v2009.01.01 - Convex Optimization
v2009.01.01 - Convex Optimization v2009.01.01 - Convex Optimization
402 CHAPTER 5. EUCLIDEAN DISTANCE MATRIX 5.8.2.1.1 Shore. The columns of Ξ r V N Ξ c hold a basis for N(1 T ) when Ξ r and Ξ c are permutation matrices. In other words, any permutation of the rows or columns of V N leaves its range and nullspace unchanged; id est, R(Ξ r V N Ξ c )= R(V N )= N(1 T ) (805). Hence, two distinct matrix inequalities can be equivalent tests of the positive semidefiniteness of D on R(V N ) ; id est, −VN TDV N ≽ 0 ⇔ −(Ξ r V N Ξ c ) T D(Ξ r V N Ξ c )≽0. By properly choosing permutation matrices, 5.36 the leading principal submatrix T Ξ ∈ S 2 of −(Ξ r V N Ξ c ) T D(Ξ r V N Ξ c ) may be loaded with the entries of D needed to test any particular triangle inequality (similarly to (958)-(966)). Because all the triangle inequalities can be individually tested using a test equivalent to the lone matrix inequality −VN TDV N ≽0, it logically follows that the lone matrix inequality tests all those triangle inequalities simultaneously. We conclude that −VN TDV N ≽0 is a sufficient test for the fourth property of the Euclidean metric, triangle inequality. 5.8.2.2 Strict triangle inequality Without exception, all the inequalities in (966) and (967) can be made strict while their corresponding implications remain true. The then strict inequality (966a) or (967) may be interpreted as a strict triangle inequality under which collinear arrangement of points is not allowed. [194,24/6, p.322] Hence by similar reasoning, −VN TDV N ≻ 0 is a sufficient test of all the strict triangle inequalities; id est, δ(D) = 0 D T = D −V T N DV N ≻ 0 ⎫ ⎬ ⎭ ⇒ √ d ij < √ d ik + √ d kj , i≠j ≠k (969) 5.8.3 −V T N DV N nesting From (963) observe that T =−VN TDV N | N←3 . In fact, for D ∈ EDM N , the leading principal submatrices of −VN TDV N form a nested sequence (by inclusion) whose members are individually positive semidefinite [134] [176] [287] and have the same form as T ; videlicet, 5.37 5.36 To individually test triangle inequality | √ d ik − √ d kj | ≤ √ d ij ≤ √ d ik + √ d kj for particular i,k,j, set Ξ r (i,1)= Ξ r (k,2)= Ξ r (j,3)=1 and Ξ c = I . 5.37 −V DV | N←1 = 0 ∈ S 0 + (B.4.1)
5.8. EUCLIDEAN METRIC VERSUS MATRIX CRITERIA 403 −V T N DV N | N←1 = [ ∅ ] (o) −V T N DV N | N←2 = [d 12 ] ∈ S + (a) −V T N DV N | N←3 = −V T N DV N | N←4 = [ ⎡ ⎢ ⎣ 1 d 12 (d ] 2 12+d 13 −d 23 ) 1 (d 2 12+d 13 −d 23 ) d 13 = T ∈ S 2 + (b) 1 d 12 (d 1 2 12+d 13 −d 23 ) (d ⎤ 2 12+d 14 −d 24 ) 1 (d 1 2 12+d 13 −d 23 ) d 13 (d 2 13+d 14 −d 34 ) 1 (d 1 2 12+d 14 −d 24 ) (d 2 13+d 14 −d 34 ) d 14 ⎥ ⎦ (c) . −VN TDV N | N←i = . −VN TDV N = ⎡ ⎣ ⎡ ⎣ −VN TDV ⎤ N | N←i−1 ν(i) ⎦ ∈ S i−1 ν(i) T + (d) d 1i −VN TDV ⎤ N | N←N−1 ν(N) ⎦ ∈ S N−1 ν(N) T + (e) d 1N (970) where ⎡ ν(i) = ∆ 1 ⎢ 2 ⎣ ⎤ d 12 +d 1i −d 2i d 13 +d 1i −d 3i ⎥ . ⎦ ∈ Ri−2 , i > 2 (971) d 1,i−1 +d 1i −d i−1,i Hence, the leading principal submatrices of EDM D must also be EDMs. 5.38 Bordered symmetric matrices in the form (970d) are known to have intertwined [287,6.4] (or interlaced [176,4.3] [285,IV.4.1]) eigenvalues; (confer5.11.1) that means, for the particular submatrices (970a) and (970b), 5.38 In fact, each and every principal submatrix of an EDM D is another EDM. [202,4.1]
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5.8. EUCLIDEAN METRIC VERSUS MATRIX CRITERIA 403<br />
−V T N DV N | N←1 = [ ∅ ] (o)<br />
−V T N DV N | N←2 = [d 12 ] ∈ S + (a)<br />
−V T N DV N | N←3 =<br />
−V T N DV N | N←4 =<br />
[<br />
⎡<br />
⎢<br />
⎣<br />
1<br />
d 12 (d ]<br />
2 12+d 13 −d 23 )<br />
1<br />
(d 2 12+d 13 −d 23 ) d 13<br />
= T ∈ S 2 + (b)<br />
1<br />
d 12 (d 1<br />
2 12+d 13 −d 23 ) (d ⎤<br />
2 12+d 14 −d 24 )<br />
1<br />
(d 1<br />
2 12+d 13 −d 23 ) d 13 (d 2 13+d 14 −d 34 )<br />
1<br />
(d 1<br />
2 12+d 14 −d 24 ) (d 2 13+d 14 −d 34 ) d 14<br />
⎥<br />
⎦ (c)<br />
.<br />
−VN TDV N | N←i =<br />
.<br />
−VN TDV N =<br />
⎡<br />
⎣<br />
⎡<br />
⎣<br />
−VN TDV ⎤<br />
N | N←i−1 ν(i)<br />
⎦ ∈ S i−1<br />
ν(i) T + (d)<br />
d 1i<br />
−VN TDV ⎤<br />
N | N←N−1 ν(N)<br />
⎦ ∈ S N−1<br />
ν(N) T + (e)<br />
d 1N (970)<br />
where<br />
⎡<br />
ν(i) = ∆ 1 ⎢<br />
2 ⎣<br />
⎤<br />
d 12 +d 1i −d 2i<br />
d 13 +d 1i −d 3i<br />
⎥<br />
. ⎦ ∈ Ri−2 , i > 2 (971)<br />
d 1,i−1 +d 1i −d i−1,i<br />
Hence, the leading principal submatrices of EDM D must also be EDMs. 5.38<br />
Bordered symmetric matrices in the form (970d) are known to have<br />
intertwined [287,6.4] (or interlaced [176,4.3] [285,IV.4.1]) eigenvalues;<br />
(confer5.11.1) that means, for the particular submatrices (970a) and (970b),<br />
5.38 In fact, each and every principal submatrix of an EDM D is another EDM. [202,4.1]