Common Conserved Densities AKNS Hierarchies of Equations

ＣｏｍｍｏｎＣｏｎｓｅｒｖｅｄＤｅｎｓｉｔｉｅｓＡＫＮＳＨｉｅｒａｒｃｈｉｅｓｏｆＥｑｕａｔｉｏｎｓ￥ＧｕｏＦｕｋｕｉ（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ，ＳｈａｎｄｏｎｇＭｉｎｉｎｇＩＮｓｔｉｔｕｔｅ）Ａｂｓｔｒａｃｔ：Ａｓｐｅｐｅｒｃ...     

Fractal Model of the Spheroidal Graphit

ＦｒａｃｔａｌＭｏｄｅｌｏｆｔｈｅＳｐｈｅｒｏｉｄａｌＧｒａｐｈｉｔｅＺ．Ｙ．ＨＥａｎｄＫ．Ｚ．ＨＷＡＮＧＤｅｐｔ．ｏｆＥｎｇｉｎｅｅｒｉｎｇＭｅｃｈａｎｉｃｓ，ＴｓｉｎｇｈｕａＵｎｉｖｅｒｓｉｔｙＢｅｉｊｉｎｇ，Ｐ．Ｒ．Ｃｈｉｎａ１０００８４Ａｂｓ...     

On the Extension of PM-Ring

ＯｎｔｈｅＥｘｔｅｎｓｉｏｎｏｆＰＭ－Ｒｉｎｇ朱元森ＯｎｔｈｅＥｘｔｅｎｓｉｏｎｏｆＰＭ－Ｒｉｎｇ￥ＺｈｕＹｕａｎｓｅｎ（Ｄｅｐｔ．ｏｆＭａｔｈ．，ＨｅｂｅｉＴｅａｃｈｅｒｓＵｎｉｖ．，Ｓｈｉｊｉａｘｈｕａｎｇ，０５００１６）Ａｂｓｔｒａｃｔ：Ａｒｉ...     

REGULARITY ESTIMATES FOR THE OBLIQUE DERIVATIVE PROBLEM ON NON-SMOOTH DOMAINS （I）

ＲＥＧＵＬＡＲＩＴＹＥＳＴＩＭＡＴＥＳＦＯＲＴＨＥＯＢＬＩＱＵＥＤＥＲＩＶＡＴＩＶＥＰＲＯＢＬＥＭＯＮＮＯＮ－ＳＭＯＯＴＨＤＯＭＡＩＮＳ（Ｉ）￥ＧＵＡＮＰＥＮＧＦＥＩ；Ｅ．ＳＡＷＹＥＲＡｂｓｔｒａｃｔ：Ｔｈｅａｕｔｈｏｒｓｃｏｎｓｉｄｅｒｔｈｅｅｘｉ...     

BINARY NONLINEARIZATION FOR THE DIRAC SYSTEMS

ＢＩＮＡＲＹＮＯＮＬＩＮＥＡＲＩＺＡＴＩＯＮＦＯＲＴＨＥＤＩＲＡＣＳＹＳＴＥＭＳＭＡＷＥＮＸＩＵＡｂｓｔｒａｃｔＡＢａｒｇｍａｎｎｓｙｍｍｅｔｒｙｃｏｎｓｔｒａｉｎｔｉｓｐｒｏｐｏｓｅｄｆｏｒｔｈｅＬａｘｐａｉｒｓａｎｄｔｈｅａｄｊｏｉｎｔＬａ...     

A COMPACTLY SUPPORTED ORTHONORMALWAVELETOFNON－TENSORTYPE

ＡＣＯＭＰＡＣＴＬＹＳＵＰＰＯＲＴＥＤＯＲＴＨＯＮＯＲＭＡＬＷＡＶＥＬＥＴＯＦＮＯＮ－ＴＥＮＳＯＲＴＹＰＥ＊ＳＵＮＱＩＹＵＡＮＤＺＨＥＮＧＹＡＮＺＨＡＮＧＡｂｓｔｒａｃｔ．Ｉｎｔｈｉｓｎｏｔｅｗｅｃｏｎｓｔｒｕｃｔａｎｅｘａｍｐｌｅｏｆｃｏｍｐａｃｔ...     

PARTIAL FERRERS MATRICES

ＰＡＲＴＩＡＬＦＥＲＲＥＲＳＭＡＴＲＩＣＥＳ￥ＲＩＣＨＡＲＤＡ；ＢＲＵＡＬＤＩ＆ＬＩＱＩＡＯ（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ，ＵｎｉｖｅｒｓｉｔｙｏｆＷｉｓｃｏｎｓｉｎ，Ｍａｄｉｓｏｎ，Ｗｉｓｃｏｎｓｉｎ５３７０６，Ｕ．Ｓ．Ａ．）（Ｄ...     

TENSOR PRODUCT OF SEMIGROUPSAND THE EQUATION AC-CB=Q

ＴＥＮＳＯＲＰＲＯＤＵＣＴＯＦＳＥＭＩＧＲＯＵＰＳＡＮＤＴＨＥＥＱＵＡＴＩＯＮＡＣ－ＣＢ＝Ｑ￥ＷＡＮＧＳＨＥＮＧｗａＮＧ；Ｉ．ＥＲＤＥＬＹＩＡｂｓｔｒａｃｔ：Ｐｒｏｐｅｒｔｉｅｓｆｏｒｔｅｎｓｏｒｐｒｏｄｕｃｔｓｏｆｓｅｍｉｇｒｏｕｐｓａｒｅｃｏｎｓ...     

The Einstein－K ah ler Metrics with Singularitieson A Class of the Reinhardt Domains

ＴｈｅＥｉｎｓｔｅｉｎ－Ｋ ａｈ ｌｅｒ　ＭｅｔｒｉｃｓｗｉｔｈＳｉｎｇｕｌａｒｉｔｉｅｓｏｎＡＣｌａｓｓｏｆｔｈｅＲｅｉｎｈａｒｄｔＤｏｍａｉｎｓ　ＹｉｎＷｅｉｐｉｎｇ（殷慰萍）；ＷａｎｇＡｎ（王安）（Ｄｅｐｔ．ｏｆＭａｔｈ．ＣａｐｉｔａｌＮｏｒｍａ...     

On the Integral Extension of Lattices

ＯｎｔｈｅＩｎｔｅｇｒａｌＥｘｔｅｎｓｉｏｎｏｆＬａｔｉｃｅｓＨａｎＳｈｉａｎ（韩士安）（ＤｅｐａｒｔｍｅｎｔｏｆＭａｔｈｅｍａｔｉｃｓ，ＥａｓｔＣｈｉｎａＮｏｒｍａｌＵｎｉｖｅｒｓｉｔｙ，Ｓｈａｎｇｈａｉ，２０００６２）ＡｂｓｔｒａｃｔＩｎｔｈｉｓ...     

Vector space of linearizations for the quadratic two-parameter matrix polynomial

Given a quadratic two-parameter matrix polynomial Q(λ,?μ), we develop a systematic approach to generating a vector space of linear two-parameter matrix polynomials. The purpose for constructing this vector space is that potential linearizations of Q(λ,?μ) lie in it. Then, we identify a set of linearizations and describe their constructions. Finally, we determine a class of linearizations for a quadratic two-parameter eigenvalue problem.     

Fuzzy双线性方程最大解的一种简便算法

引进Fuzzy双线性方程A·X=B·X中间矩阵的概念, 并利用此概念得出了这类方程最大解的一种快速算法.最后通过实例说明了该算法的优越性.     

Nonanticipative transformations of the two-parameter Wiener process and a Girsanov theorem

Nonanticipative linear transformations of the two-parameter Wiener process W are studied. It is shown that they induce measures equivalent to two-parameter Wiener measure and the corresponding Radon-Nikodym derivatives are calculated. A two-parameter extension of Girsanov's theorem is established for a class of nonanticipative, possibly nonlinear transformations of W.     

极大熵方法与二次规划子问题的显式解

本文对混合约束极大极小问题的目标函数与约束分别用熵函数来逼近,讨论了逼近问题的二次规划子问题的搜索方向的显式形式,并给出了极大极小问题和多目标规划的二次规划予问题的显式解。将所得结果用于相应的算法中,可提高算法的有效性。     

关于凸函数的双参数平均不等式

本文利用二重积分证明了凸函数的双参数平均不等式,并给出了它的几个推论从而推广和加强了文[3]的定理。     

基于Selectope解集和局中人最大满意度的合作对策解的研究

针对决策者在获取Selectope解集后难以聚焦到最终分配方案上的问题,论文对合作对策的解集进行了研究。首先借助Harsanyi红利在局中人中进行分配的思想,得到Selectope解集作为研究问题的可行域。之后,在局中人完全理性的条件下,充分考虑局中人参与合作的初衷,运用超出值的概念,构建了描述局中人最大满意度的目标函数,进而得到基于Selectope解集与局中人最大满意度的非线性规划模型,用于合作对策收益分配问题的求解。最后,通过算例验证了该求解思路的可行性与求解结果的合理性。研究结果表明,论文提出的求解思路能够有效缩减Selectope解集的体量,为决策者提供一个精炼的抉择空间,在一定程度上拓展了Selectope解集的应用,同时,构建的局中人最大满意度的非线性函数对局中人满意度研究也有一定的参考价值。     

Backward Stochastic Differential Equations in the Plane

This paper is devoted to study backward stochastic differential equations in the plane driven by a Brownian sheet, where the value of the solution at the corner (s ₀,t ₀) is fixed. The existence and uniqueness of a solution is obtained by means of Picard's approximation scheme and a suitable two-parameter Gronwall's type lemma.     

基于双参数Copula沪港股市的相关性分析

通过双参数Copula分析上证指数和恒生指数的尾部相关性,并与单参数Copula及混合Copula进行比较分析,参数估计使用半参数估计法,结果表明:与单参数Clayton Copula、Gumbel-Hougaard Copula以及由两者组成的混合Copula相比,双参数BB1 Copula对数据具有更好的拟合效果;且通过分析发现两股市的上尾相关性大于下尾相关性.