v2007.09.13 - Convex Optimization
v2007.09.13 - Convex Optimization v2007.09.13 - Convex Optimization
328 CHAPTER 5. EUCLIDEAN DISTANCE MATRIX5.5.2 Rotation/ReflectionRotation of the list X ∈ R n×N about some arbitrary point α∈ R n , orreflection through some affine subset containing α , can be accomplishedvia Q(X −α1 T ) where Q is an orthogonal matrix (B.5).We rightfully expectD ( Q(X − α1 T ) ) = D(QX − β1 T ) = D(QX) = D(X) (790)Because list-form D(X) is translation invariant, we may safely ignoreoffset and consider only the impact of matrices that premultiply X .Interpoint distances are unaffected by rotation or reflection; we say,EDM D is rotation/reflection invariant. Proof follows from the fact,Q T =Q −1 ⇒ X T Q T QX =X T X . So (790) follows directly from (705).The class of premultiplying matrices for which interpoint distances areunaffected is a little more broad than orthogonal matrices. Looking at EDMdefinition (705), it appears that any matrix Q p such thatwill have the propertyX T Q T pQ p X = X T X (791)D(Q p X) = D(X) (792)An example is skinny Q p ∈ R m×n (m>n) having orthonormal columns. Wecall such a matrix orthonormal.5.5.2.1 Inner-product form invarianceLikewise, D(Θ) (770) is rotation/reflection invariant;so (791) and (792) similarly apply.5.5.3 Invariance conclusionD(Q p Θ) = D(QΘ) = D(Θ) (793)In the making of an EDM, absolute rotation, reflection, and translationinformation is lost. Given an EDM, reconstruction of point position (5.12,the list X) can be guaranteed correct only in affine dimension r and relativeposition. Given a noiseless complete EDM, this isometric reconstruction isunique in so far as every realization of a corresponding list X is congruent:
5.6. INJECTIVITY OF D & UNIQUE RECONSTRUCTION 3295.6 Injectivity of D & unique reconstructionInjectivity implies uniqueness of isometric reconstruction; hence, we endeavorto demonstrate it.EDM operators list-form D(X) (705), Gram-form D(G) (717), andinner-product form D(Θ) (770) are many-to-one surjections (5.5) onto thesame range; the EDM cone (6): (confer (718) (800))EDM N = { D(X) : R N−1×N → S N h | X ∈ R N−1×N}= { }D(G) : S N → S N h | G ∈ S N + − S N⊥c= { (794)D(Θ) : R N−1×N−1 → S N h | Θ ∈ R N−1×N−1}where (5.5.1.1)S N⊥c = {u1 T + 1u T | u∈ R N } ⊆ S N (1763)5.6.1 Gram-form bijectivityBecause linear Gram-form EDM operatorD(G) = δ(G)1 T + 1δ(G) T − 2G (717)has no nullspace [58,A.1] on the geometric center subspace 5.23 (E.7.2.0.2)S N c∆= {G∈ S N | G1 = 0} (1761)= {G∈ S N | N(G) ⊇ 1} = {G∈ S N | R(G) ⊆ N(1 T )}= {V Y V | Y ∈ S N } ⊂ S N (1762)≡ {V N AV T N | A ∈ SN−1 }(795)then D(G) on that subspace is injective.5.23 The equivalence ≡ in (795) follows from the fact: Given B = V Y V = V N AVN T ∈ SN cwith only matrix A∈ S N−1 unknown, then V † †TNBV N = A or V † N Y V †TN = A .
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5.6. INJECTIVITY OF D & UNIQUE RECONSTRUCTION 3295.6 Injectivity of D & unique reconstructionInjectivity implies uniqueness of isometric reconstruction; hence, we endeavorto demonstrate it.EDM operators list-form D(X) (705), Gram-form D(G) (717), andinner-product form D(Θ) (770) are many-to-one surjections (5.5) onto thesame range; the EDM cone (6): (confer (718) (800))EDM N = { D(X) : R N−1×N → S N h | X ∈ R N−1×N}= { }D(G) : S N → S N h | G ∈ S N + − S N⊥c= { (794)D(Θ) : R N−1×N−1 → S N h | Θ ∈ R N−1×N−1}where (5.5.1.1)S N⊥c = {u1 T + 1u T | u∈ R N } ⊆ S N (1763)5.6.1 Gram-form bijectivityBecause linear Gram-form EDM operatorD(G) = δ(G)1 T + 1δ(G) T − 2G (717)has no nullspace [58,A.1] on the geometric center subspace 5.23 (E.7.2.0.2)S N c∆= {G∈ S N | G1 = 0} (1761)= {G∈ S N | N(G) ⊇ 1} = {G∈ S N | R(G) ⊆ N(1 T )}= {V Y V | Y ∈ S N } ⊂ S N (1762)≡ {V N AV T N | A ∈ SN−1 }(795)then D(G) on that subspace is injective.5.23 The equivalence ≡ in (795) follows from the fact: Given B = V Y V = V N AVN T ∈ SN cwith only matrix A∈ S N−1 unknown, then V † †TNBV N = A or V † N Y V †TN = A .