v2009.01.01 - Convex Optimization
v2009.01.01 - Convex Optimization v2009.01.01 - Convex Optimization
550 APPENDIX A. LINEAR ALGEBRA Because R(A T A)= R(A T ) and R(AA T )= R(A) , for any A∈ R m×n rank(AA T ) = rank(A T A) = rankA = rankA T (1372) For A∈ R m×n having no nullspace, and for any B ∈ R n×k rank(AB) = rank(B) (1373) Proof. For any compatible matrix C , N(CAB)⊇ N(AB)⊇ N(B) is obvious. By assumption ∃A † A † A = I . Let C = A † , then N(AB)= N(B) and the stated result follows by conservation of dimension (1469). For A∈ S n and any nonsingular matrix Y inertia(A) = inertia(YAY T ) (1374) a.k.a, Sylvester’s law of inertia. (1415) [96,2.4.3] For A,B∈R n×n square, [176,0.3.5] Yet for A∈ R m×n and B ∈ R n×m [68, p.72] det(AB) = det(BA) (1375) det(AB) = detA detB (1376) det(I + AB) = det(I + BA) (1377) For A,B ∈ S n , product AB is symmetric if and only if AB is commutative; (AB) T = AB ⇔ AB = BA (1378) Proof. (⇒) Suppose AB=(AB) T . (AB) T =B T A T =BA . AB=(AB) T ⇒ AB=BA . (⇐) Suppose AB=BA . BA=B T A T =(AB) T . AB=BA ⇒ AB=(AB) T . Commutativity alone is insufficient for symmetry of the product. [287, p.26]
A.3. PROPER STATEMENTS 551 Diagonalizable matrices A,B∈R n×n commute if and only if they are simultaneously diagonalizable. [176,1.3.12] A product of diagonal matrices is always commutative. For A,B ∈ R n×n and AB = BA x T Ax ≥ 0, x T Bx ≥ 0 ∀x ⇒ λ(A+A T ) i λ(B+B T ) i ≥ 0 ∀i x T ABx ≥ 0 ∀x (1379) the negative result arising because of the schism between the product of eigenvalues λ(A + A T ) i λ(B + B T ) i and the eigenvalues of the symmetrized matrix product λ(AB + (AB) T ) i . For example, X 2 is generally not positive semidefinite unless matrix X is symmetric; then (1360) applies. Simply substituting symmetric matrices changes the outcome: For A,B ∈ S n and AB = BA A ≽ 0, B ≽ 0 ⇒ λ(AB) i =λ(A) i λ(B) i ≥0 ∀i ⇔ AB ≽ 0 (1380) Positive semidefiniteness of A and B is sufficient but not a necessary condition for positive semidefiniteness of the product AB . Proof. Because all symmetric matrices are diagonalizable, (A.5.2) [287,5.6] we have A=SΛS T and B=T∆T T , where Λ and ∆ are real diagonal matrices while S and T are orthogonal matrices. Because (AB) T =AB , then T must equal S , [176,1.3] and the eigenvalues of A are ordered in the same way as those of B ; id est, λ(A) i =δ(Λ) i and λ(B) i =δ(∆) i correspond to the same eigenvector. (⇒) Assume λ(A) i λ(B) i ≥0 for i=1... n . AB=SΛ∆S T is symmetric and has nonnegative eigenvalues contained in diagonal matrix Λ∆ by assumption; hence positive semidefinite by (1347). Now assume A,B ≽0. That, of course, implies λ(A) i λ(B) i ≥0 for all i because all the individual eigenvalues are nonnegative. (⇐) Suppose AB=SΛ∆S T ≽ 0. Then Λ∆≽0 by (1347), and so all products λ(A) i λ(B) i must be nonnegative; meaning, sgn(λ(A))= sgn(λ(B)). We may, therefore, conclude nothing about the semidefiniteness of A and B .
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550 APPENDIX A. LINEAR ALGEBRA<br />
Because R(A T A)= R(A T ) and R(AA T )= R(A) , for any A∈ R m×n<br />
rank(AA T ) = rank(A T A) = rankA = rankA T (1372)<br />
For A∈ R m×n having no nullspace, and for any B ∈ R n×k<br />
rank(AB) = rank(B) (1373)<br />
Proof. For any compatible matrix C , N(CAB)⊇ N(AB)⊇ N(B)<br />
is obvious. By assumption ∃A † A † A = I . Let C = A † , then<br />
N(AB)= N(B) and the stated result follows by conservation of<br />
dimension (1469).<br />
<br />
For A∈ S n and any nonsingular matrix Y<br />
inertia(A) = inertia(YAY T ) (1374)<br />
a.k.a, Sylvester’s law of inertia. (1415) [96,2.4.3]<br />
For A,B∈R n×n square, [176,0.3.5]<br />
Yet for A∈ R m×n and B ∈ R n×m [68, p.72]<br />
det(AB) = det(BA) (1375)<br />
det(AB) = detA detB (1376)<br />
det(I + AB) = det(I + BA) (1377)<br />
For A,B ∈ S n , product AB is symmetric if and only if AB is<br />
commutative;<br />
(AB) T = AB ⇔ AB = BA (1378)<br />
Proof. (⇒) Suppose AB=(AB) T . (AB) T =B T A T =BA .<br />
AB=(AB) T ⇒ AB=BA .<br />
(⇐) Suppose AB=BA . BA=B T A T =(AB) T . AB=BA ⇒<br />
AB=(AB) T .<br />
<br />
Commutativity alone is insufficient for symmetry of the product.<br />
[287, p.26]