CONVERGENCE PROPERTIES OF THE DEPENDENT PRP CONJUGATE GRADIENT METHODS

In this paper, a new region of βk with respect to ;βk^PRP is given. With two Armijo-type line searches, the authors investigate the global convergence properties of the dependent PRP conjugate gradient methods, which extend the global convergence results of PRP conjugate gradient method proved by Grippo and Lucidi （1997） and Dai and Yuan （2002）.     

The limit theorem for dependent random variables with applications to autoregression models

This paper studies the autoregression models of order one, in a general time series setting that allows for weakly dependent innovations. Let {X _t } be a linear process defined by X _t = Σ _k=0^∞ψ _k ɛ _t−k , where {ψ _k , k ≥ 0} is a sequence of real numbers and {ɛ _k , k = 0, ±1, ±2, …} is a sequence of random variables. Two results are proved in this paper. In the first result, assuming that {ɛ _k , k ≥ 1} is a sequence of asymptotically linear negative quadrant dependent (ALNQD) random variables, the authors find the limiting distributions of the least squares estimator and the associated regression t statistic. It is interesting that the limiting distributions are similar to the one found in earlier work under the assumption of i.i.d. innovations. In the second result the authors prove that the least squares estimator is not a strong consistency estimator of the autoregressive parameter α when {ɛ _k , k ≥ 1} is a sequence of negatively associated (NA) random variables, and ψ ₀ = 1, ψ _k = 0, k ≥ 1.     

Solutions for singular p-Laplacian equation in R n

In this paper, the authors study the existence and non-existence of positive solutions for singular p-Laplacian equation −∆ _p u = f(x)u ^−α + λg(x)u ^β in R ^N ; where N ≥ 3, 1 < p < N, λ > 0, 0 < α < 1, max(p, 2) < β + 1 < p* = \fracN_pN - p \frac{{{N_p}}}{{N - p}} . We prove that there exists a critical value ¤ such that the problem has at least two solutions if 0 < λ < Λ; at least one solution if λ = Λ; and no solutions if λ > Λ.     

Random evolving networks under the diameter and average connectivity constraint

In this paper, under the constraint that the average distance and the average degree （k） remain approximately constant, we studied a random scale-free network model. We found that, if the network maintains the form of its degree distribution and the maximal degree kc is N-dependent cutoff function kc（N）〈 N, the degree distribution would be approximately power-law with an exponent between 2 and 3. The distribution exponent has little relationship with the average degree, denoted by （k）. The diameter constraint can be interpreted as an environmental selection pressure, which could explain the scale-free nature of networks. The numerical results indicate that, under the diameter constraint, the preferential attachment can produce the cutoff function kc（N）〈 N and power-law degree distribution.     

Asymptotic normality of wavelet estimator in heteroscedastic model with <Emphasis Type="Italic">α</Emphasis>-mixing errors

Consider heteroscedastic regression model Y _ni = g(x _ni ) + σ _ni ɛ _ni (1 ≤ i ≤ n), where σ _ni ² = f(u _ni ), the design points (x _ni , u _ni ) are known and nonrandom, g(·) and f(·) are unknown functions defined on closed interval [0, 1], and the random errors {ɛ _ni , 1 ≤ i ≤ n} are assumed to have the same distribution as {ξ _i , 1 ≤ i ≤ n}, which is a stationary and α-mixing time series with Eξ _i = 0. Under appropriate conditions, we study asymptotic normality of wavelet estimators of g(·) and f(·). Finite sample behavior of the estimators is investigated via simulations, too.     

Construction and comparisons of simultaneous confidence intervals for the mean difference of multivariate normal distributions

<正> In this paper,Scheffé and Simplified Scheffé simultaneous confidence intervals are firstconstructed for mean difference of several multivariate normal distributions.Then the authors theoreticallyprove that when there are only two populations,Bonferroni bounds and Simplified Scheffébounds are the same and they are shorter than Scheffé bounds for p10.In the case for 3k10and 2p10,there exists n(p,k)such that Bonferroni method is better than Simplified Schefféprocedure for nn(p,k),otherwise Simplified Scheffé procedure is better.Finally,the authors findout that neither of Scheffé critical values nor Simplified Scheffé critical values are always larger thananother through numerical calculation.     

SEMI ON-LINE SCHEDULING PROBLEM FOR MAXIMIZING THE MINIMUM MACHINE COMPLETION TIME ON TWO UNIFORM MACHINES

Ia this paper, we consider a semi on-line version on two uniform machines Mi, i = 1, 2, where the processing time of the largest job is known in advance. A speed si（s1 = 1, 1 ≤s2 = s） is associated with machine Mi. Our goal is to maximize the Cmin. We give a Cmin 2 algorithm and prove its competitive ratio is at most 2s＋1/s＋1 We also claim the Cmin 2 algorithm is tight and the gap between the competitive ratio of Cmin2 algorithm and the optimal value is not greater than 0.555. It is obvious that our result coincides with that given by He for s =1.     

Asymptotic limits and stabilization for the 1D nonlinear Mindlin-Timoshenko system

<正> This paper shows how the so called von Karman model can be obtained as a singular limitof a modified Mindlin-Timoshenko system when the modulus of elasticity in shear k tends to infinity,provided a regularizing term through a fourth order dispersive operator is added.Introducing dampingmechanisms,the authors also show that the energy of solutions for this modified Mindlin-Timoshenkosystem decays exponentially,uniformly with respect to the parameter k.As k→∞,the authors obtainthe damped von Karman model with associated energy exponentially decaying to zero as well.     

Confidence intervals for nonparametric regression functions with missing data: Multiple design case

This paper considers two estimators of θ = g (x) in a nonparametric regression model Y = g (x) + ɛ (x ∈ (0, 1) ^p ) with missing responses: Imputation and inverse probability weighted estimators. Asymptotic normality of the two estimators is established, which is used to construct normal approximation based confidence intervals on θ.     

A general iterative method of fixed points for equilibrium problems and optimization problems

The purpose of this paper is to present a general iterative scheme as below:

High accuracy analysis of tensor-product linear pentahedral finite elements for variable coefficient elliptic equations

For a general second-order variable coefficient elliptic boundary value problem in three dimensions,the authors derive the weak estimate of the first type for tensor-product linear pentahedral finite elements.In addition,the estimate for the W^1,1 -seminorm of the discrete derivative Green’s function is given.Finally,the authors show that the derivatives of the finite element solution u_h and the corresponding interpolantΠ_u are superclose in the pointwise sense of the L^∞-norm.     

Discriminant analysis based on statistical depth

<正> In the past two decades,many statistical depth functions seemed as powerful exploratoryand inferential tools for multivariate data analysis have been presented.In this paper,a new depthfunction family that meets four properties mentioned in Zuo and Serfling(2000)is proposed.Then aclassification rule based on the depth function family is proposed.The classification parameter b couldbe modified according to the type-Ⅰ error α,and the estimator of b has the consistency and achievesthe convergence rate n~(-1/2).With the help of the proper selection for depth family parameter c,theapproach for discriminant analysis could minimize the type-Ⅱ error β.A simulation study and a realdata example compare the performance of the different discriminant methods.     

An SEIRS epidemic model with two delays and pulse vaccination*

Pulse vaccination is an effective and important strategy to eradicate an infectious disease. The authors investigate an SEIRS epidemic model with two delays and pulse vaccination. By using the discrete dynamical system determined by stroboscopic map, the authors obtain that the infectious population dies out if R△ 〈 1, and the infectious population is uniformly persistent if R^△ 〉 1. The results indicate that a short period of pulse vaccination or a large pulse vaccination rate is a sufficient condition to eradicate the disease.     

Inverse Center Location Problem on a Tree

This paper discusses the inverse center location problem restricted on a tree with different costs and bound constraints. The authors first show that the problem can be formulated as a series of combinatorial linear programs, then an O（｜V｜^2 log ｜V｜） time algorithm to solve the problem is presented. For the equal cost case, the authors further give an O（｜V｜） time algorithm.     

Induced Subgraph in Random Regular Graph

Let Gn,d be a random d-regular graph with n vertices, where d = o（n）. Given a fixed graph H, YH denotes the number of induced copies of H in Gn d In this paper, the authors determine the threshold of the event ＂YH 〉 0＂, and also obtain the induced subgraph counts inside the threshold interval.     

Global stability of endemic equilibrium point of basic virus infection model with application to HBV infection

In this paper, the authors first show that if R ₀ ≤ 1, the infection free steady state is globally attractive by using approaches different from those given by Min, et al.(2008). Then the authors prove that if R ₀ > 1, the endemic steady state is also globally attractive. Finally, based on a patient’s clinical HBV DNA data of anti-HBV infection with drug lamivudine, the authors establish an ABVIM. The numerical simulations of the ABVIM are good in agreement with the clinical data.     

A NEW FAMILY OF TRIVALENT CAYLEY NETWORKS ON WREATH PRODUCT Zm ～ Sn

We propose a new family of interconnection networks （WGn^m） with regular degree three. When the generator set is chosen properly, they are isomorphic to Cayley graphs on the wreath product Zm ～ Sn. In the case of m ≥ 3 and n ≥3, we investigate their different algebraic properties and give a routing algorithm with the diameter upper bounded by [m/2]（3n^2- 8n ＋ 4） - 2n ＋ 1. The connectivity and the optimal fault tolerance of the proposed networks are also derived. In conclusion, we present comparisons of some familiar networks with constant degree 3.     

Towards a theory of game-based non-equilibrium control systems

This paper considers optimization problems for a new kind of control systems based on non-equilibrium dynamic games.To be precise,the authors consider the infinitely repeated games between a human and a machine based on the generic 2×2 game with fixed machine strategy of finite k-step memory.By introducing and analyzing the state transfer graphes(STG),it will be shown that the system state will become periodic after finite steps under the optimal strategy that maximizes the human’s averaged payoff,which helps us to ease the task of finding the optimal strategy considerably. Moreover,the question whether the optimizer will win or lose is investigated and some interesting phenomena are found,e.g.,for the standard Prisoner’s Dilemma game,the human will not lose to the machine while optimizing her own averaged payoff when k = 1;however,when k≥2,she may indeed lose if she focuses on optimizing her own payoff only The robustness of the optimal strategy and identification problem are also considered.It appears that both the framework and the results are beyond those in the classical control theory and the traditional game theory.     

Testing <Emphasis Type="Italic">k</Emphasis>-edge-connectivity of digraphs

This paper presents an algorithm that tests whether a given degree-bounded digraph is k-edge-connected or ɛ-far from k-edge-connectivity. This is the first testing algorithm for k-edgeconnectivity of digraphs whose running time is independent of the number of vertices and edges. A digraph of n vertices with degree bound d is ɛ-far from k-edge-connectivity if at least ɛdn edges have to be added or deleted to make the digraph k-edge-connected, preserving the degree bound. Given a constant error parameter ɛ and a degree bound d, our algorithm always accepts all k-edge-connected digraphs and rejects all digraphs that is ɛ-far from k-edge-connectivity with probability at least 2/3. It runs in $ O\left( {d\left( {\frac{c} {{\varepsilon d}}} \right)^k log\frac{1} {{\varepsilon d}}O} \right) $ O\left( {d\left( {\frac{c} {{\varepsilon d}}} \right)^k log\frac{1} {{\varepsilon d}}O} \right) (c > 1 is a constant) time when input digraphs are restricted to be (k-1)-edge connected and runs in $ O\left( {d\left( {\frac{{ck}} {{\varepsilon d}}} \right)^k log\frac{k} {{\varepsilon d}}O} \right) $ O\left( {d\left( {\frac{{ck}} {{\varepsilon d}}} \right)^k log\frac{k} {{\varepsilon d}}O} \right) (c > 1 is a constant) time for general digraphs.