关于线性算子的高阶饱和

设f(x)∈C_(2π)。而f(x)～sum from k=0 ( )A_k(f_1k)≡α_0/2 sum from k=1 ( )(α_kcoskx b_ksinkx)。 又设 U_n(f,x)=1/πintegral from -πto π(f(x t)u_n(t)dt,) 其中u_n(t)=1/2 sum from k=1ρ_k~(n)coskt满足条件: integral from 0 to k(|u_n(t)|dt=O(1),)ρ_k~(n)→1(n→∞;k=1,2,…,)。设m是正整数,ρ_0~(n)=1。记~mρ_k~(n)=sum form v=0 to ∞ ((-1)~(m~(-v))(m v)ρ_k v~(n) (k=0,1,…,)。)T.Nishishiraho考虑了在ρ_k~(n)=O(k>n)的情况下U_n(f,x)的饱和问题,证明了。 定理A 设{_n}是收敛于0的正数列,使得     

退缩椭圆型方程的边值问题

<正> 在 R~n 的有界凸区域Ω上考虑椭圆型方程Lu≡sum from i,j=1 to n (a_(ij)(x)u_(xi)_(xj)+sum from i=1 to n b_i(x)u_i+c(x)u=f(x),(1)设对 x∈(?)及所有的实数组(ξ_1,ξ_2,…,ξ_n)sum from i,j=1 to n a_(ij)(x)ξ_iξ_j≥λ(x)sum from i=1 to n ξ_i~2≥0,a_(ji)(x)∈C(?),即算子 L(u)可能退缩而为退缩椭圆型算子。记(?)的边界为∑,∑上满足 sum from ij=1 to n a_(ij)n_in_j=0的点集为∑_0,(n_1,…,n_n)表示∑上的内单位法向量,∑_3=∑\∑_0,设其 n-1维测度非零,则对方程(1)可提如下的边值问题:     

半线性蜕缩椭圆型方程的Dirichlet问题

设Ω(?)R~n(n≥2)是光滑有界区域.讨论如下的半线性蜕缩椭圆型方程的Dirichlet问题Lu ≡-sum from i,j=1 to n((?)/(?)x_i)(aij(x)((?)u/(?)xj)=g(x,u) (x,u),在Ω中,u=0,在(?)Ω上。(1)这里,且sum from i,j=1 to n(aijξiξj≥k sum from i=1 to n(ρ~a_i(x)ξ_i~2),(?)x∈(?),(?)ξ∈R~n,(2)     

含有n个滞量的三维微分差分方程组周期解的存在性

本文研究含有n 个滞量的三维微分差分方程组x(t)=sum from i=1 to ∞(1/i)f[x(t),x(t-τ_i),y(t),y(t-τ_i),z(t),z(t-τ_i)]y(t)=sum from i=1 to ∞(1/i)g[x(t),x(t-τ_i),y(t),y(t-τ_i),z(t),z(t-τ_i)](τ_i>0)z(t)=sum from i=1 to ∞(1/i)h[x(t),x(t-τ_i),y(t),y(t-τ_i),z(t),z(t-τ_i)]周期解的存在性,给出了方程组周期解周期的取值范围.推广并改进了文[1]的结果.     

STRONG CONVERGENCE OF KERNEL ESTIMATES OF NONPARAMETRIC REGRESSION FUNCTIONS

Let (X, Y), (X_1, Y_1), …, (X_n, Y_n) be i. i. d. random vectors taking values in R_d×Rwith E(|Y|)<∞. To estimate the regression function m (x) = E (Y|X= x), we use thekernel estimate m_n(x)= sum from i=1 to n K((X_j-x)/h_n) where K(x) is a kernel functionand h_n a window width. In this paper, we establish the strong consistency of m_n(x) whenE(|Y|~P)<∞ for some p>l or E{exp(t|Y|~λ)}<∞ for some λ>0 and t>O. It is remakablethat other conditions imposed here are independent of the distribution of (X, Y).     

Strong Consistency of Non-parametric Regression Estimates with Censored Data

Let (X,Y) be an R~d×R valued random vector with E|Y|<∞ and(X_1,Y_1) (X_2,Y_2), …, (X_n,Y_n) be i.i.d.observations of (X,Y). To estimate the regression function m(x)=E(Y|X=x), Stone suggested m_n(x)=sum from i=1 to n(W_(ni)(x)Y_i), where W_(ni)(x)=W_(ni)(x,X_1,X_2,…,X_n)(i=1,2,…,n) are weight functions. Devroye and Chen Xiru established the strong consistency of m_n(x). In this paper, we discuss the case that{Y_i} are censored by {t_i}, where{t_i} are i.i.d. random variables and also independent of{Y_i}. Under certainconditions we still obtain the strong consistency of m_n(x).     

二次指派问题的一个新的限界方法

二次指派问题(QAP)的数学模型是:min{z(x)=sum from i=1 to n sum from =1 to n a_(ip)x_(ip)+sum from i=1 to n sum from p=1 to n sum from j=1 to n sum from q=1 to n c_(ipjq)x_(ip)x_(jq)|x∈},(1)这里∈(n~2维布尔集)是满足如下约束的集合:sum from i=1 to n x_(ip)=1,1≤p≤n,(2)sum from p=1 to n x_(ip)=1,1≤i≤n,(3)x_(ip)=0,1,1≤i,p≤n.(4)因为 x_(ip)~2=x_(ip)并且有约束(2)和(3),我们可以约定 c_(ipjq)=0,当 i=j 或 p=q.如果所有二次项的系数都可以写成     

一阶中立型微分差分方程解的振动性质

在本文中我们研究中立型微分差分方程d/dt[x(t)+sum from i=1 to m(p_ix(t-τ_i))]+sum from i=1 to n(Q_i(t)x(t-σ_i)=0,t≥t_0的解的振动性态。本文推广[1]的诸结果,同时改进[1]的定理3和定理4。     

Richard模型的平均期望费用问题

设 W_t,t≥0为(Ω,■,P)上标准 Wiener 过程,■为由之所生成的上升 σ-域族,以τ_i,i≥1表任一个(?)单调上升停时列,对每个τ_i 确定一个F_(τi)可测随机变量ξ_i,我们称任一这样的对列 v={(τ_i,ξ_i),i≥1}为一脉冲过程,以 V 表脉冲过程,(以下称脉冲控制)的全体,设 h 和 B 为 R 上满足某些条件的非负实函数,再设σ,μ为任何实常数且|σ|>0.本文求得一个常数λ>0使对任一实数 x 皆有一个十分明确具体的控制 v~*={(τ_i~*,ξ_i~*),i≥1)∈V 满足lim~T→∞(1/T)E[integral from 0 to T h(x+μt+σW_t+sum τ_i~*相似文献   

回归函数递旧核估计相合的充要条件

对α-混合,φ-混合样本,本文给出回归函数递归核估计m_a(x)弱、强相合的充要条件.在E|Y|~(1+δ)<∞,δ>0,sum from n=1 to ∞(φ~1 ~2(n))<∞时.得出m_n(x)的强、弱相合是等价的.另外,还给出核估计m_n(x)弱相合的充分条件。