Next we will consider the special cases of LU factorizations of square matrices.
Proposition 6.1.1.
If all the principal minors of the matrix
are different from zero, then there exist such lower triangular matrices
L and M with the unit leading diagonal and a diagonal matrix
that
and the decomposition (1) is unique.
Proof. Since all the principal minors of the matrix
are nonzero, then the proposition
1.2.2 implies that there exists the unique LU
factorization of the matrix A
Let
where di=uii (i =1: n). From the regularity
of the matrix A it follows that the matrix D is regular.
Therefore,
and MT=D-1U is an upper triangular
matrix. Hence
The uniqueness of the decomposition (1) follows from the
uniqueness of the factorization (2).
Definition 6.1.1.
The decomposition (1) is called the LDMT
decomposition of the regular matrix .
Example 6.1.1.* Let us find the LDMT
decomposition of the matrix
We state that if the principal minors of the matrix A are different
from zero, then, by taking the matrix A to the triangular form by
the Gauss transformation, we find simultaneously both the matrix L
and the matrix U. Namely, the entry lij
of the lower triangular matrix L equals the factor by which the
j-th row must be multiplied when it is substracted from the i-th
row to delete the entry in the i-th row. We find
and
Let us check:
Proposition 6.1.2. If
the regular matrix
is symmetric and the LDMT
decomposition of it has the form (1), then L=M,
i.e.,
Proof. From decomposition (1)
it follows that
Multiplying both sides of the last equality on the left by matrix M-1,
we get
The matrix M-1AM-T is symmetric
since
The matrix M-1AM-T is a lower
triangular matrix since both M-1 and AM-T=LD
are lower triangular matrices. In virtue of relation (4), the matrix M-1LD
is also symmetric and lower triangular. Therefore, the matrix M-1LD
is diagonal. Since the matrix D is regular, then also the matrix
M-1L is diagonal. In addition, the matrix M-1L
is a lower triangular matrix with the unit diagonal. Hence M-1L=I
or
Problem 6.1.1.* Find the LU
factorization, LDMT
decomposition and LDLT decomposition
of the matrix