Digital Signal Processing Reference
In-Depth Information
since
a
k
>
0
.
The lower bound on the right-hand side can therefore be achieved
if we choose the optimal
U
f
to be the unitary matrix that diagonalizes
H
†
H
completely and arranges diagonal elements as in Eq. (12.44). The proof of the
above lemma is therefore complete once we prove Eq. (12.45):
Proof of Eq. (12.45).
The proof is based on a beautiful theorem on Hermi-
tian matrices which we first review (see Horn and Johnson [1985], p. 189).
Recall first that all eigenvalues of a Hermitian matrix are real. Let
A
be a
P
×
P
Hermitian matrix and let
A
M
be any
M
×
M
principal submatrix,
that is, a matrix obtained by deleting any
P
M
rows and the corresponding
columns from
A
.
Let the eigenvalues of
A
be arranged as
−
λ
0
(
A
)
≥ λ
1
(
A
)
...≥ λ
P−
1
(
A
)
(12
.
47)
and let the eigenvalues of
A
M
be arranged as
λ
0
(
A
M
)
≥ λ
1
(
A
M
)
...≥ λ
M−
1
(
A
M
)
.
(12
.
48)
Then the eigenvalues
λ
k
(
A
M
) are interleaved between the eigenvalues
λ
k
(
A
)
as follows:
λ
0
(
A
)
≥
λ
0
(
A
M
)
≥
λ
L
(
A
)
,
λ
1
(
A
)
≥
λ
1
(
A
M
)
≥
λ
L
+1
(
A
)
,
.
λ
M−
1
(
A
)
≥
λ
M−
1
(
A
M
)
≥
λ
P−
1
(
A
)
,
where
L
=
P
M
. This is demonstrated in Fig. 12.4. Now consider any
unitary matrix
U
f
which has performed the partial diagonalization (12.37).
The eigenvalues of the
M
−
M
leading principal submatrix of
U
f
H
†
HU
f
are
clearly
μ
k
,
whereas the eigenvalues of
U
f
H
†
HU
f
are just
σ
h,k
(eigenvalues
of
H
†
H
) regardless of
U
f
.
The interlacing property
×
σ
h,k
≥
σ
h,k
+
L
,
μ
k
≥
0
≤
k
≤
M
−
1
,
(12
.
49)
therefore holds. This implies in particular that Eq. (12.45) is true.
12.4.3 Finding the optimal
Σ
f
With the optimal unitary
U
f
shown to be the matrix that diagonalizes
H
†
H
,
we now turn to the computation of the optimal coe
cients
a
k
in Eq. (12.38)
which determine the diagonal elements of
Σ
f
. For this, recall again the neces-
sary condition (12.32) for optimality derived earlier based on stationarity of the
Lagrangian. This condition is reproduced below:
(
F
†
H
†
HF
)
−
1
=
η
F
†
F
,
(12
.
50)
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