
2 Matrices and Arra ys
condition estimate,isontheorderofeps , the floating-point relative precision,
so the computed inverse is unlikely to be of much use.
Theeigenvaluesofthemagicsquareareinteresting:
e = eig(A)
e=
34.0000
8.0000
0.0000
-8.0000
One of the eigenvalues is zero, which is another co ns eque nce of singularity.
The largest eigenvalue is 34, the magic sum. That is because the vector of all
ones is an eigenvector:
v = ones(4,1)
v=
1
1
1
1
A*v
ans =
34
34
34
34
When a magic square is scaled by its magic sum,
P = A/34
the result is a doubly stochastic matrix whose row and column sums are all 1:
P=
0.4706 0.0882 0.0588 0.3824
2-22
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