On common unital divisors of polynomial matrices

We establish a condition for the existence of common unital divisors of polynomial matrices over an arbitrary field, with the divisors having a prescribed characteristic polynomial. The results obtained are applied to find a common solution of matrix polynomial equations.Translated fromMatematichni Metodi ta Fiziko-Mekhanichni Polya, Vol. 40, No. 3, 1997, pp. 20–24.     

线性时不变系统两种描述的等价性

自从Kalman提出了用状态空间方法描述系统后,Rosenbrock与Wolovich等又提出了用微分算子描述系统的方法。这两种描述方法,利用各自表示方法的特点,在多变量系统理论的研究上,都取得了很大的进展。 本文利用Yokoyama标准形与多项式矩阵之间的关系,把上述两种描述联系起来,给出了它们之间等价的转换形式。这样就可以把在一种描述方法上得到的结果,等价地搬到另一种描述方法的系统上去。     

Spectral factorization of non-symmetric polynomial matrices

The topic of the paper is spectral factorization of rectangular and possibly non-full-rank polynomial matrices. To each polynomial matrix we associate a matrix pencil by direct assignment of the coefficients. The associated matrix pencil has its finite generalized eigenvalues equal to the zeros of the polynomial matrix. The matrix dimensions of the pencil we obtain by solving an integer linear programming (ILP) minimization problem. Then by extracting a deflating subspace of the pencil we come to the required spectral factorization. We apply the algorithm to most general-case of inner–outer factorization, regardless continuous or discrete time case, and to finding the greatest common divisor of polynomial matrices.     

Congenial matrices

For a given polynomial in the usual power form, its associated companion matrix can be applied to investigate qualitative properties, such as the location of the roots of the polynomial relative to regions of the complex plane, or to determine the greatest common divisor of a set of polynomials. If the polynomial is in “generalized” form, i.e. expressed relative to an orthogonal basis, then an analogue to the companion matrix has been termed the comrade form. This followed a special case when the basis is Chebyshev, for which the term colleague matrix had been introduced. When a yet more general basis is used, the corresponding matrix has been named confederate. These constitute the class of congenial matrices, which allow polynomials to be studied relative to an appropriate basis. Block-partitioned forms relate to polynomial matrices.     

Problems of control and information theory (Hungary)

The bezoutian matrix, which provides information concerning co-primeness and greatest common divisor of polynomials, has recently been generalized by Heinig to the case of square polynomial matrices. Some of the properties of the bezoutian for the scalar case then carry over directly. In particular, the central result of the paper is an extension of a factorization due to Barnett, which enables the bezoutian to be expressed in terms of a Kronecker matrix polynomial in an appropriate block companion matrix. The most important consequence of this result is a determination of the structure of the kernel of the bezoutian. Thus, the bezoutian is nonsingular if and only if the two polynomial matrices have no common eigenvalues (i.e., their determinants are relatively prime); otherwise, the dimension of the kernel is given in terms of the multiplicities of the common eigenvalues of the polynomial matrices. Finally, an explicit basis is developed for the kernel of the bezoutian, using the concept of Jordan chains.     

Greatest common divisor of generalized polynomials and polynomial matrices

The comrade matrix was introduced recently as the analogue of the companion matrix when a polynomial is expressed in terms of a basis set of orthogonal polynomials. It is now shown how previous results on determining the greatest common divisor of two or more polynomials can be extended to the case of generalized polynomials using the comrade form. Furthermore, a block comrade matrix is defined, and this is used to extend to the generalized case another previous result on the regular greatest common divisor of two polynomial matrices.     

A recursive algorithm for constructing complicated Dixon matrices

Whether the determinant of the Dixon matrix equals zero or not is used for determining if a system of n + 1 polynomial equations in n variables has a common root, and is a very efficient quantifier elimination approach too. But for a complicated polynomial system, it is not easy to construct the Dixon matrix. In this paper, a recursive algorithm to construct the Dixon matrix is proposed by which some problems that cannot be tackled by other methods can be solved on the same computer platform. A dynamic programming algorithm based on the recursive formula is developed and compared for speed and efficiency to the recursive algorithm.     

An extended fast algorithm for constructing the Dixon resultant matrix

In recent years,the Dixon resultant matrix has been used widely in the re-sultant elimination to solve nonlinear polynomial equations and many researchers havestudied its efficient algorithms.The recursive algorithm is a very efficient algorithm,butwhich deals with the case of three polynomial equations with two variables at most.Inthis paper,we extend the algorithm to the general case of n 1 polynomial equations in nvariables.The algorithm has been implemented in Maple 9.By testing the random polyno-mial equations,the results demonstrate that the efficiency of our program is much betterthan the previous methods,and it is exciting that the necessary condition for the existenceof common intersection points on four general surfaces in which the degree with respectto every variable is not greater than 2 is given out in 48×48 Dixon matrix firstly by ourprogram.     

Applications of the generalized Sylvester matrix

Recently a Sylvester matrix for several polynomials has been defined, establishing the relative primeness and the greatest common divisor of polynomials. Using this matrix, we perform qualitative analysis of several polynomials regarding the inners, the bigradients, Trudi's theorem, and the connection of inners and the Schur complement. Also it is shown how the regular greatest common divisor of m+1 (m>1) polynomial matrices can be determined.     

求首尾和r-循环矩阵的极小多项式的算法

研究了域上首尾和r-循环矩阵，利用多项式环的理想的Groebner基的算法给出了任意域上首尾和r-循环矩阵的极小多项式和公共极小多项式的一种算法.同时给出了这类矩阵逆矩阵的一种求法。     

An approach to solving multiparameter algebraic problems

An approach to solving the following multiparameter algebraic problems is suggested: (1) spectral problems for singular matrices polynomially dependent on q≥2 spectral parameters, namely: the separation of the regular and singular parts of the spectrum, the computation of the discrete spectrum, and the construction of a basis that is free of a finite regular spectrum of the null-space of polynomial solutions of a multiparameter polynomial matrix; (2) the execution of certain operations over scalar and matrix multiparameter polynomials, including the computation of the GCD of a sequence of polynomials, the division of polynomials by their common divisor, and the computation of relative factorizations of polynomials; (3) the solution of systems of linear algebraic equations with multiparameter polynomial matrices and the construction of inverse and pseudoinverse matrices. This approach is based on the so-called ΔW-q factorizations of polynomial q-parameter matrices and extends the method for solving problems for one- and two-parameter polynomial matrices considered in [1–3] to an arbitrary q≥2. Bibliography: 12 titles. Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 229, 1995, pp. 191–246. Translated by V. N. Kublanovskaya.     

矩阵多项式秩的和的恒等式及其应用

证明了矩阵A的两个多项式秩的和等于它们最大公因式与最小公倍式秩的和,这个结果不仅可以概括近期文献的相关工作,而且可以对应用矩阵多项式求逆矩阵的方法作进一步的研究,同时也可使关于矩阵秩恒等式的最新讨论获得一种简单统一的处理方法.     

Polynomial numerical hulls of matrix polynomials,II

In this article, we study some algebraic and geometrical properties of polynomial numerical hulls of matrix polynomials and joint polynomial numerical hulls of a finite family of matrices (possibly the coefficients of a matrix polynomial). Also, we study polynomial numerical hulls of basic A-factor block circulant matrices. These are block companion matrices of particular simple monic matrix polynomials. By studying the polynomial numerical hulls of the Kronecker product of two matrices, we characterize the polynomial numerical hulls of unitary basic A-factor block circulant matrices.     

Common multiples and common divisors of matrix polynomials, II. Vandermonde and resultant matrices

In this paper explicit formulas are given for least common multiples and greatest common divisors of a finite number of matrix polynomials in terms of the coefficients of the given polynomials. An important role is played by block matrix generalizations of the classical Vandermonde and resultant matrices. Special attention is given to the evaluation of the degrees and other characteristics. Applications to matrix polynomial equations and factorization problems are made.     

Divisibility and one-sided equivalence of polynomial matrices

A criterion is established for the one-sided equivalence of polynomial matrices; over an arbitrary field. If B(x) is a polynomial matrix of maximal rank, then a condition for the divisibility of a polynomial matrix A(x) by B(x) without a remainder, is indicated. For a square polynomial matrix, necessary and sufficient conditions for the one-sided equivalence of it to a unitary polynomial matrix are presented, and also a method is proposed for its construction.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 42, No. 9, pp. 1213–1219, September, 1990.     

The matrix equation XA=ATX and an associated algorithm for solving the inertia and stability problems

We develop a constructive procedure for generating nonsingular solutions of the matrix equation XA=A^TX and establish an interesting relationship between a given solution X of the above equation and the associated matrix polynomial p(A). The latter is then used to develop an algorithm for computing the inertia of a matrix. The algorithm is more efficient than the other common procedures.     

Polynomial Fibonacci–Hessenberg matrices

A Fibonacci–Hessenberg matrix with Fibonacci polynomial determinant is referred to as a polynomial Fibonacci–Hessenberg matrix. Several classes of polynomial Fibonacci–Hessenberg matrices are introduced. The notion of two-dimensional Fibonacci polynomial array is introduced and three classes of polynomial Fibonacci–Hessenberg matrices satisfying this property are given.     

To Solving Multiparameter Problems of Algebra. 4. The AB-Algorithm and its Applications

The paper continues the investigation of methods for factorizing q-parameter polynomial matrices and considers their applications to solving multiparameter problems of algebra. An extension of the AB-algorithm, suggested earlier as a method for solving spectral problems for matrix pencils of the form A - λB, to the case of q-parameter (q ≥ 1) polynomial matrices of full rank is proposed. In accordance with the AB-algorithm, a finite sequence of q-parameter polynomial matrices such that every subsequent matrix provides a basis of the null-space of polynomial solutions of its transposed predecessor is constructed. A certain rule for selecting specific basis matrices is described. Applications of the AB-algorithm to computing complete polynomials of a q-parameter polynomial matrix and exhausting them from the regular spectrum of the matrix, to constructing irreducible factorizations of rational matrices satisfying certain assumptions, and to computing “free” bases of the null-spaces of polynomial solutions of an arbitrary q-parameter polynomial matrix are considered. Bibliography: 7 titles. __________ Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 309, 2004, pp. 127–143.     

Solution of spectral problems for polynomial matrices

For polynomial matrices of full rank, including matrices of the form A - I and A - B, numerical methods for solving the following problems are suggested: find the divisors of a polynomial matrix whose spectra coincide with the zeros of known divisors of its characteristic polynomial; compute the greatest common divisor of a sequence of polynomial matrices; solve the inverse eigenvalue problem for a polynomial matrix. The methods proposed are based on the W and V factorizations of polynomial matrices. Applications of these methods to the solution of certain algebraic problems are considered. Bibliography: 3 titles._________Translated from Zapiski Nauchnykh Seminarov POMI, Vol. 296, 2003, pp. 122–138.     

多项式的最大公因式的一种新求法

本文介绍了一种利用数域上矩阵的初等行变换求一组一元ｎ次多项式的最大公因式的方法．