Digital Signal Processing Reference
In-Depth Information
The joint output density function can be obtained from ( 5.50 ) and ( 5.51 ):
x 1 ¼ f 1
f X 0 1 X 2 ð x 1 ; x 2 Þ
Jðx 1 ; x 2 Þ
f Xy ðx; yÞ¼
;
(5.52)
ðx; yÞ
x 2 ¼ f 1
ðx; yÞ
where J is a Jacobian of the transformation ( 5.51 ):
x 1 0
x 0 1 þ x 2
x 2
x 0 1 þ x 2
p
p
1
x 0 1 þ x 2
1
x :
J ¼
¼
p
¼
(5.53)
x 2
x 0 1 þ x 2
x 1
x 0 1 þ x 2
Note that the Jacobian of ( 5.53 ) is positive for all values of x (see ( 5.51 )).
From Fig. 5.6 , we have:
x 1 0 ¼ x cos y:
(5.54)
Placing ( 5.51 ) and ( 5.54 ) into ( 5.50 ), we arrive at:
x 2
2 xA cos y þ A 2
2 s 2
1
2 ps 2 e
f X 1 0 X 2 ðx; yÞ¼
:
(5.55)
Finally, from ( 5.52 ), ( 5.53 ), and ( 5.55 ), we get the joint density function of X and y :
for x 0
x 2
2 xA cos y þ A 2
2 s 2
x
2 ps 2 exp
f Xy ðx; yÞ¼
; p y p:
(5.56)
Note that the joint density function ( 5.56 ) cannot be represented as a product of
the marginal densities, indicating that the variables X and y are dependent.
The marginal PDF of the variable X is:
2
4
3
5 :
x 2
þ A 2
2 s 2
xA cos y
s 2
ð
ð
p
p
x
1
2 p
s 2 e
e
f X ðxÞ¼
f Xy ðx; yÞ d y ¼
d y
(5.57)
p
p
The expression in brackets in ( 5.57 ) is the modified zero-order Bessel function I 0
s 2
xA cos y
s 2
ð
p
xA
1
2 p
e
I 0
¼
d y:
(5.58)
p
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