单位积决定的若当矩阵代数(英文)

本文研究了单位积决定的若当矩阵代数M=Mn(R)的条件及分类问题.利用基矩阵及巧妙对对称双线性映射{·,·}进行构造和扩充,用初等矩阵的方法,获得了一系列新的同样重要的定义,结论与证明(与参考文献[1]相比较),推广了参考文献[1]的结论,作为其应用可以进一步证明了Mn(R)上的任意可逆线性映射都是保单位积的.     

一类2-Hessenberg矩阵的广义逆

在[2]中,Ikebe给出了一类下Hessenberg矩阵之逆的上三角部分的求法,从而导出三对角矩阵求逆的一种方法.文[4]中获得了计算该类Hessenberg矩阵的逆和广义逆的显式公式,由此也可得出计算三对角矩阵广义逆的方法,文[3]将[2]中的结果推广到更一般的k-Hessenberg矩阵,进而得到带状矩阵求逆的一种方法.本文研究一类实2-Hessenberg矩阵的广义逆,表明这些广义逆可由低阶三角矩阵的逆和几个简单的秩-1或     

广义正定矩阵的Hadamard积和Kronecker积的一些性质

本文讨论了各类型广义正定矩阵的 Hadamard 积和 Kronecker 积的一些重要性质,得到了判断 n 阶实矩阵是广义正定矩阵的一些充要条件,它们是[1]-[4]中相应定理的推广,最后,我们修正了[4]中的一个错误。     

群表示论在直积网络中的一个应用

文[1]引入了直积网络的概念,欲得出二端口网络的直积网络能使信号在系统内部不会互相影响这一结果.按照[1]的符号(本文叙述中一般采用[1]的符号),应达到v′_i=f_i(v_i),i=1,2,3,4.(*)然而,[1]仅得出v′_1=f_1(v_1),离预定目标相差甚远,更不具有推广的基础.其实,只按照[1]的方法,不可能实现(*)式,也就得不出“使信号在系统内部不互相影响”这一结果.由于[1]未揭示出矩阵 S 的数学意义,那末到多端口的推广并非容易得出.本文沿用[1]的直积网络的概念,对一般线性群 GL(n,C)[而不是[1]的特殊线性群SL(n,C)的子群]应用群表示论中对称方和交错方等知识,得出了 n 端口网络的直积网络的一个重要性质,即采用这种网络,使信号在系统内部不互相影响的充分必要条件是 n 端口网络阵为对角阵:     

自乘零化灰阵有关定理及证明的改进

本文对文[1]中有关自乘零化灰阵的定理及其证明给出了改进，并得出了传递矩阵的计算方法。     

(d,r,z]-析取矩阵的卡氏积及其性质

二元叠加码[d,r,z]-析取矩阵是Pooling设计理论的一个极其重要的数学模型,定义了两个已知(d,r,z]-析取矩阵的卡氏积并计算了它的参数,最后介绍了它的检纠错性质.     

高等数学教学大纲(48学时)

<正> 1.矢量代数(3) 矢量,点积与矢积;矢量恒等式;直线方程与平面方程,几何学与运动学应用。2.矩阵代数(6) 矩阵定义与运算,矩阵的逆,转置,余因子,子式,秩和行列式,线性方程组的解系统,克菜姆法则,消元法。     

投影矩阵的Kronecker积及其相关的正交表

文[3]证明了当P是素数时投影矩阵τp与P水平对称正交表的矩阵象的Kronecker积所包含的正交表是存在的，本文进一步研究了一个非对称正交表的矩阵象和投影矩阵τp的Kronecker积所包含的正交表的存在性，从而推广了文[3]的结论，并且构造出了一些饱和度很高的混合水平正交表．     

矩阵 K-积不可约性的等价表征

本文借助布尔矩阵理论给出了矩阵 K-积不可约性的一个等价表征.并且据此改进了文[1]中的结果.最后,给出了一个便于应用的矩阵 K-积不可约性的充分条件.     

关于三次样条插值矩阵的非奇异性

近年来,在计算数学刊物上相继发表了许多篇关于三次插值样条存在唯一性的文章,例如[1-3].这些文章讨论的是三次样条插值矩阵为非奇异的条件.[1]中用的是凑方法,讨论了与插值矩阵相关的另一个对称阵为正定的条件,经过复杂凑方,得到了某些充分条件,[2]是用大块凑方,所得结果形式上异于[1],但实质上是完全相同的.[3]则是对插值矩阵进行一种特殊分解,得出非异的四个充分条件.它不限于[1-2]所讨论的正定情形,因而适用范围更广些.     

An analysis of the velocity updating rule of the particle swarm optimization algorithm

The particle swarm optimization algorithm includes three vectors associated with each particle: inertia, personal, and social influence vectors. The personal and social influence vectors are typically multiplied by random diagonal matrices (often referred to as random vectors) resulting in changes in their lengths and directions. This multiplication, in turn, influences the variation of the particles in the swarm. In this paper we examine several issues associated with the multiplication of personal and social influence vectors by such random matrices, these include: (1) Uncontrollable changes in the length and direction of these vectors resulting in delay in convergence or attraction to locations far from quality solutions in some situations (2) Weak direction alternation for the vectors that are aligned closely to coordinate axes resulting in preventing the swarm from further improvement in some situations, and (3) limitation in particle movement to one orthant resulting in premature convergence in some situations. To overcome these issues, we use randomly generated rotation matrices (rather than the random diagonal matrices) in the velocity updating rule of the particle swarm optimizer. This approach makes it possible to control the impact of the random components (i.e. the random matrices) on the direction and length of personal and social influence vectors separately. As a result, all the above mentioned issues are effectively addressed. We propose to use the Euclidean rotation matrices for rotation because it preserves the length of the vectors during rotation, which makes it easier to control the effects of the randomness on the direction and length of vectors. The direction of the Euclidean matrices is generated randomly by a normal distribution. The mean and variance of the distribution are investigated in detail for different algorithms and different numbers of dimensions. Also, an adaptive approach for the variance of the normal distribution is proposed which is independent from the algorithm and the number of dimensions. The method is adjoined to several particle swarm optimization variants. It is tested on 18 standard optimization benchmark functions in 10, 30 and 60 dimensional spaces. Experimental results show that the proposed method can significantly improve the performance of several types of particle swarm optimization algorithms in terms of convergence speed and solution quality.     

A generalization of imaginary parts of eigenvalues for matrices: Chain rotation numbers

Rotation numbers and chain rotation numbers may be interpreted as a generalization of the imaginary parts for matrices. In dimension two they measure how the solutions of a linear autonomous differential equation rotate in the phase space, and they reduce to the imaginary parts of the eigenvalues of the system’s matrix. In higher dimensions they measure how a two-frame of vectors rotate under the induced flow in the plane which is spanned by the frame. For their calculation, only special sets in the oriented Grassmann manifold of planes are relevant, and to each of these sets corresponds a compact interval of chain rotation numbers. In this paper we will determine these relevant sets and calculate the corresponding sets of chain rotation numbers.     

On spectral decompositions of solutions to discrete Lyapunov equations

A new approach to solving discrete Lyapunov matrix algebraic equations is based on methods for spectral decomposition of their solutions. Assuming that all eigenvalues of the matrices on the left-hand side of the equation lie inside the unit disk, it is shown that the matrix of the solution to the equation can be calculated as a finite sum of matrix bilinear quadratic forms made up by products of Faddeev matrices obtained by decomposing the resolvents of the matrices of the Lyapunov equation. For a linear autonomous stochastic discrete dynamic system, analytical expressions are obtained for the decomposition of the asymptotic variance matrix of system’s states.     

On the rotations taking one vector into another

For two given vectors of the three-dimensional Euclidean space we investigate the problem of identifying all rotations that transform them into each other. For this purpose we consider three types of rotation matrices to obtain a complete characterization. Finally some attention is paid to the problem of obtaining all rotations taking two vectors into two other vectors.     

On compact vector formats in the solution of the chemical master equation with backward differentiation

A stochastic chemical system with multiple types of molecules interacting through reaction channels can be modeled as a continuous‐time Markov chain with a countably infinite multidimensional state space. Starting from an initial probability distribution, the time evolution of the probability distribution associated with this continuous‐time Markov chain is described by a system of ordinary differential equations, known as the chemical master equation (CME). This paper shows how one can solve the CME using backward differentiation. In doing this, a novel approach to truncate the state space at each time step using a prediction vector is proposed. The infinitesimal generator matrix associated with the truncated state space is represented compactly, and exactly, using a sum of Kronecker products of matrices associated with molecules. This exact representation is already compact and does not require a low‐rank approximation in the hierarchical Tucker decomposition (HTD) format. During transient analysis, compact solution vectors in HTD format are employed with the exact, compact, and truncated generated matrices in Kronecker form, and the linear systems are solved with the Jacobi method using fixed or adaptive rank control strategies on the compact vectors. Results of simulation on benchmark models are compared with those of the proposed solver and another version, which works with compact vectors and highly accurate low‐rank approximations of the truncated generator matrices in quantized tensor train format and solves the linear systems with the density matrix renormalization group method. Results indicate that there is a reason to solve the CME numerically, and adaptive rank control strategies on compact vectors in HTD format improve time and memory requirements significantly.     

矩阵方程AV+BW=EVF的一种新的解析通解

该文给出了矩阵方程AV+BW=EVF的一种新的解析通解。该通解是一组自由参向量的显式线性表示，其系数阵是依赖于矩阵F的特征值的数值矩阵。因通解中仅含数值矩阵计算，这为应用计算机求解创造了方便。     

Fokker-planck equation for brownian motion of rotating spherical particles : PMM vol. 40, n 6, 1976, pp. 1127–1131

The Langevin equation to derive the Fokker-Planck equation is used for the Brownian motion of particles in translational motion. The Fokker-Planck equation for the Brownian motion of particles which have, in addition to the translational velocity also an angular velocity, has not, so far, been derived. This can apparently be explained by the fact that in the case of the rotational motion, the Langevin equation for the translational motion velocity vector must be supplemented by a corresponding equation for an angular velocity vector. The latter equation must contain, in addition to the systematic moment of reaction linearly dependent on the angular velocity of rotation itself, a random moment rapidly varying with time. Moreover, to ensure the compatibility of two differential vector equations within the system, additional relations which must be introduced, must connect not only the coefficients of the systematic reactions, but also the. random vectors varying rapidly with time.In [1],the Boltzmann's equation for a mixture of two gases was used to derive a Fokker-Planck equation for a translational motion of Brownian particles. The same method can be applied to the Brownian motion of spherical particles which have, in addition to the translational velocities, angular velocities of self-rotations. In this case there is no need to introduce additional relations connecting the random rapidly varying vectors.In the present paper we derive the Fokker-Planck equations for a new model of rotating spherical molecules which was used in [2].     

Sets of solution-set-invariant coefficient matrices of simple fuzzy relation equations

A set of coefficient matrices which are invariant to a solution set of a simple fuzzy relation equation is considered. The equipollency of the cardinal numbers of solution sets of simple fuzzy relation equations for two constant vectors is also shown.     

On certain decompositions of complex inverse Toeplitz matrices and related fast algorithms for solving linear systems with Toeplitz coefficient matrices

Formulas for inverting nonsingular Toeplitz matrices with complex entries are derived. These formulas either refine known ones or are new. They make it possible to develop economical algorithms for calculating products of inverse Toeplitz matrices with vectors.     

Counting matrices over finite fields having a given number of rows of unit weight

We present a formula enumerating matrices over a finite field of a given rank and a given number of rows of unit weight, i.e., each having a single nonzero entry. We also determine the number of subspaces of a given dimension containing a given number of vectors of unit weight.