Digital Signal Processing Reference
In-Depth Information
1.10
Fourth-Order Moment Approximation
Instead of the small-step-size approximation of Section 1.8, we can choose to
approximate the fourth-order moment that appears in the expression for
in Equation 1.17 as
E
u i
E u i u i
g [ u i ]
E
2
2
g [ u i ]
u i
u i
g 2 [ u i ] u i
·
=
P Tr
(
P
)
,
would become
where P
=
E
(
u i u i
/
g [ u i ]
)
. In this way, Expression 1.17 for
= µ
2 P Tr
P
µ
P
+ µ
(
P
)
,
(1.50)
which is fully characterized in terms of the single moment P .Ifwenow
let P
U T
=
U
denote the eigen-decomposition of P
>
0, and introduce the
transformed quantities:
U T
U T
=
=
=
.
w i
w i ,
u i
u i U,
U
Then variance Relations 1.16 and 1.50 can be equivalently rewritten as
E
,
2
g 2 [ u i ]
u i
2
2
2
2
v
E
w i
=
E
w i 1
+ µ
σ
(1.51)
2
= µ µ + µ
Tr
().
shows that it will be diagonal as long as
The expression for
is diagonal.
Thus let again
σ =
σ =
diag
()
,
diag
(
).
Then from Equation 1.51 we find that
σ =
F
σ
,
where F is M
×
M and given by
2 , B,
2
T ,
F
=
I
µ
A
+ µ
A
=
2
,
B
= µ
δδ
where
. Repeating the arguments that led to Equation 1.22 we
can establish that, un der the assumed fourth-order moment approximation,
the evolution of E
δ =
diag
()
2
σ
w i
is described by an M -dimensional state-space model
similar to Equation 1.37.
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