Solving optimization problems on ranks and inertias of some constrained nonlinear matrix functions via an algebraic linearization method

We establish in this paper a group of closed-form formulas for calculating the global maximum and minimum ranks and inertias of the quadratic Hermitian matrix function ϕ ( X ) = Q − X P X ∗ with respect to the variable matrix X by using a linearization method and some known formulas for extremum ran...

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Published inNonlinear analysis Vol. 75; no. 2; pp. 717 - 734
Main Author Tian, Yongge
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier Ltd 2012
Elsevier
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ISSN0362-546X
1873-5215
DOI10.1016/j.na.2011.09.003

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Abstract We establish in this paper a group of closed-form formulas for calculating the global maximum and minimum ranks and inertias of the quadratic Hermitian matrix function ϕ ( X ) = Q − X P X ∗ with respect to the variable matrix X by using a linearization method and some known formulas for extremum ranks and inertias of linear Hermitian matrix functions, where both P and Q are complex Hermitian matrices and X ∗ is the conjugate transpose of X . We then derive the global maximum and minimum ranks and inertias of the two quadratic Hermitian matrix functions ϕ 1 ( X ) = Q 1 − X P 1 X ∗ and ϕ 2 ( X ) = Q 2 − X ∗ P 2 X subject to a consistent matrix equation A X = B , respectively, by using some pure algebraic operations of matrices and their generalized inverses. As consequences, we establish necessary and sufficient conditions for the solutions of the matrix equation A X = B to satisfy the quadratic Hermitian matrix equalities X P 1 X ∗ = Q 1 and X ∗ P 2 X = Q 2 , respectively, and for the quadratic matrix inequalities X P 1 X ∗ > ( ⩾ , < , ⩽ ) Q 1 and X ∗ P 2 X > ( ⩾ , < , ⩽ ) Q 2 in the Löwner partial ordering to hold, respectively. In addition, we give complete solutions to four Löwner partial ordering optimization problems on the matrix functions ϕ 1 ( X ) and ϕ 2 ( X ) subject to A X = B . Examples are also presented to illustrative applications of the equality-constrained quadratic optimizations in some matrix completion problems.
AbstractList We establish in this paper a group of closed-form formulas for calculating the global maximum and minimum ranks and inertias of the quadratic Hermitian matrix function ϕ ( X ) = Q − X P X ∗ with respect to the variable matrix X by using a linearization method and some known formulas for extremum ranks and inertias of linear Hermitian matrix functions, where both P and Q are complex Hermitian matrices and X ∗ is the conjugate transpose of X . We then derive the global maximum and minimum ranks and inertias of the two quadratic Hermitian matrix functions ϕ 1 ( X ) = Q 1 − X P 1 X ∗ and ϕ 2 ( X ) = Q 2 − X ∗ P 2 X subject to a consistent matrix equation A X = B , respectively, by using some pure algebraic operations of matrices and their generalized inverses. As consequences, we establish necessary and sufficient conditions for the solutions of the matrix equation A X = B to satisfy the quadratic Hermitian matrix equalities X P 1 X ∗ = Q 1 and X ∗ P 2 X = Q 2 , respectively, and for the quadratic matrix inequalities X P 1 X ∗ > ( ⩾ , < , ⩽ ) Q 1 and X ∗ P 2 X > ( ⩾ , < , ⩽ ) Q 2 in the Löwner partial ordering to hold, respectively. In addition, we give complete solutions to four Löwner partial ordering optimization problems on the matrix functions ϕ 1 ( X ) and ϕ 2 ( X ) subject to A X = B . Examples are also presented to illustrative applications of the equality-constrained quadratic optimizations in some matrix completion problems.
We establish in this paper a group of closed-form formulas for calculating the global maximum and minimum ranks and inertias of the quadratic Hermitian matrix function phi (X)=Q-XPX* with respect to the variable matrix X by using a linearization method and some known formulas for extremum ranks and inertias of linear Hermitian matrix functions, where both P and Q are complex Hermitian matrices and X* is the conjugate transpose of X. We then derive the global maximum and minimum ranks and inertias of the two quadratic Hermitian matrix functions phi sub(1)(X)=Q sub(1)-XP sub(1)X* ; and phi sub(2)(X)=Q sub(2)-X*P sub(2) X subject to a consistent matrix equation AX=B, respectively, by using some pure algebraic operations of matrices and their generalized inverses. As consequences, we establish necessary and sufficient conditions for the solutions of the matrix equation AX=B to satisfy the quadratic Hermitian matrix equalities XP sub(1)X*=Q sub(1) and X*P sub(2)X=Q sub(2), respectively, and for the quadratic matrix inequalities [inline image] and [inline image] in the Lowner partial ordering to hold, respectively. In addition, we give complete solutions to four Lowner partial ordering optimization problems on the matrix functions phi sub(1)(X) and phi sub(2)(X) subject to AX=B. Examples are also presented to illustrative applications of the equality-constrained quadratic optimizations in some matrix completion problems.
Author Tian, Yongge
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Issue 2
Keywords 65K15
Löwner partial ordering
Rank
Matrix inequality
15B57
15A09
Generalized inverse
Linearization method
Optimization
15A63
15A24
15B10
65K10
Inertia
Quadratic matrix function
Linear matrix function
Matrix equation
Optimization method
Partial ordering
Lowner partial ordering
Mathematical model
Linearization
Nonlinear analysis
Matrix function
Algebraic method
Problem solving
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Snippet We establish in this paper a group of closed-form formulas for calculating the global maximum and minimum ranks and inertias of the quadratic Hermitian matrix...
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SubjectTerms Algebra
Calculus of variations and optimal control
Exact sciences and technology
Finite differences and functional equations
Generalized inverse
Inertia
Linear and multilinear algebra, matrix theory
Linear matrix function
Linearization method
Löwner partial ordering
Mathematical analysis
Mathematics
Matrices
Matrix equation
Matrix inequality
Nonlinear algebraic and transcendental equations
Nonlinearity
Numerical analysis
Numerical analysis. Scientific computation
Optimization
Order disorder
Quadratic matrix function
Rank
Sciences and techniques of general use
Title Solving optimization problems on ranks and inertias of some constrained nonlinear matrix functions via an algebraic linearization method
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