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Abstract: This paper gives a group of expansion formulas for the inertias of Hermitian matrix polynomials , and through some congruence transformations for block matrices, where A is a Hermitian matrix. Then, the paper derives various expansion formulas for the ranks and inertias of some matrix pencils generated from two or three orthogonal projectors and Hermitian unitary matrices. As applications, the paper establishes necessary and sufficient conditions for many matrix equalities to hold, as well as many inequalities in the Löwner partial ordering to hold. [Copyright &y& Elsevier]

We introduce a simultaneous decomposition for a matrix triplet ( A, B, C), where A=± A and (⋅) denotes the conjugate transpose of a matrix, and use the simultaneous decomposition to solve some conjectures on the maximal and minimal values of the ranks of the matrix expressions A− BXC±( BXC) with respect to a variable matrix X. In addition, we give some explicit formulas for the maximal and minimal values of the inertia of the matrix expression A− BXC−( BXC) with respect to X. As applications, we derive the extremal ranks and inertias of the matrix expression D− CXC subject to Hermitian solutions of a consistent matrix equation AXA= B, as well as the extremal ranks and inertias of the Hermitian Schur complement D− B A B with respect to a Hermitian generalized inverse A of A. Various consequences of these extremal ranks and inertias are also presented in the paper. [ABSTRACT FROM AUTHOR]

Abstract: When an edge is removed from an undirected graph, there is a limited change that can occur in the multiplicity of an eigenvalue of a Hermitian matrix with that graph. Primarily for trees, we identify the changes that can occur and characterize the circumstances under which they occur. This extends known results for the removal of vertices. A catalog of examples is given to illustrate the possibilities that can occur and to contrast the case of trees with that of general graphs. [ABSTRACT FROM AUTHOR]

Abstract: The extremal ranks of matrix expression of A − BXC with respect to X H = X have been discussed by applying the quotient singular value decomposition Q-SVD and some rank equalities of matrices in this paper. [Copyright &y& Elsevier]

Abstract: We consider products of unitary operators with at most two points in their spectra, 1 and . We prove that the scalar operator is a product of k such operators if for . Also we prove that for , only a countable number of scalar operators can be decomposed in a product of four operators from the mentioned class. As a corollary we show that every unitary operator on an infinite-dimensional space is a product of finitely many such operators. [Copyright &y& Elsevier]

Abstract: Polygon transformations based on taking the apices of similar triangles constructed on the sides of an initial polygon are analyzed as well as the limit polygons obtained by iteratively applying such transformations. In contrast to other approaches, this is done with respect to two construction parameters representing a base angle and an apex perpendicular subdivision ratio. Furthermore, a combined transformation leading to circulant Hermitian matrices is proposed, which eliminates the rotational effect of the basic transformation. A finite set of characteristic parameter subdomains is derived for which the sequence converges to specific eigenpolygons. Otherwise, limit polygons turn out to be linear combinations of up to three eigenpolygons. This leads to a full classification of circulant Hermitian similar triangles based polygon transformations and their limit polygons. As a byproduct classical results as Napoleon’s theorem and the Petr–Douglas–Neumann theorem can be easily deduced. [Copyright &y& Elsevier]

Abstract: The inertia of a Hermitian matrix is defined to be a triplet composed of the numbers of the positive, negative and zero eigenvalues of the matrix counted with multiplicities, respectively. In this paper, we show some basic formulas for inertias of block Hermitian matrices. From these formulas, we derive various equalities and inequalities for inertias of sums, parallel sums, products of Hermitian matrices, submatrices in block Hermitian matrices, differences of outer inverses of Hermitian matrices. As applications, we derive the extremal inertias of the linear matrix expression with respect to a variable Hermitian matrix X. In addition, we give some results on the extremal inertias of Hermitian solutions to the matrix equation , as well as the extremal inertias of a partial block Hermitian matrix. [Copyright &y& Elsevier]

Abstract: Denote by a graph which is the vertex set and is an adjacency relation on a subset of . In this paper, the good distance graph is defined. Let and be two good distance graphs, and be a map. The following theorem is proved: is a graph isomorphism is a bounded distance preserving surjective map in both directions is a distance preserving surjective map in both directions (where is a positive integer), etc. Let be a division ring with an involution such that both and is not a field of characteristic 2 with , where and is the center of . Let be the set of Hermitian matrices over . It is proved that is a good distance graph, where for all . [Copyright &y& Elsevier]

Abstract: In this paper, we obtain some new inequalities by means of the mean inequalities of random variables, which include generalizations of the Greub–Rheinboldt inequality. [Copyright &y& Elsevier]

A bordered matrix is a two-by-two partitioned matrix with its lower-right corner equal to a null matrix. In this article, we present eight partitioned matrices consisting of the Moore-Penrose inverses of submatrices in a bordered matrix, and give necessary and sufficient conditions for the eight partitioned matrices to be generalized inverses of the bordered matrix. [ABSTRACT FROM AUTHOR]

Abstract: It is shown that any map which preserves adjacency on hermitian matrices over a finite field is necessary bijective and hence of the standard form. [Copyright &y& Elsevier]

Abstract: A formula for the inverse of any nonsingular matrix partitioned into two-by-two blocks is derived through a decomposition of the matrix itself and generalized inverses of the submatrices in the matrix. The formula is then applied to three matrix inverse completion problems to obtain their complete solutions. [Copyright &y& Elsevier]

In this note, for a system of q matrix equations of the form we consider the problem of the existence of Hermitian nonnegative-definite solutions. We offer an alternative with simplification and regularity to the result on necessary and sufficient conditions for the above matrix equations with q = 2 to have a Hermitian nonnegative-definite solution obtained by Zhang [1], who proposed a revised version of Young et al. [2]. Moreover, we give a necessary condition for the general case and then put forward a conjecture, with which at least some special situations are in agreement. [ABSTRACT FROM AUTHOR]

Abstract: Necessary and sufficient conditions are derived for a 2-by-2 partitioned matrix to have {1}-, {1,2}-, {1,3}-, {1,4}-inverses and the Moore–Penrose inverse with Banachiewicz–Schur forms. As applications, the Banachiewicz–Schur forms of {1}-, {1,2}-, {1,3}-, {1,4}-inverses and the Moore–Penrose inverse of a 2-by-2 partitioned Hermitian matrix are also given. [Copyright &y& Elsevier]

We present eigenvalue bounds for perturbations of Hermitian matrices and express the change in eigenvalues in terms of a projection of the perturbation onto a particular eigenspace, rather than in terms of the full perturbation. The perturbations we consider are Hermitian of rank one, and Hermitian or non-Hermitian with norm smaller than the spectral gap of a specific eigenvalue. Applications include principal component analysis under a spiked covariance model, and pseudo-arclength continuation methods for the solution of nonlinear systems. [ABSTRACT FROM AUTHOR]

We investigate necessary and sufficient conditions for semiconvergence of a splitting for solving singular linear systems, where the coefficient matrix A is a singular EP matrix. When A is a singular Hermitian matrix, necessary and sufficient conditions for semiconvergence of P-regular splittings are given, which generalize known results. As applications, the necessary and sufficient conditions for semiconvergence of block AOR and SSOR iterative methods are derived. A numerical example is given to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we investigate the additive, multiplicative and general splitting iteration methods for solving singular linear systems. When the coefficient matrix is Hermitian, the semiconvergence conditions are proposed, which generalize some results of Bai [Z.-Z. Bai, On the convergence of additive and multiplicative splitting iterations for systems of linear equations, J. Comput. Appl. Math. 154 (2003) 195–214] for the nonsingular linear systems to the singular systems. [Copyright &y& Elsevier]

Abstract: In this paper, by using normal maps originated by Lewis [A.S. Lewis, Group invariance and convex matrix analysis, SIAM J. Matrix Anal. Appl. 17 (1996) 927–949], we present a method for producing majorization inequalities on eigenvalues and singular values of matrices. Some classical and new inequalities are derived. [Copyright &y& Elsevier]

Abstract: We study theoretical properties of two inexact Hermitian/skew-Hermitian splitting (IHSS) iteration methods for the large sparse non-Hermitian positive definite system of linear equations. In the inner iteration processes, we employ the conjugate gradient (CG) method to solve the linear systems associated with the Hermitian part, and the Lanczos or conjugate gradient for normal equations (CGNE) method to solve the linear systems associated with the skew-Hermitian part, respectively, resulting in IHSS(CG, Lanczos) and IHSS(CG, CGNE) iteration methods, correspondingly. Theoretical analyses show that both IHSS(CG, Lanczos) and IHSS(CG, CGNE) converge unconditionally to the exact solution of the non-Hermitian positive definite linear system. Moreover, their contraction factors and asymptotic convergence rates are dominantly dependent on the spectrum of the Hermitian part, but are less dependent on the spectrum of the skew-Hermitian part, and are independent of the eigenvectors of the matrices involved. Optimal choices of the inner iteration steps in the IHSS(CG, Lanczos) and IHSS(CG, CGNE) iterations are discussed in detail by considering both global convergence speed and overall computation workload, and computational efficiencies of both inexact iterations are analyzed and compared deliberately. [Copyright &y& Elsevier]

Stępniak [Linear Algebra Appl. 151 (1991)] considered the problem of equivalence of the Löwner partial order of nonnegative definite matrices and the Löwner partial order of squares of those matrices. The paper was an important starting point for investigations of the problem of how an order between two matrices A and B from different sets of matrices can be preserved for the squares of the corresponding matrices A2 and B2, in the sense of the Löwner partial ordering, the star partial ordering, the minus partial ordering, and the sharp partial ordering. Many papers have since been published (mostly coauthored by J.K. Baksalary - to whom the present paper is dedicated) that generalize the results in two directions: by widening the class of matrices considered and by replacing the squares by arbitrary powers. In the present paper we make a résumé of some of these results and suggest some further generalizations for polynomials of the matrices considered. [ABSTRACT FROM AUTHOR]

Suppose [image omitted] is a field with proper involution and of arbitrary characteristic. Additive maps, which do not increase rank-one on hermitian matrices with entries from [image omitted] are classified. The result is then used to classify additive maps that do not increase minimal rank on the set of symmetric elements, relative to general involution on a matrix algebra. [ABSTRACT FROM AUTHOR]

Abstract: In an earlier paper Srivastava [2005. Combinatorial Hermitian Algebras Derived from Latin Squares. J. Statist. Plann. Inference 129, 305–316], subsequently referred to as [S05], the author had presented an infinite class of algebras of Hermitian matrices. Each of these algebras were derived from Latin Squares. In this paper, we show how to obtain a unitary matrix (over the complex field) such that is a diagonal matrix, for all matrices belonging to a particular algebra. The notation is defined in the next paragraph. The said diagonal matrix is a matrix that contains the characteristic roots of . The matrix may be different for different algebras. Many other related results are also presented. The algebras are further discussed. How the Hermitian matrices arise in Quantum Mechanics (where every observable attribute of every physical phenomenon is in a sense characterized by a Hermitian matrix) is briefly described. The significance of the existence of Hermitian algebras and the application to Physics and Chemistry is pointed out. [Copyright &y& Elsevier]

We show that any n × n conjugate-normal matrix can be brought by a unitary congruence transformation to block-tridiagonal form with the orders of the consecutive diagonal blocks not exceeding 1, 2, 3, ..., respectively. The proof is constructive; namely, a finite process is described that implements the reduction to the desired form. Sufficient conditions are indicated for the orders of the diagonal blocks to stabilize. In this case, the condensed form is a band matrix. [ABSTRACT FROM AUTHOR]

We propose a quadratically convergent algorithm for computing the invariant subspaces of an Hermitian matrix. Each iteration of the algorithm consists of one matrix-matrix multiplication and one QR decomposition. We present an accurate convergence analysis of the algorithm without using the big O notation. We also propose a general framework based on implicit rational transformations which allows us to make connections with several existing algorithms and to derive classes of extensions to our basic algorithm with faster convergence rates. Several numerical examples are given which compare some aspects of the existing algorithms and the new algorithms. [ABSTRACT FROM AUTHOR]

Abstract: Two Hermitian matrices are said to be Hermitian-congruent if there exists a nonsingular Hermitian matrix such that . In this paper, we give necessary and sufficient conditions for two nonsingular simultaneously unitarily diagonalizable Hermitian matrices A and B to be Hermitian-congruent. Moreover, when A and B are Hermitian-congruent, we describe the possible inertias of the Hermitian matrices C that carry the congruence. We also give necessary and sufficient conditions for any 2-by-2 nonsingular Hermitian matrices to be Hermitian-congruent. In both of the studied cases, we show that if A and B are real and Hermitian-congruent, then they are congruent by a real symmetric matrix. Finally we note that if A and B are 2-by-2 nonsingular real symmetric matrices having the same sign pattern, then there is always a real symmetric matrix C satisfying . Moreover, if both matrices are positive, then C can be picked with arbitrary inertia. [Copyright &y& Elsevier]

We further generalize the technique for constructing the Hermitian/skew-Hermitian splitting (HSS) iteration method for solving large sparse non-Hermitian positive definite system of linear equations to the normal/skew-Hermitian (NS) splitting obtaining a class of normal/skew-Hermitian splitting (NSS) iteration methods. Theoretical analyses show that the NSS method converges unconditionally to the exact solution of the system of linear equations. Moreover, we derive an upper bound of the contraction factor of the NSS iteration which is dependent solely on the spectrum of the normal splitting matrix, and is independent of the eigenvectors of the matrices involved. We present a successive-overrelaxation (SOR) acceleration scheme for the NSS iteration, which specifically results in an acceleration scheme for the HSS iteration. Convergence conditions for this SOR scheme are derived under the assumption that the eigenvalues of the corresponding block Jacobi iteration matrix lie in certain regions in the complex plane. A numerical example is used to show that the SOR technique can significantly accelerate the convergence rate of the NSS or the HSS iteration method. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: For a self-adjoint linear operator with a discrete spectrum or a Hermitian matrix, the “extreme” eigenvalues define the boundaries of clusters in the spectrum of real eigenvalues. The outer extreme ones are the largest and the smallest eigenvalues. If there are extended intervals in the spectrum in which no eigenvalues are present, the eigenvalues bounding these gaps are the inner extreme eigenvalues. We will describe a procedure for detecting the extreme eigenvalues that relies on the relationship between the acceleration rate of polynomial acceleration iteration and the norm of the matrix via the spectral theorem, applicable to normal matrices. The strategy makes use of the fast growth rate of Chebyshev polynomials to distinguish ranges in the spectrum of the matrix which are devoid of eigenvalues. The method is numerically stable with regard to the dimension of the matrix problem and is thus capable of handling matrices of large dimension. The overall computational cost is quadratic in the size of a dense matrix; linear in the size of a sparse matrix. We verify computationally that the algorithm is accurate and efficient, even on large matrices. [Copyright &y& Elsevier]

Let D be any division ring with an involution, ℋ n ( D) be the space of all n × n hermitian matrices over D. Two hermitian matrices A and B are said to be adjacent if rank( A − B) = 1. It is proved that if ϕ is a bijective map from ℋ n ( D)( n ≥ 2) to itself such that ϕ preserves the adjacency, then ϕ −1 also preserves the adjacency. Moreover, if ℋ n ( D ≠ $${\fancyscript S}$$ 3( $${\fancyscript F}$$ 2), then ϕ preserves the arithmetic distance. Thus, an open problem posed by Wan Zhe–Xian is answered for geometry of symmetric and hermitian matrices. [ABSTRACT FROM AUTHOR]

Given a graph G with characteristic polynomial ϕ( t), we consider the ML-decomposition ϕ( t) = q 1( t) q 2( t)2 ... q m ( t)m, where each q i ( t) is an integral polynomial and the roots of ϕ( t) with multiplicity j are exactly the roots of q j ( t). We give an algorithm to construct the polynomials q i ( t) and describe some relations of their coefficients with other combinatorial invariants of G. In particular, we get new bounds for the energy E( G) = $$\mathop \sum \limits_{i = 1}^n $$ |λi| of G, where λ1, λ2, ..., λn are the eigenvalues of G (with multiplicity). Most of the results are proved for the more general situation of a Hermitian matrix whose characteristic polynomial has integral coefficients. [ABSTRACT FROM AUTHOR]

The consistent conditions and the general expressions about the Hermitian solutions of the linear matrix equations AXB=C and (AX, XB)=(C, D) are studied in depth, where A, B, C and D are given matrices of suitable sizes. The Hermitian minimum F-norm solutions are obtained for the matrix equations AXB=C and (AX, XB)=(C, D) by Moore–Penrose generalized inverse, respectively. For both matrix equations, we design iterative methods according to the fundamental idea of the classical conjugate direction method for the standard system of linear equations. Numerical results show that these iterative methods are feasible and effective in actual computations of the solutions of the above-mentioned two matrix equations. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, using a minimum principle for Schur complements of positive semidefinite Hermitian matrices and some estimates of the eigenvalues and the singular values, we obtain some inequalities for the eigenvalues of the Schur complement of the matrix product in terms of the eigenvalues of the Schur complements of and A. [Copyright &y& Elsevier]

The optimal parameter of the Hermitian/skew-Hermitian splitting (HSS) iteration method for a real two-by-two linear system is obtained. The result is used to determine the optimal parameters for linear systems associated with certain two-by-two block matrices and to estimate the optimal parameters of the HSS iteration method for linear systems with n-by-n real coefficient matrices. Numerical examples are given to illustrate the results. [ABSTRACT FROM AUTHOR]

Abstract: We propose a new QR-like algorithm, symmetric squared QR (SSQR) method, that can be readily parallelized using commonly available parallel computational primitives such as matrix–matrix multiplication and QR decomposition. The algorithm converges quadratically and the quadratic convergence is achieved through a squaring technique without utilizing any kind of shifts. We provide a rigorous convergence analysis of SSQR and derive structures for several of the important quantities generated by the algorithm. We also discuss various practical implementation issues such as stopping criteria and deflation techniques. We demonstrate the convergence behavior of SSQR using several numerical examples. [Copyright &y& Elsevier]

Suppose A-BXB*, A-BX -X*B*, and A-BX +X*B* are three linear matrix expressions over the field of complex numbers, where A is an Hermitian or skew-Hermitian matrix. In this paper, we consider how to choose an Hermitian or skew-Hermitian matrix X such that A-BXB* have the maximal and minimal possible ranks, and how to choose X such that A - BX ± X*B* attain the minimal possible ranks. Some applications to Hermitian or skew-Hermitian solutions of matrix equations with symmetric patterns are also given. [ABSTRACT FROM AUTHOR]

Abstract: Let K be a field of characteristic not two or three with an automorphism − of order two. Let . We characterize additive mappings T from one F-vector space of Hermitian matrices over K to another that preserve rank less than or equal to one for the following cases: (i) the image of T contains a matrix of rank at least three, (ii) every nonzero endomorphism of F is surjective. [Copyright &y& Elsevier]

In this paper we propose the use of the eigensystem of complex adjacency matrices to analyze the structure of asymmetric directed weighted communication. The use of complex Hermitian adjacency matrices allows to store more data relevant to asymmetric communication, and extends the interpretation of the resulting eigensystem beyond the principal eigenpair. This is based on the fact, that the adjacency matrix is transformed into a linear self-adjoint operator in Hilbert space. Subgroups of members, or nodes of a communication network can be characterised by the eigensubspaces of the complex Hermitian adjacency matrix. Their relative ‘traffic-level’ is represented by the eigenvalue of the subspace, and their members are represented by the eigenvector components. Since eigenvectors belonging to distinct eigenvalues are orthogonal the subgroups can be viewed as independent with respect to the communication behavior of the relevant members of each subgroup. As an example for this kind of analysis the EIES data set is used. The substructures and communication patterns within this data set are described. [ABSTRACT FROM AUTHOR]

Focuses on the stability of linear stochastic finite-difference systems with almost-periodic coefficients. Reduction of the stability problem of solutions of deterministic linear finite-difference equation; Establishment of a condition for exponential stability; Validity of the criterion of asymptotic mean-square stability.

Let A =( a ij ) be an n -by- n matrix. For any real µ, define the polynomial where l (s) is the number of inversions of the permutation s in the symmetric group Sn . We prove that P µ (A) is a strictly increasing function of µ ? [-1,1], for a Hermitian positive definite nondiagonal matrix A , whose graph is a tree. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an infinite class of algebras of Hermitian matrices of size , where n is a positive integer and where is a prime number or a power of a prime number (so that the Galois Field GF exists). For each such n, we obtain separate Hermitian algebras, no two of which mutually commute. [Copyright &y& Elsevier]

Abstract: In this paper, an extended projection method in the complex number field is presented. We consider two classes of complex linear matrix inequalities and then derive the corresponding projection operators. Applications to the control system with pole assignment problem and the robust stability of linear descriptor systems, which are described in complex linear matrix inequalities, are given. Based on the numerical algorithms, some examples are illustrated for the merits of the proposed method. [Copyright &y& Elsevier]

Groß [Linear Algebra Appl. 326 (2001) 215] developed characterizations of the minus and star partial orders between the squares of Hermitian nonnegative definite matrices referring to the concept of the space preordering. In the present paper, his results are generalized by deleting the nonnegative definiteness assumption and supplemented by alternative characterizations. [Copyright &y& Elsevier]

Given an n-by-n Hermitian matrix A and a real number λ, index i is said to be Parter (resp., neutral, downer) if the multiplicity of λ as an eigenvalue of the principal submatrix A(i) is one more (resp., the same, one less) than that in A. In case the multiplicity of λ in A is at least 2 and the graph of A is a tree, there are always Parter vertices. Our purpose here is to advance the classification of vertices and, in particular, to relate classification to the combinatorial structure of eigenspaces. Some general results are given and then used to deduce some rather specific facts not otherwise easily observed. Examples are given. [ABSTRACT FROM AUTHOR]

Baksalary and Pukelsheim [Linear Algebra Appl. 151 (1991) 135] considered the problem of how an order between two Hermitian nonnegative definite matrices A and B is related to the corresponding order between the squares A2 and B2, in the sense of the star partial ordering, the minus partial ordering, and the Lo¨wner partial ordering. In the present paper, possibilities of generalizing and strengthening their results are studied from two points of view: by widening the class of matrices considered and by replacing the squares by arbitrary powers. [Copyright &y& Elsevier]

Certain classes of matrices are indicated for which the star, left-star, right-star, and minus partial orderings, or some of them, are equivalent. Characterizations of the left-star and right-star orderings, similar to those devised by Hartwig and Styan [Linear Algebra Appl. 82 (1986) 145] for the star and minus orderings, are established along with other auxiliary results, which are of independent interest as well. Some inheritance-type properties of matrices are also given. The class of EP matrices appears to be essential in several points of our considerations. [Copyright &y& Elsevier]

An important theorem about the existence of principal submatrices of a Hermitian matrix whose graph is a tree, in which the multiplicity of an eigenvalue increases, was largely developed in separate papers by Parter and Wiener. Here, the prior work is fully stated, then generalized with a self-contained proof. The more complete result is then used to better understand the eigenvalue possibilities of reducible principal submatrices of Hermitian tridiagonal matrices. Sets of vertices, for which the multiplicity increases, are also studied. [ABSTRACT FROM AUTHOR]

We describe the set of all (α,n), for which the scalar complex matrix αIn is a sum of k idempotent Hermitian matrices, and get the minimal number of summands for each αIn. [Copyright &y& Elsevier]

If −∞<α<β<∞ let mid(α,x,β)=α if x<α, x if α&les;x&les;β, β if x>β. Let An=Bn+Pn where Bn and Pn are n×n Hermitian matrices. We show that if &par;Pn&par;F2=o(n) then, for any [α,β], (A) ∑i=1n|F(mid(α,λi(An),β))−F(mid(α,λi(Bn),β))|=o(n) if F∈C[α,β]. (Eigenvalues numbered in nondecreasing order.) We consider the special case where {Pn} are real Hankel matrices. We also show that if rank(Pn)=o(n) then (A) holds for every [α,β] and F∈C[α,β]. Combining these results yields a result concerning Cn=Bn+En+Rn, where &par;En&par;2F=o(n) and rank(Rn)=o(n). We also consider the case where the conditions on {En} are stated in terms of Schatten p-norms. Finally, we show that if {Tn} are Hermitian Toeplitz matrices generated by f∈C[−π,π] with minimum mf and maximum Mf, (2(i−1)−n)π/n&les;ξin&les;(2i−n)π/n, 1&les;i&les;n, and τn is a permutation of {1,2,…,n} such that f(ξτn(1),n)&les;f(ξτn(2),n)&les;⋯&les;f(ξτn(n),n), then ∑i=1n|F(λi(Tn))−F(f(ξτn(i),n))|=o(n) if F∈C[mf,Mf]. [Copyright &y& Elsevier]

We study convergence conditions for the additive and the multiplicative splitting iteration methods, i.e., two generalizations of the additive and the multiplicative Schwarz iterations, for Hermitian and non-Hermitian systems of linear equations, under an algebraic setting. Theoretical analyses show that when the coefficient and the splitting matrices are Hermitian, or non-Hermitian but diagonalizable, satisfying mild conditions, both additive and multiplicative splitting iteration methods are convergent, even if the coefficient matrix is indefinite. [Copyright &y& Elsevier]

For Hermitian matrices, whose graph is a given tree, the relationships among vertex degrees, multiple eigenvalues and the relative position of the underlying eigenvalue in the ordered spectrum are discussed in detail. In the process, certain aspects of special vertices, whose removal results in an increase in multiplicity are investigated. [Copyright &y& Elsevier]

We introduced an efficient technique to suppress speckle noise in medical ultrasound images while maintaining low computational complexity. The medical ultrasound image is divided into overlapping subimages, and Lanczos decomposition is then applied to the average Hermitian covariance matrix of all subimages. The resultant orthonormal vectors are used for filtering speckle noise through orthogonal and oblique projections, i.e., by projecting noisy signal onto the signal subspace. After sorting the orthonormal vectors, an orthogonal projection matrix is formed by selecting the first K vectors contributing to the signal, whereas an oblique projection matrix is formed by selecting the first K vectors contributing to the signal and the last K vectors contributing to the noise. The procedure of Lanczos is also followed with singular value decomposition (SVD). Schemes are applied to real ultrasound images and two types of speckle noise simulations: fine and rough speckle noise. Numerical and visual results depict that proposed technique has outperformed various popular benchmark schemes, i.e., Frost, Lee, probabilistic nonlocal means, geometric nonlinear diffusion filter, guided speckle reducing bilateral filter, and SVD, while maintaining a competitive computational complexity. Lanczos-based scheme showed a relatively lagging performance in terms of resolution, which was always outshone by a leading performance in terms of key measures such as signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), feature similarity, and mean structural similarity. Orthogonal and oblique projections were found to perform the same except when speckle noise is fine, where insignificant differences were found in terms of SNR, PSNR, and resolution. Lanczos-based scheme tends to offer a better estimation of orthonormal vectors than SVD, consequently a better speckle noise suppression. Furthermore, it offers an efficient tuning parameter per block/subimage size to treat various speckle noise patterns. [ABSTRACT FROM AUTHOR]