Digital Signal Processing Reference
In-Depth Information
have studied in previous examples in this chapter. The input samples and desired
output values are
x
=
[6
,
36
,
233
,
99
,
37
,
18
,
11
,
7
,
5
,
4
,
3
,
2
,
2
,
2
,
1] mV
y
target
=
[0
,
0
,
150
,
0
,
0
,
0
,
0
,
0
,
0
,
0
,
0
,
0
,
0
,
0
,
0] mV
For the ZFS equalizer we choose
=
12, and for the sign-sign LMS equalizer
we set
µ
equal to
0
.
025. Applying equations (12-29) and (12-30) iteratively
gives the results shown in Figure 12-37, which shows the trajectories of each
algorithm in terms of the mean square error of the equalizer output. The mean
−
0.020
Start
0.018
0.016
0.014
0.012
0.010
0.008
0.006
0.004
End
0.002
0.000
0.50
0.60
0.70
0.80
0.90
1.00
C
0
(a)
0.020
Start
0.018
0.016
0.014
0.012
0.010
0.008
0.006
0.004
End
0.002
0.000
0.5
0.6
0.7
0.8
0.9
1
C
0
(b)
Figure 12-37
Adaptive algorithm convergence for Example 12-6: (a) adaptive ZFS;
(b) adaptive sign-sign LMS.
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