v2010.10.26 - Convex Optimization

779SDPSVDSNRdBEDMS n 1S n hS n⊥hS n csemidefinite programsingular value decompositionsignal to noise ratiodecibelEuclidean distance matrixsubspace comprising all symmetric n×n matrices having all zeros infirst row and column (2002)subspace comprising all symmetric hollow n×n matrices (0 maindiagonal), the symmetric hollow subspace (66)orthogonal complement of S n h in Sn (67), the set of all diagonal matricessubspace comprising all geometrically centered symmetric n×nmatrices; geometric center subspace S N c = {Y ∈ S N | Y 1=0} (1998)S n⊥c orthogonal complement of S n c in S n (2000)R m×ncsubspace comprising all geometrically centered m×n matricesX ⊥ basis N(X T ) (2.13.9)x ⊥ N(x T ) ; {y ∈ R n | x T y = 0} (2.13.10.1.1)R(P ) ⊥ N(P T ) (fundamental subspace relations (137))N(P ) ⊥ R(P T )R ⊥ = {y ∈ R n | 〈x,y〉=0 ∀x∈ R} (373).Orthogonal complement of R in R n when R is a subspaceK ⊥ normal cone (449)A ⊥ normal cone to affine subset A (3.1.2.1.2)KK ∗conedual cone