关于形式三角矩阵环

本文研究形式三角矩阵环 R 的若干新性质,讨论 R-模的伪投射性,给出了形式三角矩阵环 R 是 V-环或半 V-环的充要条件．同时,给出了 R 是 PS-环的条件．     

Matrix models, complex geometry, and integrable systems: I

We consider the simplest gauge theories given by one-and two-matrix integrals and concentrate on their stringy and geometric properties. We recall the general integrable structure behind the matrix integrals and turn to the geometric properties of planar matrix models, demonstrating that they are universally described in terms of integrable systems directly related to the theory of complex curves. We study the main ingredients of this geometric picture, suggesting that it can be generalized beyond one complex dimension, and formulate them in terms of semiclassical integrable systems solved by constructing tau functions or prepotentials. We discuss the complex curves and tau functions of one-and two-matrix models in detail. [This article was written at the request of the Editorial Board. It is based on several lectures presented at schools of mathematical physics and talks at the conference “Complex Geometry and String Theory” and the Polivanov memorial seminar.] __________ Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 147, No. 2, pp. 163–228, May, 2006.     

混合互补判断矩阵一致性研究

给出混合互补判断矩阵一致性的定义和判别加性一致性的方法.定义了核算子、核矩阵,对带有精确数、三角模糊数和梯形模糊数的混合互补判断矩阵给出基于核矩阵的一致性调整方法,调整量可以是精确数也可以是模糊数.最后给出一个应用实例.     

A Frisch-Newton Algorithm for Sparse Quantile Regression

Recent experience has shown that interior-point methods using a log barrier approach are far superior to classical simplex methods for computing solutions to large parametric quantile regression problems. In many large empirical applications, the design matrix has a very sparse structure. A typical example is the classical fixed-effect model for panel data where the parametric dimension of the model can be quite large, but the number of non-zero elements is quite small. Adopting recent developments in sparse linear algebra we introduce a modified version of the Prisch-Newton algorithm for quantile regression described in Portnoy and Koenker~([28]). The new algorithm substantially reduces the storage (memory) requirements and increases computational speed. The modified algorithm also facilitates the development of nonparametric quantile regression methods. The pseudo design matrices employed in nonparametric quantile regression smoothing are inherently sparse in both the fidelity and roughness penalty components. Exploiting the sparse structure of these problems opens up a whole range of new possibilities for multivariate smoothing on large data sets via ANOVA-type decomposition and partial linear models.     

实对称矩阵的迹的几点性质

研究实对称矩阵的迹的几点性质，给出６个引理，推得３个定理     

Minimum Cycle of Row Vector of a Generalized Circulant Fuzzy Matrix

51.IntroductionLetF=[O,1],foranya,beF,definea b=max{a,b},a*b=min{a,b}.Mn(F)standsforthesetofa1lthenthordermatrixesinF,matrixAinMn(F)iscalledFuzzymatrixA.Letrbeanynon-negativeinteger.lnannthordermatrix,exclusiveofthefirstrow,theelementsofeveryotherrowarethee1ementsoftheprecedingrowthatcirculaterightwardr-co1umns.Thisnthordermatrixisannthorderr-circulantFuzzymatrix(alsocalledgenearLizedcirculantFuzzymatrix)-Wecallrthecircu1antindexofr-circulantFuzzymatrix.Inthebooklistedin[1j,thisisgiven:…     

关于广义正定矩阵的进一步推广

受到Johnson、佟文廷、夏长富的启发,进一步推广了广义正定矩阵的定义,并得出了更广义正定矩阵P∈PA+的若干性质.     

On Polynomials of Special Form over a Finite Field of Odd Characteristic Attaining the Weil Bound

An explicit construction of polynomials over a finite field of odd characteristic, for which the absolute value of trigonometric sums attains the Weil bound, is based on the construction of cyclic matrices of given rank. Dickson polynomials of the second kind play an essential role in the study of such matrices.__________Translated from Matematicheskie Zametki, vol. 78, no. 1, 2005, pp. 16–25.Original Russian Text Copyright © 2005 by L. A. Bassalygo, V. A. Zinov’ev.     

On the use of two QMR algorithms for solving singular systems and applications in Markov chain modeling

Recently, Freund and Nachtigal proposed the quasi-minimal residual algorithm (QMR) for solving general nonsingular non-Hermitian linear systems. The method is based on the Lanczos process, and thus it involves matrix—vector products with both the coefficient matrix of the linear system and its transpose. Freund developed a variant of QMR, the transpose-free QMR algorithm (TFQMR), that only requires products with the coefficient matrix. In this paper, the use of QMR and TFQMR for solving singular systems is explored. First, a convergence result for the general class of Krylov-subspace methods applied to singular systems is presented. Then, it is shown that QMR and TFQMR both converge for consistent singular linear systems with coefficient matrices of index 1. Singular systems of this type arise in Markov chain modeling. For this particular application, numerical experiments are reported.