The error bound of the perturbation of the Drazin inverse

Let A and E be n×n matrices and B = A + E. Denote the Drazin inverse of A by A^D. In this paper we give an upper bound for the relative error ∥B^D ? A^D∥/∥A^D∥₂ and a lower bound for ∥B^D∥₂ under certain circumstances. The continuity properties and the derivative of the Drazin inverse are also considered.     

New perturbation bounds for the W-weighted Drazin inverse

The constructive perturbation bounds for the W-weighted Drazin inverse are derived by two approaches in this paper. One uses the matrixG = [(A+E)W]^l?(AW)^l, whereA, E ∈ C ^mxn ,W ∈ C ^nxm ,l = max Ind(AW), Ind[(A + E)W]. The other uses a technique proposed by G. Stewart and based on perturbation theory for invariant subspaces of a matrix. The new approaches to develop perturbation bounds for W-weighted Drazin inverse of a matrix extend the previous results in [19, 29, 31, 36, 42, 44]. Several examples which indicate the sharpness of the new perturbation bounds are presented.     

Representations for the weighted Drazin inverse of a sum of matrices

Three representations for the W-weighted Drazin inverse of a matrix A?CWB have been developed under some conditions where A,B,C∈? ^m×n , and W∈? ^n×m . The results of this paper not only extend the earlier works about the Drazin inverse and group inverse, but also weaken the assumed condition of a result of the Drazin inverse to the case where Γ _d ZZ _g =ZZ _g Γ _d is substituted with C(Γ _d ZZ _g ?ZZ _g Γ _d )B=0. Numerical examples are given to illustrate some new results.     

The reverse order law for theW-weighted Drazin inverse of multiple matrices product

By using the rank methods of matrix, a necessary and sufficient condition is established for reverse order law $$\begin{gathered} WA_{d,W} W = (W_n (A_n )_{d,W_n } W_n )(W_{n - 1} (A_{n - 1} )_{d,W_{n - 1} } W_{n - 1} ) \hfill \\ ... (W_1 (A_1 )_{d,W_1 } W_1 ) \hfill \\ \end{gathered} $$ to hold for the W-weighted Drazin inverses, whereA =A ₁ A ₂ … A _n andW =W _n W _n-1 …W ₁. This result is the extension of the result proposed by [Linear Algebra Appl., 348(2002)265-272] and the result proposed by [J. Math. Research and Exposition. 19(1999)355-358].     

Relative perturbation bounds for the unitary polar factor

LetB be anm×n (m≥n) complex (or real) matrix. It is known that there is a uniquepolar decomposition B=QH, whereQ*Q=I, then×n identity matrix, andH is positive definite, providedB has full column rank. Existing perturbation bounds suggest that in the worst case, for complex matrices the change inQ be proportional to the reciprocal ofB's least singular value, or the reciprocal of the sum ofB's least and second least singular values if matrices are real. However, there are situations where this unitary polar factor is much more accurately determined by the data than the existing perturbation bounds would indicate. In this paper the following question is addressed: how much mayQ change ifB is perturbed to $\tilde B = D_1^* BD_2 $ , whereD ₁ andD ₂ are nonsingular and close to the identity matrices of suitable dimensions? It is shown that for a such kind of perturbation, the change inQ is bounded only by the distances fromD ₁ andD ₂ to identity matrices and thus is independent ofB's singular values. Such perturbation is restrictive, but not unrealistic. We show how a frequently used scaling technique yields such a perturbation and thus scaling may result in better-conditioned polar decompositions.     

The computation and perturbation analysis for weighted group inverse of rectangular matrices

Cen (Math. Numer. Sin. 29(1):39–48, 2007) has defined a weighted group inverse of rectangular matrices. Let A∈C ^m×n ,W∈C ^n×m , if X∈C ^m×n satisfies the system of matrix equations $$(W_{1})\quad AWXWA=A,\quad\quad (W_{2})\quad XWAWX=X,\quad\quad (W_{3})\quad AWX=XWA$$ X is called the weighted group inverse of A with W, and denoted by A _W ^# . In this paper, we will study the algebra perturbation and analytical perturbation of this kind weighted group inverse A _W ^# . Under some conditions, we give a decomposition of B _W ^# ?A _W ^# . As a results, norm estimate of ‖B _W ^# ?A _W ^# ‖ is presented (where B=A+E). An expression of algebra of perturbation is also obtained. In order to compute this weighted group inverse with ease, we give a new representation of this inverse base on Gauss-elimination, then we can calculate this weighted inverse by Gauss-elimination. In the end, we use a numerical example to show our results.     

Additive results for the Wg-Drazin inverse

In this paper we prove the formula for the expression (A+B)^d,W in terms of A,B,W,A^d,W,B^d,W, assuming some conditions for A,B and W. Here S^d,W denotes the generalized W-weighted Drazin inverse of a linear bounded operator S on a Banach space.     

Comment on “Condition number of W-weighted Drazin inverse and their condition numbers of singular linear systems”

In this paper, we establish the explicit condition number formulas for the W-weighted Drazin inverse of a singular matrix A, where A∈? ^m×n , W∈? ^n×m , ?((AW) ^k )=?((AW) ^{k *}), ?((WA) ^k )=?((WA) ^{k *}), and k=max{index(AW), index(WA)}, by the Schur decomposition of A and W. The sensitivity for the W-weighted Drazin-inverse solution of singular systems is also discussed. Based on this form of Schur decomposition, the explicit condition number formulas for the W-weighted Drazin inverse are given by the spectral norm and Frobenius norm instead of the ‖?‖ _P,W -norm, where P is a transformation matrix of the Jordan canonical form of AW, thereby improving the earlier work of Lei et al. (Appl. Math. Comput. 165:185–194, [2005]) and Wang et al. (Appl. Math. Comput. 162:434–446, [2005]).     

A Drazin inverse for rectangular matrices

The definition of the Drazin inverse of a square matrix with complex elements is extended to rectangular matrices by showing that for any B and W,m by n and n by m, respectively, there exists a unique matrix, X, such that (BW)^k=(BW)^k+1XW for some positive integer k, XWBWX = X, and BWX = XWB. Various expressions satisfied by B, W,X and related matrices are developed.     

Acute perturbation of Drazin inverse and oblique projectors

For an n×n complex matrix A with ind(A) = r; let A^D and A^π = I–AA^D be respectively the Drazin inverse and the eigenprojection corresponding to the eigenvalue 0 of A: For an n×n complex singular matrix B with ind(B) = s, it is said to be a stable perturbation of A, if I–(B^π–A^π)² is nonsingular, equivalently, if the matrix B satisfies the condition \(\mathcal{R}(B^s)\cap\mathcal{N}(A^r)=\left\{0\right\}\) and \(\mathcal{N}(B^s)\cap\mathcal{R}(A^r)=\left\{0\right\}\), introduced by Castro-González, Robles, and Vélez-Cerrada. In this paper, we call B an acute perturbation of A with respect to the Drazin inverse if the spectral radius ρ(B^π–A^π) < 1: We present a perturbation analysis and give suffcient and necessary conditions for a perturbation of a square matrix being acute with respect to the matrix Drazin inverse. Also, we generalize our perturbation analysis to oblique projectors. In our analysis, the spectral radius, instead of the usual spectral norm, is used. Our results include the previous results on the Drazin inverse and the group inverse as special cases and are consistent with the previous work on the spectral projections and the Moore-Penrose inverse.     

Almost commuting matrices

It is shown that if A and B are n × n complex matrices with $\text{A = A}{}^1\text{and}\text{∥AB ? BA∥</}\text{2?}{}^2\text{(n ? 1)}$, then there exist n × n matrices A′ and B′ with $\text{A′ = A′}{}^1\text{such that}\text{A′B′ = B′A′}\text{and}\text{∥A ? A′∥? ?, ∥B ? B′∥? ?}$.     

On the Schur multiplier norm of matrices

The Schur product of two n×n complex matrices A=(a_ij), B=(b_ij) is defined by A°B=(a_ijb_ij. By a result of Schur [2], the algebra of n×n matrices with Schur product and the usual addition is a commutative Banach algebra under the operator norm (the norm of the operator defined on $\text{C}$ⁿ by the matrix). For a fixed matrix A, the norm of the operator B?A°B on this Banach algebra is called the Schur multiplier norm of A, and is denoted by ∥A∥^m. It is proved here that $\text{∥A∥=∥U}{}^1\text{AU∥}{}_{\mathrm{m}}$ for all unitary U (where ∥·∥ denotes the operator norm) iff A is a scalar multiple of a unitary matrix; and that ∥A∥_m=∥A∥ iff there exist two permutations P, Q, a p×p (1?p?n) unitary U, an (n?p)×(n?p)1 contraction C, and a nonnegative number λ such that

$\text{A=λP}\text{U}\text{0}\text{0}\text{C}\text{Q;}$

and this is so iff $\text{∥A°}\text{A}\text{?}\text{∥=∥A∥}{}^2$, where ā is the matrix obtained by taking entrywise conjugates of A.     

关于带W权Drazin逆的表示定理及迭代方法

To study singular linear system, Cline and Greville[8] proposed the concept of W-weighted Drazin inverse for the rectangular matrices,where the properties were also discussed. The computation for the W-weighted Drazin inverse is of much interest, which is mainly divided into two kinds of methods: direct method[2,4,6] and iterative method[3,5,7,9,12,13]. In this paper, we study the iterative method and successive matrix squaring(SMS) method for the W-weighted Drazin inverse and generalize the main results in [12,13].     

Condition number for the w-weighted drazin inverse and its applications in the solution of rectangular linear system

In this paper, we generalized the results of [23, 26], and get the results of the condition number of the W-weighted Drazin-inverse solution of linear systemWAWx =b, whereA is anm x n rank-deficient matrix and the index ofAW isk ₁, the index ofWA isk ₂,b is a real vector of sizen in the range of (WA) ^k2 ,x is a real vector of sizem in the range of (AW) ^k1 . Let α and β be two positive real numbers, when we consider the weighted Frobenius norm $\left\| {\left[ {\alpha W AW,\beta b} \right]} \right\|_{Q,\tilde P}^{(F)} $ on the data we get the formula of condition number of the W-weighted Drazin-inverse solution of linear system. For the normwise condition number, the sensitivity of the relative condition number itself is studied, and the componentwise perturbation is also investigated.     

On the perturbation of the group generalized inverse for a class of bounded operators in Banach spaces

Given a bounded operator A on a Banach space X with Drazin inverse AD and index r, we study the class of group invertible bounded operators B such that I+AD(B−A) is invertible and R(B)∩N(Ar)={0}. We show that they can be written with respect to the decomposition X=R(Ar)⊕N(Ar) as a matrix operator, , where B₁ and are invertible. Several characterizations of the perturbed operators are established, extending matrix results. We analyze the perturbation of the Drazin inverse and we provide explicit upper bounds of ‖B^?−AD‖ and ‖BB^?−ADA‖. We obtain a result on the continuity of the group inverse for operators on Banach spaces.     

Spectral norm of products of random and deterministic matrices

We study the spectral norm of matrices W that can be factored as W?=?BA, where A is a random matrix with independent mean zero entries and B is a fixed matrix. Under the (4?+???)th moment assumption on the entries of A, we show that the spectral norm of such an m × n matrix W is bounded by ${\sqrt{m} + \sqrt{n}}$ , which is sharp. In other words, in regard to the spectral norm, products of random and deterministic matrices behave similarly to random matrices with independent entries. This result along with the previous work of Rudelson and the author implies that the smallest singular value of a random m × n matrix with i.i.d. mean zero entries and bounded (4?+???)th moment is bounded below by ${\sqrt{m} - \sqrt{n-1}}$ with high probability.     

Boundedness of the solution of a degenerate second order differential equation system

We consider a linear system of second order differential equations (1) $$A x(t) = B x (t),$$ whereA andB are singularn×n matrices,x is ann-dimensional vector with coordinates twice differentiable int. Using the Drazin inverse matrix theory we find a solution of the Cauchy problem that is bounded on the whole axis.     

Separability of distinct Boolean rank-1 matrices

For two distinct rank-1 matricesA andB, a rank-1 matrixC is called aseparating matrix ofA andB if the rank ofA+C is 2 but the rank ofB+C is 1 or vice versa. In this case, rank-1 matricesA andB are said to beseparable. We show that every pair of distinct Boolean rank-1 matrices are separable.     

Condition numbers with their condition numbers for the weighted moore-penrose inverse and the weighted least squares solution

In this paper, the authors investigate the condition number with their condition numbers for weighted Moore-Penrose inverse and weighted least squares solution of $\mathop {\min }\limits_x ||Ax - b||_M $ , whereA is a rank-deficient complex matrix in ?^{m × n} andb a vector of lengthm in ?^m,x a vector of length n in ?ⁿ. For the normwise condition number, the sensitivity of the relative condition number itself is studied, the componentwise perturbation is also investigated.     

Representation for the W-weighted Drazin inverse of linear operators

In this paper we study the W-weighted Drazin inverse of the bounded linear operators between Banach spaces and its representation theorem. Based on this representation, utilizing the spectral theory of Banach space operators, we derive an approximating expression of the W-weighted Drazin inverse and an error bound. Also, a perturbation theorem for the W-weighted Drazin inverse is uniformly obtained from the representation theorem.