Gaussian Fitting:
(a) ”bus” sequence, QP = 34.
Fitting parameters:
H
0
:
a
=
6.2212
,
b
=
-
5.4761
e
-
04
,
c
=
6.4005
e
-
02
H
1
:
a
=
7.926754
,
b
=
0.553918
,
c
=
0.050516
(b) ”mobile” sequence, QP = 34.
Fitting parameters:
H
0
:
a
=
7.1948
,
b
=
8.1512
e
-
04
,
c
=
5.3305
e
-
02
H
1
:
a
=
11.842797
,
b
=
0.710918
,
c
=
0.033372
(c) ”paris” sequence, QP = 34.
Fitting parameters:
H
0
:
a
=
4.678730
,
b
=
-
0.017032
,
c
=
0.083650
H
1
:
a
=
8.048697
,
b
=
0.682223
,
c
=
0.049388
(d) ”tempete” sequence, QP = 34.
Fitting parameters:
H
0
:
a
=
5.8060784
,
b
=
-
0.0048921
,
c
=
0.0693044
H
1
:
a
=
7.884043
,
b
=
0.562901
,
c
=
0.049994
(e) ”waterfall” sequence, QP = 34.
Fitting parameters:
H
0
:
a
=
4.9277053
,
b
=
-
0.0058813
,
c
=
0.0836856
H
1
:
a
=
7.339423
,
b
=
0.409214
,
c
=
0.054555
Figure 1:
H0 vs. H1 analysis for all five input sequences with Qp=34.
(a) ”bus” sequence, QP = 40.
Fitting parameters:
H
0
:
a
=
5.498887
,
b
=
-
0.016963
,
c
=
0.073417
H
1
:
a
=
7.963332
,
b
=
0.329699
,
c
=
0.050277
(b) ”mobile” sequence, QP = 40.
Fitting parameters:
H
0
:
a
=
6.2660935
,
b
=
0.0017538
,
c
=
0.0647696
H
1
:
a
=
10.412253
,
b
=
0.476854
,
c
=
0.037460
(c) ”paris” sequence, QP = 40.
Fitting parameters:
H
0
:
a
=
4.7300
,
b
=
-
3.1101
e
-
05
,
c
=
8.1493
e
-
02
H
1
:
a
=
7.280051
,
b
=
0.445942
,
c
=
-
0.056150
(d) ”tempete” sequence, QP = 40.
Fitting parameters:
H
0
:
a
=
5.9628764
,
b
=
0.0044851
,
c
=
0.0662983
H
1
:
a
=
6.643629
,
b
=
0.352375
,
c
=
0.059915
(e) ”waterfall” sequence, QP = 40.
Fitting parameters:
H
0
:
a
=
4.4221210
,
b
=
-
0.0023984
,
c
=
0.0911297
H
1
:
a
=
7.725922
,
b
=
0.249784
,
c
=
0.050042
Figure 2:
H0 vs. H1 analysis for all five input sequences with Qp=40.