双正交小波滤波器簇代数结构及构造

研究了一类向量多项式两种特殊分解结构,由此引进了与双正交小波滤波器簇相应的多相向量概念,分析了多相向量分解代数结构,得到了在低通滤波器给定条件下,满足任意阶可和规则的对偶低通滤波器构造方法.分析并证明了双正交滤波器簇对应多相向量至多具有的3种代数分解结构,根据其分解的形式得到了双正交小波基构造的新方法,该方法便于双正交小波构造计算机程序化.     

具有多项式衰减面具的向量细分格式

具有多项式衰减面具的向量细分方程在刻画小波Riesz基和双正交小波等方面有着重要作用.本文主要研究这类方程解的性质.向量的细分方程具有形式：Ф=∑α∈Zsa（α）（2·-α）,其中Ф=（Ф1,...,Фr）T是定义在Rs上的向量函数,a：=（a（α））α∈Zs是一个具有多项式衰减的r×r矩阵序列称为面具.关于面具a定义一个作用在（Lp（Rs））r上的线性算子Qa,Qaf：=∑α∈Zsa（α）f（2·α）.迭代格式（Qanf）n=1,2,...称为向量细分格式或向量细分算法.本文证明如果具有多项式衰减面具的向量细分格式在（L2（Rs））r中收敛,那么其收敛的极限函数将自动具有多项式衰减.另外,给出了当迭代的初始函数满足一定的条件时的向量细分格式的收敛阶.     

不同基底的正交多项式回归

提出了把Legendre多项式转换为定义在{1,2,…,n}上的正交多项式的Gram-Schmidt正交化方法.模拟比较了不同基底的正交多项式回归效果的差异.实证发现在AIC准则下,正交多项式回归在保证拟合效果的同时可最大限度地降低多项式次数.开发了正交多项式回归全过程和模型评价的MATLAB软件工程.     

单位圆上正交多项式及其导数

对单位圆上关于有限正Ｂｏｒｅｌ测度的正交多项式导数的渐近性质的研究在七十年代已有所结果和突破，如熟知的Ｓｚｅｇ理论等。然而对其微分性质的分析和讨论并不算多，即使如此，也只是限于考虑单位圆上正交多项式的某些特殊类型￣［１］。本文证明单位圆上正交多项式序列的导数仍然是单位圆上正交多项式序列，并给出它们与相关微分方程之间的一些关系。     

单位圆上正交多顶式及其导数

对单位圆上关于有限正Ｂｏｒｅｌ测度的正交多项式导数的渐近性质的研究在七十年代已有所结果和突破，如熟知的Ｓｚｅｇｏｅ理论等。然而对其微分性质的分析和讨论并不算多，即使如此，也只是限于考虑单位圆上正交多项式的某些特殊类型＾［４］。本文证明单位圆上正交多项式序列的导数仍然是单位圆上正交多项式序列，并给出它们与相关微分方程之间的一些关系。     

利用正交多项式优化炼油装置操作条件

本文对于炼油装置所安排的正交试验过程，利用正交多项式确定出各影响试验指标的因素对试验指标的效应函数，从而求出所有因素对试验指标的效应函数多项式．利用多项式来优化装置操作条件．     

新的一类三变量正交多项式及其递推公式

研究一类新的三变量正交多项式, 定义为二阶偏微分算子的本征函数, 且在一曲四面体域上正交. 该曲四面体可由普通的四面体映射而得, 可视为 二维Steiner区域的三维推广. 所讨论的正交多项式可视为该区域上的Jacobi多项式. 推导了正交多项式的显式递推公式, 证明其所含的正交多项式项数不依赖多项式的总次数, 沿两个复变量z和$\bar z$方向及单个实变量r方向, 递推公式所含的正交多项式项数分别只为5项与7项. 作为3个特例, 详细讨论了三变量的第1类与第2类Chebyshev多项式及Lengendre多项式.     

与Hermite多项式和广义Laguerre多项式相关联的双正交多项式系统

生成函数刻画了正交多项式的很多重要性质.本文的主要目的是根据生成函数的特点研究正交多项式类之间的渐近关系.本文拓展了Lee及其合作者的工作,构造一类双正交多项式系统,并由此构造出分别渐近于Hermite多项式和广义Laguerre多项的函数列;给出渐近于Hermite多项式和广义Laguerre多项的函数列的判定定理.作为这些性质的应用,可以直接获得若干正交多项式和组合多项式的渐近表示,从而验证了揭示超几何多项式渐近关系的Askey格式成立.     

渐近于Hermite多项式的双正交系统

本文利用渐近于Gauss函数的函数类?,给出渐近于Hermite正交多项式的一类Appell多项式的构造方法,使得该序列与?的n阶导数之间构成了一组双正交系统.利用此结果,本文得到多种正交多项式和组合多项式的渐近性质.特别地,由N阶B样条所生成的Appell多项式序列恰为N阶Bernoulli多项式.从而,Bernoulli多项式与B样条的导函数之间构成了一组双正交系统,且标准化之后的Bernoulli多项式的渐近形式为Hermite多项式.由二项分布所生成的Appell序列为Euler多项式,从而,Euler多项式与二项分布的导函数之间构成一组双正交系统,且标准化之后的Euler多项式渐近于Hermite多项式.本文给出Appell序列的生成函数满足的尺度方程的充要条件,给出渐近于Hermite多项式的函数列的判定定理.应用该定理,验证广义Buchholz多项式、广义Laguerre多项式和广义Ultraspherical(Gegenbauer)多项式渐近于Hermite多项式的性质,从而验证超几何多项式的Askey格式的成立.     

多维周期双正交向量小波的构造

本文研究了多维周期双正交向量小波的构造通过使用矩阵分解，给出具有矩阵伸缩的周期双正交向量小波构造的一种算法     

Vector Interpretation of the Matrix Orthogonality on the Real Line

In this paper we study sequences of vector orthogonal polynomials. The vector orthogonality presented here provides a reinterpretation of what is known in the literature as matrix orthogonality. These systems of orthogonal polynomials satisfy three-term recurrence relations with matrix coefficients that do not obey to any type of symmetry. In this sense the vectorial reinterpretation allows us to study a non-symmetric case of the matrix orthogonality. We also prove that our systems of polynomials are indeed orthonormal with respect to a complex measure of orthogonality. Approximation problems of Hermite-Padé type are also discussed. Finally, a Markov’s type theorem is presented.     

Formal vector orthogonal polynomials

The aim of this paper is to define and to study orthogonal polynomials with respect to a linear functional whose moments are vectors. We show how a Clifford algebra allows us to construct such polynomials in a natural way. This new definition is motivated by the fact that there exist natural links between this theory of orthogonal polynomials and the theory of the vector valued Padé approximants in the sense of Graves-Morris and Roberts. This revised version was published online in June 2006 with corrections to the Cover Date.     

Some Linear Functionals Having Classical Orthogonal Polynomials as Moments

In this paper, we deal with some linear functionals on the vector space of polynomials whose moments are, in certain normalization, classical orthogonal polynomials (Hermite, Laguerre and Gegenbauer). We show that these linear functionals are semiclassical of class, at most, three. We give the coefficients in the three-term recurrence relations that the corresponding monic orthogonal polynomial sequences satisfy.     

Unbiased estimation in the multivariate natural exponential family with simple quadratic variance function

We give expansions for the unbiased estimator of a parametric function of the mean vector in a multivariate natural exponential family with simple quadratic variance function. This expansion is given in terms of a system of multivariate orthogonal polynomials with respect to the density of the sample mean. We study some limit properties of the system of orthogonal polynomials. We show that these properties are useful to establish the limit distribution of unbiased estimators.     

A generalization of the symmetric classical polynomials: Hermite and Gegenbauer polynomials

In this paper, we give new families of polynomials orthogonal with respect to a d-dimensional vector of linear functionals, d being a positive integer number, and generalizing the standard symmetric classical polynomials: Hermite and Gegenbauer. We state the inversion formula which is used to express the corresponding moments by means of integral representations involving the Meijer G-function. Moreover, we determine some characteristic properties for these polynomials: generating functions, explicit representations and component sets.     

Modified Moments and Matrix Orthogonal Polynomials

In the scalar case, computation of recurrence coefficients of polynomials orthogonal with respect to a nonnegative measure is done via the modified Chebyshev algorithm. Using the concept of matrix biorthogonality, we extend this algorithm to the vector case.     

A vector Chebyshev algorithm

We consider polynomials orthogonal relative to a sequence of vectors and derive their recurrence relations within the framework of Clifford algebras. We state sufficient conditions for the existence of a system of such polynomials. The coefficients in the above relations may be computed using a cross-rule which is linked to a vector version of the quotient-difference algorithm, both of which are proved here using designants. An alternative route is to employ a vector variant of the Chebyshev algorithm. This algorithm is established and an implementation presented which does not require general Clifford elements. Finally, we comment on the connection with vector Padé approximants. This revised version was published online in June 2006 with corrections to the Cover Date.     

Relative asymptotics for orthogonal matrix polynomials

In this paper we study sequences of matrix polynomials that satisfy a non-symmetric recurrence relation. To study this kind of sequences we use a vector interpretation of the matrix orthogonality. In the context of these sequences of matrix polynomials we introduce the concept of the generalized matrix Nevai class and we give the ratio asymptotics between two consecutive polynomials belonging to this class. We study the generalized matrix Chebyshev polynomials and we deduce its explicit expression as well as we show some illustrative examples. The concept of a Dirac delta functional is introduced. We show how the vector model that includes a Dirac delta functional is a representation of a discrete Sobolev inner product. It also allows to reinterpret such perturbations in the usual matrix Nevai class. Finally, the relative asymptotics between a polynomial in the generalized matrix Nevai class and a polynomial that is orthogonal to a modification of the corresponding matrix measure by the addition of a Dirac delta functional is deduced.     

On a Compression of Normal Matrix Polynomials

In this article, we study a compression of normal matrices and matrix polynomials with respect to a given vector and its orthogonal complement. The numerical range of this compression satisfies special boundary properties, which are investigated in detail. The characteristic polynomial of the compression is also considered.     

Upward Extension of the Jacobi Matrix for Orthogonal Polynomials

Orthogonal polynomials on the real line always satisfy a three-term recurrence relation. The recurrence coefficients determine a tridiagonal semi-infinite matrix (Jacobi matrix) which uniquely characterizes the orthogonal polynomials. We investigate new orthogonal polynomials by adding to the Jacobi matrixrnew rows and columns, so that the original Jacobi matrix is shifted downward. Thernew rows and columns contain 2rnew parameters and the newly obtained orthogonal polynomials thus correspond to an upward extension of the Jacobi matrix. We give an explicit expression of the new orthogonal polynomials in terms of the original orthogonal polynomials, their associated polynomials, and the 2rnew parameters, and we give a fourth order differential equation for these new polynomials when the original orthogonal polynomials are classical. Furthermore we show how the 1?orthogonalizing measure for these new orthogonal polynomials can be obtained and work out the details for a one-parameter family of Jacobi polynomials for which the associated polynomials are again Jacobi polynomials.