时滞差分系统基于两种度量的稳定性分析

本文建立了一些关于时滞差分系统（h0,h）稳定性（一致稳定性，渐近稳定性，一致渐近稳定性）的判定准则。在所得到的定理中，去除了△V为常负的限制，特别地，△V甚至可以恒为正，从而大大改进了已有结果，并更加便于应用。     

Asymptotic behaviors of competitive Lotka-Volterra system with stage structure

In this paper, a two-species competitive model with stage structure is presented and studied. Results on the global extinction and permanence are given, which generalize the well-known three theorems for the two species competitive system and, moreover, they confirm the negative effect of stage structure on the permanence of populations as well as estimate the degree of such effect. Conclusions in this paper suggest that for a competitive community stage structure is also one of the important reasons that cause permanence and extinction.     

一种检验定性指标的有效方法

介绍了一种检验定性指标的有效方法,可用于确定产品的合格率和评价检验人员的检验水平。用该方法分析了某厂产品的一项实际指标,合格率为91 4%,还对该厂10名检验员的检验水平作了客观的评价。     

PERSISTENCE AND GLOBAL STABILITY FOR TWO-SPECIES NONAUTONOMOUS PREDATOR-PREY SYSTEM WITH DIFFUSION AND TIME DELAY

In this paper, a non-autonomous predator-prey model with diffusion andcontinuous time delay is studied, where the prey can diffuse between two pat-ches of a heterogeneous environment with barriers between patches, but for thepredator, the diffusion does not involve a barrier between patches, further itis assumed that all the parameters are time-dependent. It is shown that thesystem can be made persistent under some appropriate conditions. Moreover,sufficient conditions that guarantee the existence of a unique periodic solutionwhich is globally asymptotic stable are derived.     

青岛港货运吞吐量的时间序列模型

运用时间序列分析方法对时间序列建立ARMA,ARIMA模型.搜集了青岛港1999年1月～2003年5月的货运吞吐量数据,对进行分析,建立了青岛港货运吞吐量的模型.通过预留的部分数据对模型进行检验,并对模型的残差进行检验,得出模型比较合理.     

最大似然方法和Bayes方法在结构方程模型分析中的讨论(英文)

本文通过模拟研究,讨论了最大似然方法和Bayes方法在分析结构方程模型中的相似点和不同之处。     

ULTIMATE BOUNDEDNESS FOR A DIFFERENTIAL DELAY MODEL

This paper considers the scalar differential delay equation x(t) = -μx(t)-f(x(t-Τ(t)), t). By using the mapping method we obtain that the solutionswill be ultimately in some interval.     

加热炉热过程动态操作数学模型

根据加热炉生产特点,建立了钢坯加热过程的动态操作数学模型,分析了待轧时间变化时炉内钢坯温度分布情况。并针对加热炉待轧的灰色性,采用多目标灰色局势决策方法,得出了相应合理的待轧优化控制策略。模拟结果表明:该方法具有良好的动态性能,适合于在线控制。     

A new algorithm for fixed design regression and denoising

In this paper, we present a new algorithm to estimate a regression function in a fixed design regression model, by piecewise (standard and trigonometric) polynomials computed with an automatic choice of the knots of the subdivision and of the degrees of the polynomials on each sub-interval. First we give the theoretical background underlying the method: the theoretical performances of our penalized least-squares estimator are based on non-asymptotic evaluations of a mean-square type risk. Then we explain how the algorithm is built and possibly accelerated (to face the case when the number of observations is great), how the penalty term is chosen and why it contains some constants requiring an empirical calibration. Lastly, a comparison with some well-known or recent wavelet methods is made: this brings out that our algorithm behaves in a very competitive way in term of denoising and of compression.     

Covariance estimation under spatial dependence

Correlated multivariate processes have a dependence structure which must be taken into account when estimating the covariance matrix. The natural estimator of the covariance matrix is introduced and is shown that to be biased under the dependence structure. This bias is studied under two different asymptotic models, namely increasing the domain by increasing the number of observations, and increasing the number of observations in the fixed domain. Using the first asymptotic model, we quantify the convergence rate of the bias and of the covariance between the components of the estimated covariance matrix. The second asymptotic model serves to derive a fast and accurate bias correction. As shown, under mild hypotheses, the asymptotic normality of the estimated covariance matrix holds and can be used to test whether the bias is significant, for example, in the sense that the eigenvectors of the estimated and true covariance matrices are significantly different.