jxyaibaiiYdd9qrFfea0dXdf9vqai-hEir8Ve% ea0de9qq-hbrpepeea0db9q8as0-LqLs-Jirpepeea0-as0Fb9pgea% 0lrP0xe9Fve9Fve9qapdbaqaaeGacaGaaiaabeqaamaabaabcaGcba% GaamiEamaaBaaaleaamiaadkhadaWgaaqaaSGaaGymaiaacYcaaWqa% baGaamOBaiaacYcacaGGUaGaaiOlaiaac6caaSqabaGccaGGSaGaam% iEamaaBaaaleaamiaadkhadaWgaaqaaSGaam4AaiaacYcaaWqabaGa% amOBaaWcbeaaaaa!48BB!\[x_{r_{1,} n,...} ,x_{r_{k,} n} \]with % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXafv3ySLgzGmvETj2BSbqefm0B1jxALjhiov2D% aebbfv3ySLgzGueE0jxyaibaiiYdd9qrFfea0dXdf9vqai-hEir8Ve% ea0de9qq-hbrpepeea0db9q8as0-LqLs-Jirpepeea0-as0Fb9pgea% 0lrP0xe9Fve9Fve9qapdbaqaaeGacaGaaiaabeqaamaabaabcaGcba% GaaGimaiabgsMiJkaadIhadaWgaaWcbaadcaWGYbWaaSbaaeaaliaa% igdacaGGSaaameqaaiaad6gaaSqabaGccqGHKjYOcqWIVlctcqGHKj% YOcaWG4bWaaSbaaSqaaWGaamOCamaaBaaabaWccaWGRbGaaiilaaad% beaacaWGUbaaleqaaeXatLxBI9gBaGqbaOGae8hpaWJaeyOhIukaaa!521B!\[0 \le x_{r_{1,} n} \le \cdots \le x_{r_{k,} n} > \infty \]. This is a multiply Type II censored sample. A special case where each x _ri ,n goes to a particular percentile of the population has been studied by various authors. But for the general situation where the number of gaps as well as the number of unobserved values in some gaps goes to , the asymptotic properties of MLE are still not clear. In this paper, we derive the conditions under which the maximum likelihood estimate of is consistent, asymptotically normal and efficient. As examples, we show that Weibull distribution, Gamma and Logistic distributions all satisfy these conditions.This research was supported in part by the Designated Research Initiative Fund, University of Maryland Baltimore County.     

Deriving calculus with cotriples

We construct a Taylor tower for functors from pointed categories to abelian categories via cotriples associated to cross effect functors. The tower was inspired by Goodwillie's Taylor tower for functors of spaces, and is related to Dold and Puppe's stable derived functors and Mac Lane's -construction. We study the layers, , and the limit of the tower. For the latter we determine a condition on the cross effects that guarantees convergence. We define differentials for functors, and establish chain and product rules for them. We conclude by studying exponential functors in this setting and describing their Taylor towers.