广义B—D逆及其应用

本文首先给出了著名的Bott-Duffrin逆(简称B-D逆)A_(L)~((-1))的许多进一步的性质与新的应用,指出了A_(L)~((-1))的存在性与方程组的解的两种唯一性之间的紧密联系;然后定义了广义B-D逆A_(L)~(+)=P_L(AP_L+P_L~⊥)~+,讨论了A_(L)~(+)的一些性质,给出了当A为一般方阵与当A为L=N(B)—非负定阵时关于方程组(1)的可解性的方便的判别条件以及有解时其解的显式,统一处理了在最优化、线性统计推断、二维插值中出现的方程组(1)与约束二次极值问题的求解问题。     

GMRES方法的收敛率

1 引 言 GMRES方法是目前求解大型稀疏非对称线性方程组 Ax=b,A∈R~(n×n);x,b∈R~n (1)最为流行的方法之一.设x~((0))是(1)解的初始估计,r~((0))=b-Ax~((0))是初始残量,K_k=span{r~((0)),Ar~((0)),…A~(k-1)r~((0))}为由r~((0))和A产生的Krylov子空间.GMRES方法的第k步     

具有左、右特征向量及特征值约束下逆特征值问题

§1 问题的提法R~(n×m)表示所有 n×m 阶实阵集合,(A)表示矩阵 A 的列空间,A~+表示 A 的 Moore-Penrose 广义逆,P_A=AA~+表示到(A)的正交投影核子;I_n 表示 n 阶单位阵,‖·‖_F 表示 Frobenius 范数。问题Ⅰ给定X,Y∈~(n×m),Λ=diag(λ_1,λ_2,…,λ_m)∈R~(m×m),找 A∈R~(n×m),使得问题Ⅱ给定 A~*∈R~(n×n),找∈S_E,使得‖A~*-‖_F=‖A~*-A‖_F,其中 S_E是问题Ⅰ的集合。本文讨论问题Ⅰ有解的充分与必要条件,且求出 S_E的表达式,同时给出的表达式。     

等式约束加权线性最小二乘问题的解法

1 引言 在实际应用中常会提出解等式约束加权线性最小二乘问题 min||b-Ax||_M,(1.1) x∈C~n s.t.Bx=d, 其中B∈C~(p×n),A∈C~(q×n),d∈C~p,b∈C~q,M∈C~(q×q)为Hermite正定阵. 对于问题(1.1),目前已有多种解法,见文[1—3).本文将利用广义逆矩阵的知识,给出(1.1)的通解及迭代解法.本文中关于矩阵广义逆与投影算子(矩阵)的记号基本上与文[4]的相同.例如,A~+表示A的MP逆,P_L表示到子空间L上的正交投影算子,λ_(max)(MAY)表示矩阵M~(1/2)AY的最大特征值.我们还要用到广义BD逆的概念: 设A∈C~(n×n),L为C~n的子空间,则称A_(L)~(+)=P_L(AP_L+P_L⊥)~+为A关于L的广义BD逆.     

一类奇异线性方程组的Cramer法则

在 [3]中 ,给出了一类奇异线性方程组Ax =b的唯一解x =Adb的Cramer法则。本文将其推广到带W 权Drazin逆Ad ,w,得到如下结果 :奇异线性方程组Ax =b的唯一解x =WAd,wWb的分量xj 可表示成xj=det (WA) (j→Wb) UV(j→ 0 ) 0 　det WAUV 0 　j=1,2 ,… ,n ,其中A∈Cm×n,W∈Cn×m,Ind(WA) =k1,Ind(AW ) =k2 ,rank(WA) k1=r 相似文献   

H（n,≥）中矩阵广义逆的单调性问题

在文献[4—7]基础上,本文给出了Lowner偏序下半正定自共轭四元数矩阵的单调性解集A{1;≥,Υ_1;≤B~((1))},B{1;≥,Υ_2;≥A~((1))}的显式及单调性“A≥BB~((1,2))≥A~((1,2))”成立的充要条件。     

ON UNIQUENESS OF SOLUTION TO POINTWISE LANDAU PROBLEM ON THE FINITE INTERVAL

1. Introduction Let W_∞~((r)) (β) = {f| f∈W_∞~((r)) [-1,1], ||f||_(C[-1,1]) β, ||f~((r))||_∞ 1}.In this paper, we will consider the following Landau problem:λf~((k))(ξ) + μf~((k-1)) (ξ) →inf, f∈W_∞~((r)) (β), (1.1)where ξ∈[-1,1], 1(?)k(?)r-1, and λ, μ real and not all zero, (if k=1,suppose λ≠0 in addition ). A. Pinkus studied it first. To begin with, we introduce some fundamental definitions anddenotions. The perfect spline f, which satisfies || f~((r))||_∞ = 1 andhas n knots and n+r+1 points of equioscillation in [-1,1], isdenoted by x_(nr), which is refered as Tchebyshev perfect spline. And     

关于Fuzzy矩阵的广义逆

本文分别给出了Fuzzy矩阵存在广义{1,3}-逆、广义{1,4}-逆以及Moore-Penrose广义逆Fuzzy矩阵的一些充要条件。又得到求上述广义逆Fuzzy矩阵的一些公式。主要的结果有: 1.Fuzzy矩阵A的广义{1,3}-逆A~((1.3))(广义{1,4}-逆A~((1.4))存在的充要条件是Fuzzy关系方程有解。2.Fuzzy矩阵A的Moore-Penrose广义逆A~T存在的充要条件是Fuzzy关系方程均有解。3.如果B、C分别为Fuzzy关系方程的一个解,那么。     

轨形Gromov-Witten不变量沿光滑点的加权涨开公式

本文考虑,当一个紧辛轨形群胚(X,ω)沿着光滑点作加权涨开时,它的形如<α_1,…,α_m,[pt]>_(g,A)~X的轨形Gromov-Witten不变量的变化公式,其中[pt]∈H_(dR)~(2n)(X)是生成元,dimX=2n.我们证明了对于非零A∈H_2(|X|,Z),<α_1,…,α_m,[pt]>_(g,A)~X={_(g_1,pl(A)-e’)~xdimX=4,g≥0,∑((-1)g_1·2)/(2g_1+2)!_(g_2,pl(A)-e’)~xdimX=6,g≥0,_(g_1,pl(A)-e’)~xdimX≥8,g=0其中x是X沿一光滑点的权α=(α_1,…,α_n)的加权涨开,且α_1≥α_i,2≤i≤n.     

Bernstein-Kantorovich算子逆中插式的强逆不等式

给出并证明了Bernstein—Kantorovich算子逆中插式的B型强逆不等式,即存在l,使得ω_φ~(2r)(f,1/n~(1/2))≤C(||k_n~((2r-1))f-f||_∞+||K_(ln)~((2r-1))f-f||_∞).     

The recovery of even polynomial potentials

We consider the problem of reconstructing an even polynomial potential from one set of spectral data of a Sturm-Liouville problem. We show that we can recover an even polynomial of degree 2m from m+1 given Taylor coefficients of the characteristic function whose zeros are the eigenvalues of one spectrum. The idea here is to represent the solution as a power series and identify the unknown coefficients from the characteristic function. We then compute these coefficients by solving a nonlinear algebraic system, and provide numerical examples at the end. Because of its algebraic nature, the method applies also to non self-adjoint problems.     

Two-letter group codes that preserve aperiodicity of inverse finite automata

We construct group codes over two letters (i.e., bases of subgroups of a two-generated free group) with special properties. Such group codes can be used for reducing algorithmic problems over large alphabets to algorithmic problems over a two-letter alphabet. Our group codes preserve aperiodicity of inverse finite automata. As an application we show that the following problems are PSpace-complete for two-letter alphabets (this was previously known for large enough finite alphabets): The intersection-emptiness problem for inverse finite automata, the aperiodicity problem for inverse finite automata, and the closure-under-radical problem for finitely generated subgroups of a free group. The membership problem for 3-generated inverse monoids is PSpace-complete. Both authors were supported in part by NSF grant DMS-9970471. The first author was also supported in part by NSF grant CCR-0310793. The second author acknowledges the support of the Excellency Center, “Group Theoretic Methods for the Study of Algebraic Varieties” of the Israeli Science Foundation.     

Optimality-based clustering: An inverse optimization approach

We propose a new clustering approach, called optimality-based clustering, that clusters data points based on their latent decision-making preferences. We assume that each data point is a decision generated by a decision-maker who (approximately) solves an optimization problem and cluster the data points by identifying a common objective function of the optimization problems for each cluster such that the worst-case optimality error is minimized. We propose three different clustering models and test them in the diet recommendation application.     

Characterization of Inverse and Left Inverse SemigroupsbyTheirS1┐acts

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Inverse Obstacle Problem for the Non-Stationary Wave Equation with an Unknown Background

We consider boundary measurements for the wave equation on a bounded domain M ? ?² or on a compact Riemannian surface, and introduce a method to locate a discontinuity in the wave speed. Assuming that the wave speed consist of an inclusion in a known smooth background, the method can determine the distance from any boundary point to the inclusion. In the case of a known constant background wave speed, the method reconstructs a set contained in the convex hull of the inclusion and containing the inclusion. Even if the background wave speed is unknown, the method can reconstruct the distance from each boundary point to the inclusion assuming that the Riemannian metric tensor determined by the wave speed gives simple geometry in M. The method is based on reconstruction of volumes of domains of influence by solving a sequence of linear equations. For τ ∈C(?M) the domain of influence M(τ) is the set of those points on the manifold from which the distance to some boundary point x is less than τ(x).     

Detection of multilayered media in the acoustic waveguide

This work is concerned with the inverse problem for ocean acoustics modeled by a multilayered waveguide with a finite depth. We provide explicit formulae to locate the layers, including the seabed, and reconstruct the speed of sound and the densities in each layer from measurements collected on the surface of the waveguide. We proceed in two steps. First, we use Gaussian type excitations on the upper surface of the waveguide and then from the corresponding scattered fields, collected on the same surface, we recover the boundary spectral data of the related 1D spectral problem. Second, from these spectral data, we reconstruct the values of the normal derivatives of the singular solutions, of the original waveguide problem, on that upper surface. Finally, we derive formulae to reconstruct the layers from these values based on the asymptotic expansion of these singular solutions in terms of the source points.     

Inverse Eigenvalue Problems for Smooth Potential

We consider the inverse eigenvalue problem of the onedimensional Schrödinger operator for finite intervals. We give sufficient conditions for finitely many partially known spectra and partial information on the potential to determine the Schrodinger operator on the whole interval.     

The inverse solution of the atomic mixing equations by an operator-splitting method

The quantification problem of recovering the original material distribution from secondary ion mass spectrometry (SIMS) data is considered in this paper. It is an inverse problem, is ill-posed and hence it requires a special technique for its solution. The quantification problem is essentially an inverse diffusion or (classically) a backward heat conduction problem. In this paper an operator-splitting method (that is proposed in a previous paper by the first author for the solution of inverse diffusion problems) is developed for the solution of the problem of recovering the original structure from the SIMS data. A detailed development of the quantification method is given and it is applied to typical data to demonstrate its effectiveness.     

Inverse degree and edge-connectivity

Let G be a connected graph with vertex set V(G), order n=|V(G)|, minimum degree δ and edge-connectivity λ. Define the inverse degree of G as , where d(v) denotes the degree of the vertex v. We show that if