v2010.10.26 - Convex Optimization
v2010.10.26 - Convex Optimization v2010.10.26 - Convex Optimization
590 CHAPTER 7. PROXIMITY PROBLEMS
Appendix ALinear algebraA.1 Main-diagonal δ operator, λ , trace, vecWe introduce notation δ denoting the main-diagonal linear self-adjointoperator. When linear function δ operates on a square matrix A∈ R N×N ,δ(A) returns a vector composed of all the entries from the main diagonal inthe natural order;δ(A) ∈ R N (1415)Operating on a vector y ∈ R N , δ naturally returns a diagonal matrix;δ(y) ∈ S N (1416)Operating recursively on a vector Λ∈ R N or diagonal matrix Λ∈ S N ,δ(δ(Λ)) returns Λ itself;δ 2 (Λ) ≡ δ(δ(Λ)) Λ (1417)Defined in this manner, main-diagonal linear operator δ is self-adjoint[227,3.10,9.5-1]; A.1 videlicet, (2.2)δ(A) T y = 〈δ(A), y〉 = 〈A , δ(y)〉 = tr ( A T δ(y) ) (1418)A.1 Linear operator T : R m×n → R M×N is self-adjoint when, ∀ X 1 , X 2 ∈ R m×n〈T(X 1 ), X 2 〉 = 〈X 1 , T(X 2 )〉2001 Jon Dattorro. co&edg version 2010.10.26. All rights reserved.citation: Dattorro, Convex Optimization & Euclidean Distance Geometry,Mεβoo Publishing USA, 2005, v2010.10.26.591
- Page 539 and 540: 6.8. DUAL EDM CONE 5396.8.1.5 Affin
- Page 541 and 542: 6.8. DUAL EDM CONE 5416.8.1.7 Schoe
- Page 543 and 544: 6.8. DUAL EDM CONE 5430dvec rel ∂
- Page 545 and 546: 6.10. POSTSCRIPT 5456.10 Postscript
- Page 547 and 548: Chapter 7Proximity problemsIn the
- Page 549 and 550: 549project on the subspace, then pr
- Page 551 and 552: 551HS N h0EDM NK = S N h ∩ R N×N
- Page 553 and 554: 5537.0.3 Problem approachProblems t
- Page 555 and 556: 7.1. FIRST PREVALENT PROBLEM: 555fi
- Page 557 and 558: 7.1. FIRST PREVALENT PROBLEM: 5577.
- Page 559 and 560: 7.1. FIRST PREVALENT PROBLEM: 559di
- Page 561 and 562: 7.1. FIRST PREVALENT PROBLEM: 5617.
- Page 563 and 564: 7.1. FIRST PREVALENT PROBLEM: 563wh
- Page 565 and 566: 7.1. FIRST PREVALENT PROBLEM: 565Th
- Page 567 and 568: 7.2. SECOND PREVALENT PROBLEM: 567O
- Page 569 and 570: 7.2. SECOND PREVALENT PROBLEM: 569S
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- Page 573 and 574: 7.2. SECOND PREVALENT PROBLEM: 573w
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- Page 577 and 578: 7.2. SECOND PREVALENT PROBLEM: 577a
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- Page 583 and 584: 7.3. THIRD PREVALENT PROBLEM: 583su
- Page 585 and 586: 7.3. THIRD PREVALENT PROBLEM: 585Gi
- Page 587 and 588: 7.3. THIRD PREVALENT PROBLEM: 587Op
- Page 589: 7.4. CONCLUSION 589filtering, multi
- Page 593 and 594: A.1. MAIN-DIAGONAL δ OPERATOR, λ
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- Page 597 and 598: A.2. SEMIDEFINITENESS: DOMAIN OF TE
- Page 599 and 600: A.3. PROPER STATEMENTS 599(AB) T
- Page 601 and 602: A.3. PROPER STATEMENTS 601A.3.1Semi
- Page 603 and 604: A.3. PROPER STATEMENTS 603For A dia
- Page 605 and 606: A.3. PROPER STATEMENTS 605Diagonali
- Page 607 and 608: A.3. PROPER STATEMENTS 607For A,B
- Page 609 and 610: A.3. PROPER STATEMENTS 609When B is
- Page 611 and 612: A.4. SCHUR COMPLEMENT 611A.4 Schur
- Page 613 and 614: A.4. SCHUR COMPLEMENT 613A.4.0.0.3
- Page 615 and 616: A.4. SCHUR COMPLEMENT 615From Corol
- Page 617 and 618: A.5. EIGENVALUE DECOMPOSITION 617wh
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- Page 623 and 624: A.6. SINGULAR VALUE DECOMPOSITION,
- Page 625 and 626: A.7. ZEROS 625A.6.5SVD of symmetric
- Page 627 and 628: A.7. ZEROS 627(Transpose.)Likewise,
- Page 629 and 630: A.7. ZEROS 629For X,A∈ S M +[34,2
- Page 631 and 632: A.7. ZEROS 631A.7.5.0.1 Proposition
- Page 633 and 634: Appendix BSimple matricesMathematic
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- Page 639 and 640: B.2. DOUBLET 639R([u v ])R(Π)= R([
Appendix ALinear algebraA.1 Main-diagonal δ operator, λ , trace, vecWe introduce notation δ denoting the main-diagonal linear self-adjointoperator. When linear function δ operates on a square matrix A∈ R N×N ,δ(A) returns a vector composed of all the entries from the main diagonal inthe natural order;δ(A) ∈ R N (1415)Operating on a vector y ∈ R N , δ naturally returns a diagonal matrix;δ(y) ∈ S N (1416)Operating recursively on a vector Λ∈ R N or diagonal matrix Λ∈ S N ,δ(δ(Λ)) returns Λ itself;δ 2 (Λ) ≡ δ(δ(Λ)) Λ (1417)Defined in this manner, main-diagonal linear operator δ is self-adjoint[227,3.10,9.5-1]; A.1 videlicet, (2.2)δ(A) T y = 〈δ(A), y〉 = 〈A , δ(y)〉 = tr ( A T δ(y) ) (1418)A.1 Linear operator T : R m×n → R M×N is self-adjoint when, ∀ X 1 , X 2 ∈ R m×n〈T(X 1 ), X 2 〉 = 〈X 1 , T(X 2 )〉2001 Jon Dattorro. co&edg version 2010.10.26. All rights reserved.citation: Dattorro, <strong>Convex</strong> <strong>Optimization</strong> & Euclidean Distance Geometry,Mεβoo Publishing USA, 2005, <strong>v2010.10.26</strong>.591