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分析、理论与应用(英文版)
分析、理论与应用(英文版)

徐利治

季刊

1672-4070

suqiu@nju.edu.cn

025-83593684

210093

南京市汉口路22号南京大学数学系ATA编辑部

分析、理论与应用(英文版)/Journal Analysis in Theory and ApplicationsCSCDCSTPCD北大核心
查看更多>>主要读者对象为数学类高年级学生、研究生、数学教师、数学工作者以及理、工科有关研究方向的人员。
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    Multiple Integral Inequalities for Schur Convex Functions on Symmetric and Convex Bodies

    Silvestru Sever Dragomir
    1-15页
    查看更多>>摘要:In this paper,by making use of Divergence theorem for multiple integrals,we establish some integral inequalities for Schur convex functions defined on bodies B C Rn that are symmetric,convex and have nonempty interiors.Examples for three dimensional balls are also provided.

    Boundedness of Some Commutators of Marcinkiewicz Integrals on Hardy Spaces

    Cuilan Wu
    16-27页
    查看更多>>摘要:Based on the results of the boundedness of μΩb on Lp spaces,by using the theory of atomic decomposition of Hardy spaces,we obtain the boundedness of μΩb on Hardy spaces.

    Sharp Bound for the Generalized m-Linear n-Dimensional Hardy-Littlewood-Pólya Operator

    Qianjun HeMingquan WeiDunyan Yan
    28-41页
    查看更多>>摘要:In this paper,we calculate the sharp bound for the generalized m-linear n-dimensional Hardy-Littlewood-Pólya operator on power weighted central and non-central homogeneous Morrey spaces.As an application,the sharp bound for the Hardy-Littlewood-Pólya operator on power weighted central and noncentral homo-geneous Morrey spaces is obtained.Finally,we also find the sharp bound for the Hausdorff operator on power weighted central and noncentral homogeneous Morrey spaces,which generalizes the previous results.

    Boundedness of the Multilinear Maximal Operator with the Hausdorff Content

    Shao LiuQianjun HeDunyan Yan
    42-52页
    查看更多>>摘要:In this paper,we establish the strong and weak boundedness of the multi-linear maximal operator in the setting of the Choquet integral with respect to the α-dimensional Hausdorff content.Our results cover Orobitg and Verdera's results in[8].

    Existence of Solution for a General Class of Strongly Nonlinear Elliptic Problems Having Natural Growth Terms and L1-Data

    Youssef AkdimMorad Ouboufettal
    53-68页
    查看更多>>摘要:This paper is concerned with the existence of solution for a general class of strongly nonlinear elliptic problems associated with the differential inclusionβ(u)+A(u)+g(x,u,Du)∋ f,where A is a Leray-Lions operator from W01,p(Ω)into its dual,β maximal monotone mapping such that 0 ∈ β(0),while g(x,s,ζ)is a nonlinear term which has a growth condition with respect to ζ and no growth with respect to s but it satisfies a sign-condition on s.The right hand side f is assumed to belong to L1(Ω).

    Busemann-Petty Type Problem for the General Lp-Centroid Bodies

    Weidong Wang
    69-82页
    查看更多>>摘要:Lutwak showed the Busemann-Petty type problem(also called the Shep-hard type problem)for the centroid bodies.Grinberg and Zhang gave an affirmation and a negative form of the Busemann-Petty type problem for the Lp-centroid bodies.In this paper,we obtain an affirmation form and two negative forms of the Busemann-Petty type problem for the general Lp-centroid bodies.

    On a Right Inverse of a Polynomial of the Laplace in the Weighted Hilbert Space L2(Rn,e-|x|2)

    Shaoyu DaiYang LiuYifei Pan
    83-92页
    查看更多>>摘要:Let P(Δ)be a polynomial of the Laplace operatorΔ=nΣj=1∂2/∂xj2 on Rn.We prove the existence of a bounded right inverse of the differential operator P(Δ)in the weighted Hilbert space with the Gaussian measure,i.e.,L2(Rn,e-|x|2).

    On Approximation by Neural Networks with Optimized Activation Functions and Fixed Weights

    Dansheng YuYunyou QianFengjun Li
    93-104页
    查看更多>>摘要:Recently,Li[16]introduced three kinds of single-hidden layer feed-forward neural networks with optimized piecewise linear activation functions and fixed weights,and obtained the upper and lower bound estimations on the approximation accuracy of the FNNs,for continuous function defined on bounded intervals.In the present paper,we point out that there are some errors both in the definitions of the FNNs and in the proof of the upper estimations in[16].By using new methods,we also give right approximation rate estimations of the approximation by Li's neural networks.