Kronecker Product Of Matrices Research Articles

Kronecker product of matrices and solutions of Sylvestertype matrix polynomial equations

We investigate the solutions of the Sylvester-type matrix polynomial equation $$A(\lambda)X(\lambda)+Y(\lambda)B(\lambda)=C(\lambda),$$ where\ $A(\lambda),$ \ $ B(\lambda),$\ and \ $C(\lambda)$ are the polynomial matrices with elements in a ring of polynomials \ $\mathcal{F}[\lambda],$ \ $\mathcal{F}$ is a field,\ $X(\lambda)$\ and \ $Y(\lambda)$ \ are unknown polynomial matrices. Solving such a matrix equation is reduced to the solving a system of linear equations $$G \left\|\begin{array}{c}\mathbf{x} \\ \mathbf{y} \end{array} \right\|=\mathbf{c}$$ over a field $\mathcal{F}.$ In this case, the Kronecker product of matrices is applied. In terms of the ranks of matrices over a field $\mathcal{F},$ which are constructed by the coefficients of the Sylvester-type matrix polynomial equation,the necessary and sufficient conditions for the existence of solutions \ $X_0(\lambda)$\ and \ $Y_0(\lambda)$ \ of given degrees to the Sylvester-type matrix polynomial equation are established. The solutions of this matrix polynomial equation are constructed from the solutions of the linear equations system.As a consequence of the obtained results, we give the necessary and sufficient conditions for the existence of the scalar solutions \ $X_0$\ and \ $Y_0,$ \ whose entries are elements in a field $\mathcal{F},$ to the Sylvester-type matrix polynomial equation.

Structure and Approximation Properties of Laplacian-Like Matrices

Many of today’s problems require techniques that involve the solution of arbitrarily large systems Atextbf{x}=textbf{b}. A popular numerical approach is the so-called Greedy Rank-One Update Algorithm, based on a particular tensor decomposition. The numerical experiments support the fact that this algorithm converges especially fast when the matrix of the linear system is Laplacian-Like. These matrices that follow the tensor structure of the Laplacian operator are formed by sums of Kronecker product of matrices following a particular pattern. Moreover, this set of matrices is not only a linear subspace it is a Lie sub-algebra of a matrix Lie Algebra. In this paper, we characterize and give the main properties of this particular class of matrices. Moreover, the above results allow us to propose an algorithm to explicitly compute the orthogonal projection onto this subspace of a given square matrix A in mathbb {R}^{Ntimes N}.

Semi-Blind Receivers for Two-Hop MIMO Relay Systems with a Combined TSTF-MSMKron Coding.

Due to the increase in the number of mobile stations in recent years, cooperative relaying systems have emerged as a promising technique for improving the quality of fifth-generation (5G) wireless networks with an extension of the coverage area. In this paper, we propose a two-hop orthogonal frequency division multiplexing and code-division multiple-access (OFDM-CDMA) multiple-input multiple-output (MIMO) relay system, which combines, both at the source and relay nodes, a tensor space-time-frequency (TSTF) coding with a multiple symbol matrices Kronecker product (MSMKron), called TSTF-MSMKron coding, aiming to increase the diversity gain. It is first established that the signals received at the relay and the destination satisfy generalized Tucker models whose core tensors are the coding tensors. Assuming the coding tensors are known at both nodes, tensor models are exploited to derive two semi-blind receivers, composed of two steps, to jointly estimate symbol matrices and individual channels. Necessary conditions for parameter identifiability with each receiver are established. Extensive Monte Carlo simulation results are provided to show the impact of design parameters on the symbol error rate (SER) performance, using the zero-forcing (ZF) receiver. Next, Monte Carlo simulations illustrate the effectiveness of the proposed TSTF-MSMKron coding and semi-blind receivers, highlighting the benefit of exploiting the new coding to increase the diversity gain.

New facts related to dilation factorizations of Kronecker products of matrices

<abstract><p>The Kronecker product of two matrices is known as a special algebraic operation of two arbitrary matrices in the computational aspect of matrix theory. This kind of matrix operation has some interesting and striking operation properties, one of which is given by $ (A \otimes B)(C \otimes D) = (AC) \otimes (BD) $ and is often called the mixed-product equality. In view of this equality, the Kronecker product $ A_1 \otimes A_2 $ of any two matrices can be rewritten as the dilation factorization $ A_1 \otimes A_2 = (A_1 \otimes I_{m_2})(I_{n_1} \otimes A_2) $, and the Kronecker product $ A_1 \otimes A_2 \otimes A_3 $ can be rewritten as the dilation factorization $ A_1 \otimes A_2 \otimes A_3 = (A_1\otimes I_{m_2} \otimes I_{m_3})(I_{n_1} \otimes A_2 \otimes I_{m_3})(I_{n_1} \otimes I_{n_2} \otimes A_3) $. In this article, we proposed a series of concrete problems regarding the dilation factorizations of the Kronecker products of two or three matrices, and established a collection of novel and pleasing equalities, inequalities, and formulas for calculating the ranks, dimensions, orthogonal projectors, and ranges related to the dilation factorizations. We also present a diverse range of interesting results on the relationships among the Kronecker products $ I_{m_1} \otimes A_2 \otimes A_3 $, $ A_1 \otimes I_{m_2} \otimes A_3 $ and $ A_1 \otimes A_2 \otimes I_{m_3} $.</p></abstract>

Hybrid Kronecker Product Decomposition and Approximation

Discovering underlying low dimensional structure of a high-dimensional matrix is traditionally done through low rank matrix approximations in the form of a sum of rank-one matrices. In this article, we propose a new approach. We assume a high-dimensional matrix can be approximated by a sum of a small number of Kronecker products of matrices with potentially different configurations, named as a hybrid Kronecker outer Product Approximation (hKoPA). It provides an extremely flexible way of dimension reduction compared to the low-rank matrix approximation. Challenges arise in estimating a hKoPA when the configurations of component Kronecker products are different or unknown. We propose an estimation procedure when the set of configurations are given, and a joint configuration determination and component estimation procedure when the configurations are unknown. Specifically, a least squares backfitting algorithm is used when the configurations are given. When the configurations are unknown, an iterative greedy algorithm is developed. Both simulation and real image examples show that the proposed algorithms have promising performances. Some identifiability conditions are also provided. The hybrid Kronecker product approximation may have potentially wider applications in low dimensional representation of high-dimensional data. Supplementary materials for this article are available online.

Inequalities for the Kronecker product of matrices

Inequalities for the Kronecker product of matrices

An Efficient Method for Split Quaternion Matrix Equation X − Af(X)B = C

In this paper, we consider the split quaternion matrix equation X−Af(X)B=C, f(X)∈{X,XH,XiH,XjHXkH}. The H representation method has the characteristics of transforming a matrix with a special structure into a column vector with independent elements. By using the real representation of split quaternion matrices, H representation method, the Kronecker product of matrices and the Moore-Penrose generalized inverse, we convert the split quaternion matrix equation into the real matrix equation, and derive the sufficient and necessary conditions and the general solution expressions for the (skew) bisymmetric solution of the original equation. Moreover, we provide numerical algorithms and illustrate the efficiency of our method by two numerical examples.

On the Stabilization of a Network of a Class of SISO Coupled Hybrid Linear Subsystems via Static Linear Output Feedback

This paper deals with the closed-loop stabilization of a network which consists of a set of coupled hybrid single-input single-output (SISO) subsystems. Each hybrid subsystem involves a continuous-time subsystem together with a digital (or, eventually, discrete-time) one being subject to eventual mutual couplings of dynamics and also to discrete delayed dynamics. The stabilizing controller is static and based on linear output feedback. The controller synthesis method is of algebraic type and based on the use of a linear algebraic system, whose unknown is a vector equivalent form of the controller gain matrix, which is obtained from a previous algebraic problem version which is based on the ad hoc use of the matrix Kronecker product of matrices. As a first step of the stabilization, an extended discrete-time system is built by discretizing the continuous parts of the hybrid system and to unify them together with its digital/discrete-time ones. The stabilization study via static linear output feedback contains several parts as follows: (a) stabilizing controller existence and controller synthesis for a predefined targeted closed-loop dynamics, (b) stabilizing controller existence and its synthesis under necessary and sufficient conditions based on the statement of an ad hoc algebraic matrix equation for this problem, (c) achievement of the stabilization objective under either partial or total decentralized control so that the whole controller has only a partial or null information about couplings between the various subsystems and (d) achievement of the objective under small coupling dynamics between subsystems.

The Lorentz group and the Kronecker product of matrices

The group of all complex 2 × 2 matrices with determinant one is closely related to the group of real 4 × 4 matrices representing the restricted Lorentz transformations. This relation, sometimes called the spinor map, is of fundamental importance in relativistic quantum mechanics and has applications also in general relativity. In this paper we show how the spinor map may be expressed in terms of pure matrix algebra by including the Kronecker product between matrices in the formalism. The so-obtained formula for the spinor map may be manipulated by matrix algebra and used in the study of Lorentz transformations.

Kronecker Product of Matrices and Applications to Two-Point Boundary Value Problems Associated With First Order Matrix Difference Systems

This paper presents a criteria for the existence and uniqueness of solutions to two-point boundary value problems associated with a system of Kronecker product first order differential equation. Some of the natural questions on Kronecker product of matrices about seemingly“simple” cases are still unansweredin spite of their increasing interest and hence some significant results on Kronecker product of matrices are answered in this paper. We mainly explain a set of necessary and sufficient conditions on the decomposition of a matrix into Kronecker product of two matrices.

Kronecker Product of matrices and their applications to self-adjoint two-point boundary value problems associated with first order matrix differential systems

In this paper, we shall be concerned with Kronecker product or Tensor product of matrices and develop their properties in a systematic way. The properties of the Kronecker product of matrices is used as a tool to establish existence and uniqueness of solutions to two-point boundary value problems associated with system of first order differential systems. A new approach is described to solve the Kronecker product linear systems and establish best least square solutions to the problem. Several interesting examples are given to highlight the importance of Kronecker product of matrices. We present adjoint boundary value problems and deduce a set of necessary and sufficient conditions for the Kronecker product boundary value problem to be self-adjoint.

Multidimensional Arrays, Indices and Kronecker Products

Much of the algebra that is associated with the Kronecker product of matrices has been rendered in the conventional notation of matrix algebra, which conceals the essential structures of the objects of the analysis. This makes it difficult to establish even the most salient of the results. The problems can be greatly alleviated by adopting an orderly index notation that reveals these structures. This claim is demonstrated by considering a problem that several authors have already addressed without producing a widely accepted solution.

An explicit expression for Euclidean self-dual cyclic codes of length 2k over Galois ring GR(4,m)

For any positive integers m and k, existing literature only determines the number of all Euclidean self-dual cyclic codes of length 2k over the Galois ring GR(4,m), such as in Kiah et al. (2012) [17]. Using properties for Kronecker products of matrices of a specific type and column vectors of these matrices, we give a simple and efficient method to construct all these self-dual cyclic codes precisely. On this basis, we provide an explicit expression to represent accurately all distinct Euclidean self-dual cyclic codes of length 2k over GR(4,m), using binomial coefficients. As an application, we list all distinct Euclidean self-dual cyclic codes over GR(4,m) of length 2k explicitly, for k=4,5,6.

Solution of the symmetric band partial inverse eigenvalue problem for the damped mass spring system

ABSTRACT The structured partial quadratic inverse eigenvalue problem (SPQIEP) is to construct the structured quadratic matrix polynomial using the partial eigendata. The structures arising in physical applications include symmetry, band (tridiagonal, diagonal, pentagonal) etc. The construction of the structured matrix polynomial is the most difficult aspect of this problem and the research on structured inverse eigenvalue problem is rare. In this paper, the symmetric band partial quadratic inverse eigenvalue problem (SBPQIEP) for the damped mass spring system is considered. This problem concerns in finding the symmetric band matrices , and C with bandwidth p from m ( ) prescribed eigenpairs so that the corresponding quadratic matrix polynomial has the given eigenpairs as its eigenvalues and eigenvectors. In general, SBPQIEP is very hard to solve due to the additional band structure constraint. We propose a novel method, based on the matrix-vectorization and Kronecker product of matrices for solving this problem. Furthermore, explicit expressions for general solutions are presented. Numerical experiments on a spring mass problem are presented to illustrate the applicability and the practical usefulness of the proposed method.

An efficient solver for space–time isogeometric Galerkin methods for parabolic problems

In this work we focus on the preconditioning of a Galerkin space–time isogeometric discretization of the heat equation. Exploiting the tensor product structure of the basis functions in the parametric domain, we propose a preconditioner that is the sum of Kronecker products of matrices and that can be efficiently applied thanks to an extension of the classical Fast Diagonalization method. The preconditioner is robust w.r.t. the polynomial degree of the spline space and the time required for the application is almost proportional to the number of degrees-of-freedom, for a serial execution. By incorporating some information on the geometry parametrization and on the equation coefficients, we keep high efficiency with non-trivial domains and variable thermal conductivity and heat capacity coefficients.

Three-associate class partially balanced incomplete block designs through kronecker product

Kronecker product of matrices can be advantageously used to obtain three-associate class partially balanced incomplete block (PBIB) designs from two-associate class PBIB designs, for a larger number of treatments. This method has been described here and two such series of PBIB designs are obtained. If the experimenter is constrained of resources, theses designs can be used as an alternative to balanced incomplete block designs or 2-associate class partially balanced incomplete block designs.

Using the kronecker product of matrices for modification cryptographic algorithm

Using the kronecker product of matrices for modification cryptographic algorithm

Least-squares bihermitian and skew bihermitian solutions of the quaternion matrix equation AXB = C

In this paper, by using the special structure of the real representation of quaternion matrices, the properties of the Moore–Penrose inverse of quaternion matrices and the Kronecker product of matrices, we study least-squares bihermitian and skew bihermitian solutions of the quaternion matrix equation AXB = C, respectively. First we study the special structures of quaternion bihermitian and skew bihermitian matrices. Then the problem of solving the least-squares bihermitian and skew bihermitian solutions of the quaternion matrix equation AXB = C can be transformed into particular real linear system using these special structures. We deduce the form of all least-squares bihermitian and skew bihermitian solutions of the quaternion matrix equation AXB = C and propose real structure-preserving algorithms to compute the minimal norm least-squares bihermitian and skew bihermitian solution. All the computation process only involve real arithmetic. Numerical examples are provided to verify the effectiveness of our algorithms. Particularly, we also propose the conditions and computation method of bihermitian and skew bihermitian solutions of quaternion matrix equation AXB = C.

An efficient method to construct self-dual cyclic codes of length [formula omitted] over [formula omitted

Let p be any odd prime number, m and s be arbitrary positive integers, and let Fpm be the finite field of cardinality pm. Existing literature only determines the number of all (Euclidean) self-dual cyclic codes of length ps over finite chain ring R=Fpm+uFpm(u2=0), such as Dinh et al. (2018). Using some combinatorial identities, we obtain certain properties for Kronecker product of matrices over Fp with a specific type. On that basis, we give an explicit representation and enumeration for all distinct self-dual cyclic codes of length ps over R. Moreover, we provide an efficient method to construct every self-dual cyclic code of length ps over R precisely.

On the Ψ-asymptotic equivalence of the Ψ-bounded solutions of two Lyapunov matrix differential equations

Using Schauder Tychonoff fixed point theorem and the technique of Kronecker product of matrices, we prove existence results for Ψ-asymptotic equivalence of the Ψ-bounded solutions of two Lyapunov matrix differential equations.