Minimal energy problems for strongly singular Riesz kernels

We study minimal energy problems for strongly singular Riesz kernels ${|\mathbf{x}-\mathbf{y}|}^{\alpha -n}$, where $n\ge 2$ and $\alpha \in (-1,1)$, considered for compact $(n-1)$‐dimensional $C^{\infty }$‐manifolds Γ immersed into ${\mathbb{R}}^n$. Based on the spatial energy of harmonic double layer potentials, we are motivated to formulate the natural regularization of such minimization problems by switching to Hadamard's partie finie integral operator which defines a strongly elliptic pseudodifferential operator of order $\beta =1-\alpha$ on Γ. The measures with finite energy are shown to be elements from the Sobolev space $H^{\beta /2}(\mathrm{\Gamma })$, $0<\beta <2$, and the corresponding minimal energy problem admits a unique solution. We relate our continuous approach also to the discrete one, which has been worked out earlier by D. P. Hardin and E. B. Saff.     

E-inversive semigroups with a completely simple kernel

We show that an E-inversive semigroup S has a completely simple kernel K_S if and only if it contains a primitive idempotent (in that case, K_S is the set-theoretic union of the groups eSe, where e is a primitive idempotent of S). Along the way, some equivalent conditions for a semigroup to be E-inversive are given. Moreover, some applications of the above theorem will be pointed out.     

Large and moderate deviations principles for kernel estimators of the multivariate regression

In this paper, we prove large deviations principle for the Nadaraya-Watson estimator and for the semi-recursive kernel estimator of the regression in the multidimensional case. Under suitable conditions, we show that the rate function is a good rate function. We thus generalize the results already obtained in the one-dimensional case for the Nadaraya-Watson estimator. Moreover, we give a moderate deviations principle for these two estimators. It turns out that the rate function obtained in the moderate deviations principle for the semi-recursive estimator is larger than the one obtained for the Nadaraya-Watson estimator.      

Hilbert-type inequalities with a product-type homogeneous kernel and Schur polynomials

The main objective of this paper is to prove Hilbert-type and Hardy-Hilbert-type inequalities with a product-type homogeneous kernel, thus generalizing a result obtained in [Z. Xie, Z. Zheng, A Hilbert-type integral inequality whose kernel is a homogeneous form of degree −3, J. Math. Anal. Appl. 339 (2008) 324-331]. In some cases the best possible constants obtained in these inequalities are expressed using the Schur polynomials.     

Robust designs for models with possible bias and correlated errors

This paper studies the model-robust design problem for general models with an unknown bias or contamination and the correlated errors. The true response function is assumed to be from a reproducing kernel Hilbert space and the errors are fitted by the qth order moving average process MA（q）, especially the MA（1） errors and the MA（2） errors. In both situations, design criteria are derived in terms of the average expected quadratic loss for the least squares estimation by using a minimax method. A case is studied and the orthogonality of the criteria is proved for this special response. The robustness of the design criteria is discussed through several numerical examples.     

Improvement of the WENO scheme smoothness estimator

This paper has analyzed the weights of the fifth‐order weighted essentially nonoscillatory scheme suggested by Jiang and Shu and a modified smoothness estimator is suggested to improve the accuracy. Using a function of the minimum and maximum of the original smoothness estimators, the new smoothness estimators have smaller variation among them than the original ones in smooth regions. Hence, as the new weights are closer to the optimal weights, the numerical accuracy is improved. Several numerical experiments are presented to demonstrate the accuracy and robustness of the new scheme. Copyright © 2009 John Wiley & Sons, Ltd.     

用再生核表示小波变换

本文研究了调制高斯函数的小波变换．利用再生核函数的特殊技巧，得到了该小波变换的等距恒等式和像空间的结构，同时给出了该小波变换的采样定理．使得小波变换能用再生核函数表示．这为一般的小波变换的像空间的研究提供了理论基础．     

势问题的复变量重构核粒子法

在重构核粒子法的基础上,引入复变量,提出复变量重构核粒子法,在构造形函数时采用一维基函数建立二维问题的修正函数.应用于势问题,具有计算量小、精度高的优点.数值算例证明了方法的有效性.     

On the Reproducing Kernel Hilbert Spaces Associated with the Fractional and Bi-Fractional Brownian Motions

We present decompositions of various positive kernels as integrals or sums of positive kernels. Within this framework we study the reproducing kernel Hilbert spaces associated with the fractional and bi-fractional Brownian motions. As a tool, we define a new function of two complex variables, which is a natural generalization of the classical Gamma function for the setting we consider. D. Alpay thanks the Earl Katz family for endowing the chair which supports his research.     

Influence Function and Efficiency of the Minimum Covariance Determinant Scatter Matrix Estimator

The minimum covariance determinant (MCD) scatter estimator is a highly robust estimator for the dispersion matrix of a multivariate, elliptically symmetric distribution. It is relatively fast to compute and intuitively appealing. In this note we derive its influence function and compute the asymptotic variances of its elements. A comparison with the one step reweighted MCD and with S-estimators is made. Also finite-sample results are reported.