Moore-Penrose Inverses and Group Inverses of Block k-Circulant Matrices

Ｍｏｏｒｅ－Ｐｅｎｒｏｓｅ　Ｉｎｖｅｒｓｅｓ　ａｎｄ　Ｇｒｏｕｐ　Ｉｎｖｅｒｓｅｓ　ｏｆ　Ｂｌｏｃｋ　ｋ－Ｃｉｒｃｕｌａｎｔ　ＭａｔｒｉｃｅｓＭｏｏｒｅ－ＰｅｎｒｏｓｅＩｎｖｅｒｓｅｓａｎｄＧｒｏｕｐＩｎｖｅｒｓｅｓｏｆＢｌｏｃｋｋ－Ｃｉｒｃｕｌａｎ...     

A CLASS OF FACTORIZATION UPDATE ALGORITHM FOR SOLVING SYSTEMS OF SPARSE NONLINEAR EQUATIONS

ＡＣＬＡＳＳＯＦＦＡＣＴＯＲＩＺＡＴＩＯＮＵＰＤＡＴＥＡＬＧＯＲＩＴＨＭＦＯＲＳＯＬＶＩＮＧＳＹＳＴＥＭＳＯＦＳＰＡＲＳＥＮＯＮＬＩＮＥＡＲＥＱＵＡＴＩＯＮＳＢＡＩＺＨＯＮＧＺＨＩ（ＩｎｓｔｉｔｕｔｅｏｆＣｏｍｐｕｔａｔｉｏｎａｌＭａｔｈｅｍａｔｉｃ...     

广义矩阵函数及其指标

本文推广了广义矩阵函数及对称张量的一些定理，给出了广义矩阵函数指标的若干关系式．     

矩阵的多行拟相合分类及其应用

本文把方阵的拟相合概念推广为长方阵的多行拟相合概念，并对最简情形即Ｍ２，４（Ｆｐ）给出分类结果．此概念之一应用出现在有限环的同构分类之中．     

关于G－分次环与G－集的Smash积的几个结果

设Ｇ为任意群，本文借助于环的矩阵表示给出了Ｇ-分次环与任意可迁Ｇ-集的ｓｍａｓｈ积是素环或单环的刻画．     

A note on the simple structural regression model

In this paper we investigate some aspects like estimation and hypothesis testing in the simple structural regression model with measurement errors. Use is made of orthogonal parametrizations obtained in the literature. Emphasis is placed on some properties of the maximum likelihood estimators and also on the distribution of the likelihood ratio statistics.     

A preconditioner for constrained and weighted least squares problems with Toeplitz structure

We study methods for solving the constrained and weighted least squares problem min _x by the preconditioned conjugate gradient (PCG) method. HereW = diag (₁, , _m ) with _{1 m} 0, andA ^T = [T ₁ ^T , ,T _k ^T ] with Toeplitz blocksT _l R ^{n × n} ,l = 1, ,k. It is well-known that this problem can be solved by solving anaugmented linear 2 × 2 block linear systemM +Ax =b, A ^T = 0, whereM =W ^–1. We will use the PCG method with circulant-like preconditioner for solving the system. We show that the spectrum of the preconditioned matrix is clustered around one. When the PCG method is applied to solve the system, we can expect a fast convergence rate.Research supported by HKRGC grants no. CUHK 178/93E and CUHK 316/94E.     

The generalized linear complementarity problem revisited

Given a vertical block matrixA, we consider in this paper the generalized linear complementarity problem VLCP(q, A) introduced by Cottle and Dantzig. We formulate this problem as a linear complementarity problem with a square matrixM, a formulation which is different from a similar formulation given earlier by Lemke. Our formulation helps in extending many well-known results in linear complementarity to the generalized linear complementarity problem. We also show that the class of vertical block matrices which Cottle and Dantzig's algorithm can process is the same as the class of equivalent square matrices which Lemke's algorithm can process. We also present some degree-theoretic results on a vertical block matrix.     

Equilibrium programming using proximal-like algorithms

We compute constrained equilibria satisfying an optimality condition. Important examples include convex programming, saddle problems, noncooperative games, and variational inequalities. Under a monotonicity hypothesis we show that equilibrium solutions can be found via iterative convex minimization. In the main algorithm each stage of computation requires two proximal steps, possibly using Bregman functions. One step serves to predict the next point; the other helps to correct the new prediction. To enhance practical applicability we tolerate numerical errors. Research supported partly by the Norwegian Research Council, project: Quantec 111039/401.     

Normal dilatation of triangular matrices

LetR be a (real or complex) triangular matrix of ordern, say, an upper triangular matrix. Is it true that there exists a normaln×n matrixA whose upper triangle coincides with the upper triangle ofR? The answer to this question is “yes” and is obvious in the following cases: (1)R is real; (2)R is a complex matrix with a real or a pure imaginary main diagonal, and moreover, all the diagonal entries ofR belong to a straight line. The answer is also in the affirmative (although it is not so obvious) for any matrixR of order 2. However, even forn=3 this problem remains unsolved. In this paper it is shown that the answer is in the affirmative also for 3×3 matrices.