一种有效计算离散Gabor展开的方法(英文)

定义了一种有限和无限序列的实数形式离散Ｇａｂｏｒ展开方式,这种展开方式使用了类似于广泛应用的复数形式Ｇａｂｏｒ展开方式。但前者由于仅涉及实数运算,结果不仅节省大量的运算,而且更便于硬件和软件的实现。另外,实数形式离散Ｇａｂｏｒ展开方式与复数形式离散Ｇａｂｏｒ展开方式有着非常简单的关系,所以前者可以取代后者的运算。     

直接消耗系数的组合更新法研究

 本文提出了一种更新直接消耗系数的新方法,即将修正RAS法与修正交叉熵法的更新结果进行平均的组合更新法。因为电力数据具有相对准确与及时的特点,所以本文首先提出了结合电力数据的修正RAS法与修正交叉熵法,在此基础上建立了组合更新法的数学模型,然后分别以三个实验比较了修正RAS法、修正交叉熵法以及组合更新法的效果。结果表明本组合更新法的更新精度比前两种方法都高,它是一种合理有效的更新方法。     

用矩阵的行、列初等变换同时解S个线性方程组

求解S个具有相同系数矩阵的线性方程组是线性代数常见的问题.本文提出用矩阵的行、列初等变换同时求解S个线性方程组的新方法,并讨论它的应用。     

平均单叶函数相邻两系数模之差

将胡克所得的关于单叶函数相邻系数模之差的定理B推广到了平均单叶函数族M_5,得到结论:f(z)=z+sum from n=2 to ∞a_nz~n∈Ms,则||a_n|-|a_n+1||≤2~(3/2)e~(1-c/2)(n=2,3,…),其中.为尤拉常数.     

Confidence Interval Estimation in Ultrastructural Model

The present article proposes a methodology to construct confidence interval for slope parameter and joint confidence region for intercept term and slope parameter in an ultra-structural model with equation error and correlated measurement errors.     

Additive time-dependent hazard model with doubly truncated data

For doubly truncated data, i.e. the variables of interest are only observable if they lie in a certain random interval, an additive hazard model with time-dependent regression coefficients is investigated. Consistency and asymptotic normality are proven under mild assumptions. A simulation study investigates the finite sample properties and the influence of the truncation distribution on the estimation error. Finally, the method is applied to a doubly truncated data set of German companies, where the age at insolvency is of interest.     

Designs for large degree polynomial regression

Limiting designs are considered for estimating the individual coefficients in a large degree polynomial regression.     

Multivariate Saddlepoint test for the wrapped normal model

In this article we show the effectiveness and the accuracy of the test statistic based on the expnnent of the saddlepoint approximation for the density of M-estimators, proposed by Robinson, Ronchetti and Young (1999), for testing simultaneous hypotheses on the mean and on the variance of a wrapped normal distribution. We base this test statistic on the trigonometric method of moments estimator proposed by Gatto and Jammalamadaka (l999b), which admits the M-estimator representation necessary for this test. This test statistic has an approximate chi-squared distribution, asympiotically up to the second order, and the high accuracy of this approximation is shown by numerical simulations.     

Tests on the Equality of Two Multiple Correlation Coefficients

Asymptotic tests are suggested for testing the equality of two multiple correlation coefficients calculated from a single sample from a multivariate normal distribution. An F test is possible only when the two dependent variables coincide and one set of independent variables is a subset of the second set. Tests are compared by simulation for situations in which the F test is inapplicable. Special attention is paid to cases in which asymptotic normality of the test statistics does not hold.     

Asymptotic behavior of RA-estimates in autoregressive 2D processes

In this work we study the asymptotic behavior of a robust class of estimators of the coefficient of a AR-2D process. We establish the precise conditions for the consistency and asymptotic normality of the RA estimator. The AR-2D model has many applications in image modeling and statistical image processing, therefore the relevance of knowing such properties. The adequacy of the AR-2D model is analyzed with real images; we also show the impact of contamination and the capability of the RA estimator to produce useful results even in the presence of spurious data.