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Feb
r
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y
20
22
,
p
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.
229
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1.
I
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RO
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UCT
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T
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cr
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cles
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d
m
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cle
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atig
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m
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ts
[
1
]
.
T
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-
lik
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an
in
ter
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p
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s
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m
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f
th
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p
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te
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tial
(
AP)
o
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all
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to
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its
(
MU
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in
t
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r
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g
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o
f
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d
e
tectin
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elec
tr
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d
es
[
2
]
.
T
h
is
s
i
g
n
al'
s
s
tati
s
tical
p
r
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p
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elate
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m
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cle
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[
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.
T
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[
4
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.
T
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[
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T
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[
6
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.
Mo
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to
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MU
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ly
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d
p
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s
tech
n
iq
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th
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[
7
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.
I
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MU
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d
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I
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p
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[
8
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I
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I
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t J E
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&
C
o
m
p
E
n
g
,
Vo
l.
12
,
No
.
1
,
Feb
r
u
ar
y
20
22
:
2
2
9
-
238
230
MU
AP
p
r
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s
s
in
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tech
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i
q
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T
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PP
)
in
s
p
e
ctio
n
m
eth
o
d
[
9
]
.
Stan
d
ar
d
ized
r
esid
u
als
ev
alu
a
te
th
e
p
r
in
cip
le
o
f
th
e
(
PP
)
m
eth
o
d
ac
co
r
d
in
g
to
th
e
s
ca
le
p
ar
am
eter
esti
m
ato
r
o
f
th
e
o
r
d
er
s
tatis
tics
f
o
r
th
e
s
u
g
g
ested
d
is
tr
ib
u
tio
n
an
d
th
e
in
v
er
s
e
p
r
o
b
ab
ilit
y
o
f
th
e
cu
m
u
lativ
e
d
is
tr
ib
u
tio
n
s
th
at
h
ad
b
ee
n
r
elate
d
t
o
th
e
ass
u
m
ed
d
is
tr
ib
u
tio
n
[
1
0
]
.
Asy
m
p
to
tic
f
o
r
m
u
la
to
en
a
b
le
th
e
ap
p
licatio
n
.
A
v
ar
iety
o
f
n
ew
m
eth
o
d
s
ar
e
p
r
o
p
o
s
ed
to
im
p
r
o
v
e
E
MG
s
ig
n
al
esti
m
atio
n
in
th
e
las
t
f
ew
y
ea
r
s
.
So
m
m
er
et
a
l.
[
1
1
]
,
p
r
o
p
o
s
ed
f
o
u
r
tech
n
iq
u
es
to
esti
m
ate
t
h
e
elb
o
w
jo
in
t
an
g
le
f
r
o
m
s
u
r
f
ac
e
E
MG
.
T
h
ese
m
eth
o
d
s
ar
e
au
to
r
eg
r
ess
iv
e
with
ex
o
g
en
o
u
s
in
p
u
t,
s
ta
te
s
p
ac
e,
au
to
r
eg
r
ess
iv
e
m
o
v
in
g
-
a
v
er
ag
e
with
ex
o
g
en
o
u
s
in
p
u
t,
au
to
r
e
g
r
ess
iv
e
in
teg
r
ate
d
m
o
v
in
g
-
av
er
a
g
e
with
ex
o
g
en
o
u
s
in
p
u
t.
Af
t
er
th
e
m
o
d
el
was
s
elec
ted
,
a
s
ec
o
n
d
e
x
p
er
im
e
n
t
was
p
er
f
o
r
m
ed
i
n
o
r
d
er
t
o
v
a
lid
ate
th
e
esti
m
atio
n
p
r
o
ce
d
u
r
e.
Fu
r
u
i
et
a
l.
[
1
2
]
,
p
r
esen
ts
an
esti
m
atio
n
m
eth
o
d
b
ased
o
n
v
ar
ian
ce
d
is
tr
ib
u
tio
n
an
d
m
ar
g
in
al
lik
elih
o
o
d
m
ax
im
izatio
n
.
T
h
e
ex
p
er
im
en
t
r
esu
lts
s
h
o
w
th
at
th
e
p
r
o
p
o
s
ed
alg
o
r
ith
m
is
m
o
r
e
ac
cu
r
ate
th
an
t
h
e
Gau
s
s
ian
-
b
ased
ap
p
r
o
ac
h
.
W
r
ig
h
t
an
d
Stas
h
u
k
[
1
3
]
d
esc
r
ib
e
a
n
ew
alg
o
r
ith
m
t
o
esti
m
ate
m
o
to
r
u
n
it
p
o
ten
tial
.
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
is
b
ased
o
n
k
er
n
el
weig
h
ted
en
s
em
b
le
av
er
ag
in
g
s
u
p
p
o
r
ted
b
y
d
y
n
am
ic
tim
e
wr
ap
p
in
g
(
DT
W
)
.
T
h
e
ex
p
er
im
en
t
r
esu
lts
s
h
o
w
s
ig
n
if
ican
t
im
p
r
o
v
em
en
t
co
m
p
ar
ed
with
a
s
p
ik
e
-
tr
ig
g
er
e
d
av
er
ag
e.
So
m
m
e
r
an
d
C
o
r
d
er
o
[
1
4
]
,
p
r
o
p
o
s
ed
an
al
g
o
r
ith
m
to
esti
m
ate
E
MG
s
ig
n
al
b
ased
o
n
th
e
Ham
m
er
s
tein
-
wien
er
with
w
av
elet
n
etwo
r
k
.
T
h
e
r
esu
lts
s
h
o
w
lo
w
r
o
o
t
-
m
ea
n
-
s
q
u
ar
e
er
r
o
r
s
(
R
MSE
)
(
1
0
.
8
2
±
3
.
7
3
°)
an
d
h
ig
h
c
o
r
r
elatio
n
s
(
9
4
.
9
0
±
9
2
%)
to
th
e
m
ea
s
u
r
ed
d
ata.
Klin
e
an
d
L
u
ca
[
1
5
]
,
p
r
esen
t
a
m
eth
o
d
f
o
r
er
r
o
r
r
ed
u
ctio
n
co
n
tain
m
u
lti
p
le
d
ec
o
m
p
o
s
itio
n
esti
m
ates
b
ased
o
n
th
e
tr
ad
e
-
o
f
f
b
etwe
en
th
e
y
ield
o
f
MU
AP
tr
ain
s
o
b
tain
ed
f
r
o
m
a
g
iv
en
ac
cu
r
ac
y
lev
el
an
d
th
e
tim
e
o
f
d
ec
o
m
p
o
s
itio
n
.
All th
ese
r
esear
ch
es su
p
p
o
s
e
th
at
th
e
er
r
o
r
s
ig
n
al
is
wh
ite
n
o
is
e.
2.
O
P
T
I
M
AL
F
I
L
T
E
R
I
NG
M
E
T
H
O
DS
T
h
e
id
ea
o
f
o
p
tim
u
m
s
p
ec
tr
a
l
d
en
s
ity
esti
m
ate
ac
co
r
d
in
g
to
th
e
s
u
g
g
ested
d
is
tr
ib
u
tio
n
m
ak
es
n
o
d
if
f
er
en
ce
b
ased
o
n
th
e
p
r
o
ce
d
u
r
es
r
elate
d
to
th
e
r
o
b
u
s
t
f
ilter
in
g
m
eth
o
d
p
r
o
v
ed
by
T
h
o
m
s
o
n
[
1
6
]
.
Nev
er
th
eless
,
with
th
e
ad
d
itio
n
o
f
th
e
weig
h
t
f
u
n
cti
o
n
g
en
e
r
ated
b
y
s
p
ec
if
ic
d
is
tr
ib
u
tio
n
asy
m
p
to
tic
with
th
e
s
h
ap
e
o
f
n
o
r
m
al
d
i
s
tr
ib
u
tio
n
i
n
th
e
a
v
er
ag
e
a
r
ea
,
th
e
ed
g
es
ar
e
h
ea
v
ier
an
d
th
ick
er
th
an
n
o
r
m
al
d
is
tr
ib
u
tio
n
s
[
1
7
]
.
Sin
ce
th
e
MU
AP
d
ata
h
a
v
e
o
u
tlier
s
,
th
e
ass
u
m
p
tio
n
th
a
t
th
e
r
esid
u
al
o
f
A
R
(
p
)
h
as
a
n
o
r
m
al
d
is
tr
ib
u
tio
n
is
v
io
lated
.
T
h
e
ab
ilit
y
o
f
t
h
e
ex
ten
s
io
n
o
f
th
e
r
o
b
u
s
t
f
ilter
in
g
p
r
o
ce
d
u
r
e
m
et
h
o
d
as
a
r
esu
lt
o
f
m
u
lti
-
co
n
tam
in
atio
n
ty
p
es,
wh
ich
r
ef
lect
s
ev
er
al
k
in
d
s
o
f
o
u
tlie
r
s
,
wh
ich
ar
e
eith
e
r
u
p
p
e
r
o
r
lo
wer
o
u
tlier
s
,
o
r
with
in
th
e
s
am
p
lin
g
o
b
s
er
v
a
tio
n
[
1
8
]
.
I
n
co
n
s
eq
u
en
ce
,
t
wo
ty
p
es
o
f
co
n
tam
in
atin
g
d
is
tr
ib
u
tio
n
ca
n
b
e
ch
ar
ac
ter
ized
.
T
ab
le
1
s
h
o
w
s
weig
h
ted
f
ilter
f
o
r
m
u
las
c
o
n
ce
r
n
in
g
th
e
s
tan
d
ar
d
ized
cu
m
u
lativ
e
d
en
s
ity
ac
co
r
d
in
g
to
th
e
s
p
ec
if
ic
d
is
tr
ib
u
tio
n
m
e
n
tio
n
ed
in
[
1
9
]
.
T
ab
le
1
.
W
eig
h
ted
f
ilter
f
o
r
m
u
las co
n
ce
r
n
in
g
th
e
s
tan
d
a
r
d
iz
ed
cu
m
u
lativ
e
d
en
s
ity
A
d
j
u
st
e
d
D
i
st
r
i
b
u
t
i
o
n
F
u
n
c
t
i
o
n
s
F
i
l
t
e
r
W
e
i
g
h
t
e
d
F
u
n
c
t
i
o
n
A
d
j
u
st
e
d
E
x
t
r
e
m
e
V
a
l
u
e
-
S
ma
l
l
e
st
(
)
=
[
−
(
−
(
(
|
|
−
)
)
)
]
A
d
j
u
st
e
d
E
x
t
r
e
m
e
V
a
l
u
e
-
La
r
g
e
s
t
(
)
=
[
−
(
(
(
|
|
−
)
)
)
]
A
d
j
u
st
e
d
C
a
u
c
h
y
(
)
=
0
.
5
+
−
1
tan
−
1
(
(
|
|
−
)
)
A
d
j
u
st
e
d
L
o
g
i
st
i
c
(
)
=
1
/
[
1
+
[
−
(
(
|
|
−
)
)
]
]
A
d
j
u
st
e
d
D
o
u
b
l
e
E
x
p
o
n
e
n
t
i
a
l
(
)
=
{
1
−
0
.
5
[
−
(
(
|
|
−
)
)
)
]
:
≥
0
.
5
[
(
|
|
−
)
]
:
.
.
i
f
u
≥
a
A
d
j
u
st
e
d
N
o
r
ma
l
(
)
=
0
.
5
[
1
+
{
1
−
(
−
2
(
(
|
|
−
)
)
)
2
/
)
}
0
.
5
]
W
h
er
e:
(
)
: is th
e
weig
h
ted
f
ilter
: is th
e
r
esid
u
al
r
an
d
o
m
v
ar
iab
le
: is a
p
ar
am
eter
an
d
=
−
1
(
0
,
1
)
(
1
−
1
/
)
(
0
,
1
)
: th
e
n
atu
r
al
cu
m
u
lativ
e
d
en
s
ity
f
u
n
ctio
n
: n
u
m
b
er
o
f
s
am
p
les p
er
in
ter
v
al
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
E
ffect
o
f o
p
tima
l filter
in
g
p
a
r
a
mete
r
s
fo
r
a
u
to
r
eg
r
es
s
ive
mo
d
el
A
R
(
p
)
…
(
A
ya
d
A
s
a
a
d
I
b
r
a
h
im
)
231
2
.
1
.
Sy
m
m
e
t
ric
co
nta
m
ina
t
e
dis
t
ributio
n
T
h
e
(
∗
)
r
ef
lects
an
y
s
y
m
m
etr
ic
d
is
tr
ib
u
tio
n
,
s
y
n
cs
ab
o
u
t
th
e
ce
n
tr
o
id
o
f
th
e
o
b
s
er
v
ed
s
y
m
m
etr
ic
d
is
tr
ib
u
tio
n
(
:
(
,
2
)
)
,
an
d
s
u
b
s
eq
u
en
tly
(
∗
)
b
ec
o
m
es
(
:
(
,
2
)
)
.
I
n
th
e
ev
en
t
o
f
a
s
tate
s
h
if
t
(
∗
)
wo
u
ld
b
e
(
:
(
±
,
2
)
)
.
T
h
e
s
y
m
m
etr
ic
alter
n
ativ
e
to
th
e
n
o
r
m
al
d
is
tr
ib
u
tio
n
as
a
lo
g
is
tic,
d
o
u
b
le
ex
p
o
n
en
tial,
C
au
ch
y
,
an
d
n
o
r
m
al
d
is
tr
ib
u
tio
n
h
as b
ee
n
ch
o
s
en
.
2
.
2
.
Asy
m
m
et
ric
co
nta
m
ina
t
e
dis
t
ributio
n
T
h
e
(
∗
)
r
ef
lects
an
y
asy
m
m
etr
ic
d
is
tr
ib
u
tio
n
ab
o
u
t
ev
er
y
o
th
er
p
o
in
t
d
is
tin
ctiv
e
f
r
o
m
th
e
lo
ca
tio
n
o
f
(
∗
)
d
is
tr
ib
u
tio
n
.
T
h
e
ce
n
ter
p
o
in
t
o
f
(
∗
)
will
d
if
f
er
f
r
o
m
th
at
o
f
(
μ
)
an
d
will
also
d
if
f
er
f
r
o
m
th
at
o
f
(
∗
)
.
Acc
o
r
d
in
g
ly
,
we
h
av
e
ch
o
s
en
th
e
alter
n
ativ
e
as
y
m
m
etr
ic
d
is
tr
ib
u
tio
n
s
.
A
p
r
elim
in
ar
y
test
f
o
r
th
e
f
it
o
f
th
e
r
esid
u
al
d
is
tr
ib
u
tio
n
s
was
p
er
f
o
r
m
ed
to
esti
m
ate
th
e
f
o
r
m
u
la
f
o
r
th
e
o
p
tim
u
m
weig
h
t.
T
h
e
s
tan
d
ar
d
ized
co
m
m
u
tativ
e
d
en
s
ity
o
f
th
e
r
esid
u
al
d
is
tr
ib
u
tio
n
is
th
o
u
g
h
t
to
b
e
m
o
r
e
ad
v
an
tag
eo
u
s
th
an
th
e
o
th
er
s
tan
d
ar
d
cu
m
u
lativ
e
d
en
s
ities
ex
p
ec
ted
f
o
r
r
esid
u
al
s
ets,
wh
ich
is
r
ef
er
r
ed
to
as
r
o
b
u
s
t f
ilter
in
g
.
As
we
m
en
tio
n
ed
ab
o
v
e,
T
ab
le
1
s
h
o
ws
weig
h
ted
f
ilter
f
o
r
m
u
las
co
n
ce
r
n
in
g
th
e
s
tan
d
ar
d
ized
cu
m
u
lativ
e
d
en
s
ity
ac
co
r
d
in
g
to
th
e
s
p
ec
if
ic
d
is
tr
ib
u
tio
n
m
en
tio
n
ed
in
[
1
9
]
.
T
h
e
d
if
f
er
en
t
m
eth
o
d
s
ar
e
co
m
p
atib
le
with
th
e
d
is
tr
ib
u
tio
n
o
f
r
esid
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al
g
r
ad
e
an
d
th
e
d
eg
r
ee
o
f
s
y
n
th
esis
o
r
d
eter
m
in
atio
n
o
f
th
e
s
ig
n
if
ican
ce
o
f
cr
itical
p
o
in
ts
f
o
r
ap
p
r
o
p
r
iate
test
s
tatis
tics
an
d
g
iv
e
th
e
r
ig
o
r
o
u
s
p
r
o
ce
s
s
o
f
ex
am
in
atio
n
,
co
m
p
ar
is
o
n
,
an
d
ev
alu
atio
n
am
o
n
g
th
e
v
ar
io
u
s
p
r
o
p
o
s
ed
d
is
tr
ib
u
tio
n
s
.
As
s
u
g
g
ested
in
[
1
7
]
,
th
e
p
r
o
b
ab
ilit
y
p
lo
t
ap
p
r
o
ac
h
an
d
ap
p
r
o
p
r
iate
p
ar
am
eter
s
(
f
o
r
ex
am
p
le,
s
in
g
le
co
r
r
elatio
n
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ef
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icien
t m
ea
s
u
r
em
en
t a
n
d
g
o
o
d
n
ess
o
f
f
it a
cc
o
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d
in
g
to
s
tatic
(
SR
)
)
wer
e
ch
o
s
en
.
(
(
)
.
)
)
=
∑
(
−
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(
)
−
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(
−
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2
.
∑
(
(
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−
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2
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0
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5
(
1
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(
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2
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(
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−
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2
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1
=
−
1
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0
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5
(
2
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R
(
t)
:
is
th
e
o
r
d
er
s
tatis
tics
o
f
s
tan
d
ar
d
ize
d
r
esid
u
al
ac
co
r
d
in
g
to
th
e
ass
u
m
ed
d
is
tr
ib
u
tio
n
s
ca
le
p
ar
am
eter
.
K:
d
en
o
tes
th
e
in
v
er
s
e
p
r
o
b
ab
ilit
ies
o
f
th
e
cu
m
u
late
s
am
p
le
d
is
tr
ib
u
tio
n
with
r
esp
e
ct
to
th
e
ass
u
m
ed
d
is
tr
ib
u
tio
n
.
Fig
u
r
e
1
s
h
o
ws th
e
f
lo
wch
ar
t
o
f
th
e
r
o
b
u
s
t o
p
tim
al
f
ilter
alg
o
r
ith
m
f
o
r
th
e
s
u
g
g
ested
m
eth
o
d
.
2
.
2
.
1
.
T
he
s
t
ud
ied
d
is
t
ributio
ns
T
ab
le
2
s
h
o
ws
th
e
ar
ith
m
etica
l
f
o
r
m
u
la
f
o
r
th
e
p
r
o
b
ab
ilit
y
p
lo
t
co
o
r
d
in
ate
m
eth
o
d
,
r
ep
r
esen
tin
g
th
e
in
v
er
s
e
p
r
o
b
ab
ilit
ies o
f
th
e
cu
m
u
lativ
e
s
am
p
lin
g
o
f
n
o
n
-
n
o
r
m
al
d
is
tr
ib
u
tio
n
s
.
−
1
(
+
1
)
−
1
(
−
0
.
5
)
(
3
)
An
d
th
e
s
tan
d
ar
d
ized
r
esid
u
als'
o
r
d
er
s
tatis
tics
:
(
)
=
(
ɛ
(
)
(
.
)
⁄
)
(
4
)
w
h
er
e
SP
=scale
p
ar
am
eter
[
1
9
]
,
[
2
0
]
.
T
h
e
s
tan
d
ar
d
ized
cu
m
u
lativ
e
d
en
s
ity
f
u
n
ctio
n
ca
n
n
o
t
b
e
im
m
ed
iately
ev
alu
ated
to
y
ield
F(u
)
with
r
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ec
t to
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e
r
an
d
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m
v
ar
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w)
.
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)
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−
0
.
5
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e
xp
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−
0
.
5
2
)
−
(
5
)
T
ab
le
2
.
T
h
e
in
v
er
s
e
p
r
o
b
a
b
ilit
ies o
f
th
e
cu
m
u
lativ
e
s
am
p
lin
g
s
is
tr
ib
u
tio
n
f
u
n
ctio
n
s
A
d
j
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st
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d
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i
st
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b
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u
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l
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u
n
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A
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t
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A
d
j
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a
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y
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)
=
0
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5
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1
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−
1
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(
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A
d
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c
(
)
=
1
/
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1
+
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(
(
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−
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A
d
j
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st
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d
D
o
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b
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E
x
p
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t
i
a
l
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=
{
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5
[
−
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:
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5
[
(
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.
.
if
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d
j
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st
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ma
l
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=
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{
1
−
(
−
2
(
(
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−
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2
/
)
}
0
.
5
]
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
12
,
No
.
1
,
Feb
r
u
ar
y
20
22
:
2
2
9
-
238
232
Fig
u
r
e
1
.
T
h
e
f
lo
wch
a
r
t o
f
t
h
e
p
r
o
p
o
s
ed
m
eth
o
d
o
lo
g
y
a
lg
o
r
i
th
m
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
E
ffect
o
f o
p
tima
l filter
in
g
p
a
r
a
mete
r
s
fo
r
a
u
to
r
eg
r
es
s
ive
mo
d
el
A
R
(
p
)
…
(
A
ya
d
A
s
a
a
d
I
b
r
a
h
im
)
233
On
e
o
f
th
e
f
o
llo
win
g
ap
p
r
o
x
im
ate
eq
u
atio
n
was c
h
o
s
en
to
s
o
lv
e
(
5
)
[
1
1
]
:
(
)
≈
0
.
5
(
1
+
(
1
−
e
xp
(
−
2
2
2
)
⁄
)
2
)
(
6
)
at
wh
ich
u
=2
.
8
0
7
,
3
.
0
9
0
,
a
n
d
3
.
4
8
0
f
o
r
1
0
0
,
2
5
0
,
an
d
4
0
0
m
s
ec
win
d
o
ws
r
esp
ec
tiv
ely
at
m
ax
im
u
m
er
r
o
r
≈
0
.
0
0
3
.
Acc
o
r
d
in
g
to
th
e
ab
o
v
e,
a
n
ew
eq
u
atio
n
was d
er
iv
ed
b
y
[
9
]
:
(
)
=
(
7
)
=
(
2
(
−
ln
(
1
−
(
2
−
1
)
2
)
)
)
⁄
0
.
5
(
8
)
−
1
(
)
=
(
(
2
⁄
)
.
(
−
ln
(
1
−
(
2
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1
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2
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0
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5
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9
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1
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(
2
⁄
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(
−
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1
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2
−
−
1
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1
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2
)
)
)
0
.
5
(
1
0
)
T
h
e
in
v
er
s
e
p
r
o
b
ab
ilit
y
o
f
n
o
r
m
al
cu
m
u
late
s
am
p
lin
g
d
is
tr
ib
u
tio
n
s
f
u
n
ctio
n
s
:
−
1
(
−
0
.
5
)
=
(
(
2
⁄
)
(
−
ln
(
1
−
(
2
−
−
1
)
2
)
)
)
0
.
5
(
1
1
)
f
o
r
ea
ch
v
alu
e
o
f
(
T
)
,
we
o
b
tain
±K
t
at
th
e
f
ailed
u
=0
.
T
h
e
f
lo
wch
ar
t
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
alg
o
r
ith
m
is
s
h
o
wn
in
Fig
u
r
e
1
.
I
t
s
tar
ted
with
th
e
d
ata
ac
q
u
is
itio
n
o
f
th
e
in
p
u
t
s
ig
n
als,
th
en
th
e
p
ilo
t
esti
m
atio
n
to
s
elec
t
th
e
o
r
d
er
o
f
th
e
AI
C
cr
iter
io
n
.
A
.
R
b
y
s
eq
u
en
tially
L
S
esti
m
atio
n
to
ca
lcu
late
th
e
er
r
o
r
to
s
et
weig
h
t
wh
ile
th
e
p
r
o
b
ab
ilit
y
p
lo
t
is
in
s
p
ec
ted
.
T
h
e
s
u
b
ject'
s
s
u
b
r
o
u
tin
e
p
er
f
o
r
m
s
th
e
ca
lcu
latio
n
o
f
th
e
d
is
tr
ib
u
tio
n
f
u
n
ctio
n
o
f
weig
h
t.
C
o
n
s
eq
u
en
tly
,
th
e
co
r
r
ec
tio
n
o
f
p
r
e
-
wh
iten
in
g
is
p
er
f
o
r
m
ed
.
Fin
ally
,
th
e
m
in
im
u
m
wh
ite
n
o
is
e
v
alu
e
is
s
elec
ted
.
3.
T
H
E
P
RO
P
O
SE
D
M
E
T
H
O
D
Fig
u
r
e
2
s
h
o
ws
a
b
l
o
ck
d
ia
g
r
am
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
f
o
r
s
y
s
tem
co
n
f
ig
u
r
atio
n
.
Fo
u
r
s
u
b
jects,
m
ales
an
d
f
em
ales,
d
if
f
er
en
t
ty
p
es
o
f
m
u
s
cles,
f
le
x
o
r
,
ex
ten
s
o
r
,
an
d
Ab
d
u
cto
r
Po
llicis
B
r
ev
is
,
ar
e
u
s
ed
in
th
is
in
v
esti
g
atio
n
.
T
h
ese
co
r
r
esp
o
n
d
to
th
e
te
n
s
io
n
s
g
en
er
ate
d
b
y
th
e
s
u
b
jects.
A
two
-
d
im
e
n
s
io
n
al
ar
r
a
n
g
em
en
t
o
f
th
e
m
ea
s
u
r
in
g
elec
tr
o
d
e,
h
ig
h
s
p
atial
r
eso
lu
tio
n
elec
tr
o
m
y
o
g
r
ap
h
y
,
is
u
s
ed
,
d
esig
n
ed
,
an
d
d
ev
elo
p
e
d
b
y
th
e
I
n
s
titu
te
o
f
Ap
p
lied
Me
d
ical
E
n
g
in
ee
r
in
g
,
Helm
h
o
ltz
I
n
s
titu
te
o
f
R
W
T
H
Aac
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en
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a
n
d
Un
iv
er
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ity
Ho
s
p
ital
Aac
h
en
ar
e
u
s
ed
.
Fig
u
r
e
3
s
h
o
ws th
e
elec
tr
o
d
e
ar
r
a
y
ar
r
a
n
g
e
m
en
t.
Fig
u
r
e
2
.
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
o
f
th
e
s
y
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tem
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etu
p
T
h
e
s
e
e
l
e
ct
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o
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e
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h
a
v
e
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d
r
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r
f
a
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e
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o
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e
d
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s
a
u
n
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p
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r
,
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t
h
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s
e
p
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r
at
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o
n
o
f
2
.
5
m
m
.
T
h
e
d
e
t
e
c
t
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d
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e
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o
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a
1
6
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h
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n
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s
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/
D
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o
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r
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I
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I
n
t J E
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&
C
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p
E
n
g
,
Vo
l.
12
,
No
.
1
,
Feb
r
u
ar
y
20
22
:
2
2
9
-
238
234
Fig
u
r
e
3
.
T
h
e
e
lectr
o
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e
a
r
r
ay
a
r
r
an
g
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e
n
t
3
.
1
.
Sp
a
t
ia
l
f
ilte
r
Fo
r
s
p
ec
if
ic
an
d
ac
cu
r
ate
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tr
o
p
h
y
s
io
lo
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ical
an
aly
s
is
o
f
a
s
in
g
le
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o
to
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n
it,
it is
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en
tial
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ed
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c
e
th
e
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ea
o
f
d
etec
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n
.
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o
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er
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m
e
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er
en
t
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o
f
s
u
r
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n
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e
s
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ati
al
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ilter
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m
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ilter
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u
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4
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2
3
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2
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Ro
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tlier
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m
ay
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e
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tr
ib
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lo
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th
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lin
g
o
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s
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C
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eq
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it
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e
s
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T
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e
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o
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th
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r
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d
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th
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ated
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Par
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Han
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Qu
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[
2
4
]
,
wh
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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5
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[
2
6
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.
Fo
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ata
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r
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o
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m
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las
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ch
iter
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ilter
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t=1
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2
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.
.
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u
n
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th
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ter
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im
u
latio
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ates
th
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n
o
is
e
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t
h
at
will
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er
v
e
as
an
in
p
u
t
to
t
h
e
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b
u
s
t
esti
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ato
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el'
s
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u
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.
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n
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al
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is
tr
ib
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tio
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p
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w
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in
g
s
ig
n
al
was
also
g
en
er
ated
as
an
i
n
p
u
t
to
t
h
e
tr
an
s
f
e
r
f
u
n
ctio
n
o
f
th
e
AR
(
n
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p
ar
am
e
ter
,
wh
ile
th
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t
p
u
t is
(
(
)
)
.
4.
E
XP
E
R
I
M
E
N
T
A
L
RE
SUL
T
S
T
h
e
o
p
tim
u
m
esti
m
atio
n
o
f
t
h
e
m
o
d
el'
s
o
r
d
er
f
o
r
th
e
f
o
u
r
s
u
b
jects
an
d
tim
e
in
ter
v
als
o
f
1
0
0
,
4
0
0
,
8
0
0
m
s
ec
ar
e
s
h
o
wn
in
T
ab
le
3
.
T
h
e
r
esu
lts
o
b
tain
ed
s
h
o
w
th
at
FP
E
,
AI
C
,
C
AT
,
an
d
R
.
V.
h
av
e
th
e
o
p
tim
u
m
esti
m
atio
n
o
f
th
e
r
esid
u
al
er
r
o
r
m
o
d
el
o
r
d
er
.
I
r
r
ig
atio
n
p
r
ef
e
r
en
ce
is
g
iv
en
R
V
f
o
r
th
e
s
tab
ilit
y
o
f
th
e
m
o
d
e
l
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d
er
'
s
esti
m
atio
n
r
eg
ar
d
less
o
f
th
e
d
u
r
atio
n
o
f
th
e
win
d
o
w
o
f
in
v
esti
g
atio
n
.
At
th
e
s
am
e
ti
m
e,
R
I
S
s
h
o
ws
th
e
wo
r
s
t
o
r
d
er
esti
m
atio
n
f
o
r
r
esid
u
al
er
r
o
r
.
T
ab
le
4
s
h
o
ws
th
e
s
im
p
ly
co
r
r
elate
d
co
e
f
f
i
cien
t
s
f
o
r
th
e
f
o
u
r
s
u
b
jects
with
win
d
o
ws
1
0
0
,
4
0
0
,
8
0
0
m
s
ec
o
f
th
e
o
p
tim
u
m
d
is
tr
ib
u
tio
n
f
o
r
th
ese
co
ef
f
icien
ts
.
T
h
e
r
esu
lts
s
h
o
w
th
at
SC
C
i
s
s
tatio
n
ar
y
f
o
r
all
th
e
s
tu
d
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2
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0
msec
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FPE
10
10
10
14
14
14
8
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3
3
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10
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.
SC
C
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s
tim
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T
ab
le
5
s
h
o
ws
th
e
m
ea
n
s
q
u
ar
e
o
f
th
e
p
r
e
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wh
iten
in
g
er
r
o
r
s
f
o
r
all
ca
s
es
at
th
e
last
cy
cle
o
f
iter
atio
n
f
o
r
r
o
b
u
s
t
an
d
co
n
v
en
tio
n
al
m
o
d
els.
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h
e
r
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lts
s
h
o
w
th
at
g
o
o
d
im
p
r
o
v
em
en
t
h
as
b
ee
n
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h
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i
n
all
ca
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o
n
s
eq
u
en
tly
,
th
e
c
o
n
v
e
n
tio
n
al
m
o
d
el
is
s
till
s
en
s
i
tiv
e
to
th
e
(
AO)
.
T
h
e
r
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lts
s
h
o
w
th
at
th
e
r
o
b
u
s
t
m
eth
o
d
is
m
o
r
e
ef
f
icien
t
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th
e
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n
v
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n
al
m
eth
o
d
.
Als
o
,
th
e
MU
AP
o
f
all
ca
s
es
s
h
o
ws
th
a
t
th
e
ex
tr
em
e
lar
g
est
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alu
e
d
is
tr
ib
u
tio
n
is
th
e
b
est
m
o
d
el
f
o
r
r
esid
u
al
e
r
r
o
r
.
Fig
u
r
e
5
illu
s
tr
ates
th
e
p
o
wer
s
p
ec
tr
u
m
f
o
r
th
e
r
ea
l
an
d
s
im
u
lated
E
MG
at
th
e
last
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ati
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n
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s
in
g
th
e
ex
tr
em
e
m
o
s
t
ex
ten
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e
d
is
tr
ib
u
tio
n
.
W
ith
in
ty
p
ical
ty
p
e
o
n
g
en
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atin
g
p
r
e
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wh
iten
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g
,
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o
is
e
f
o
r
th
e
s
elec
ted
s
u
b
ject
at
2
5
0
m
s
ec
win
d
o
ws.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
12
,
No
.
1
,
Feb
r
u
ar
y
20
22
:
2
2
9
-
238
236
T
ab
le
5
.
T
h
e
MSE
o
f
th
e
p
r
e
-
wh
iten
in
g
MU
AP f
o
r
th
e
c
o
n
v
en
tio
n
al
an
d
r
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b
u
s
t m
eth
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d
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u
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t
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d
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(
msec
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(
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Fig
u
r
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5
.
T
h
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p
o
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r
s
p
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tr
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m
ad
o
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tin
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E
SV d
is
tr
ib
u
tio
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:
(
a
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er
r
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r
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ig
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(
b
)
f
in
al
iter
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n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
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0
8
E
ffect
o
f o
p
tima
l filter
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g
p
a
r
a
mete
r
s
fo
r
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u
to
r
eg
r
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ive
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el
A
R
(
p
)
…
(
A
ya
d
A
s
a
a
d
I
b
r
a
h
im
)
237
5.
CO
NCLU
SI
O
N
Pro
v
id
e
th
e
in
v
esti
g
atio
n
test
s
o
n
th
e
r
ea
l
a
n
d
s
im
u
lated
E
MG
s
ig
n
als
ac
co
r
d
in
g
to
th
e
s
u
g
g
ested
f
ilter
s
o
f
d
if
f
er
en
t
m
u
s
cles
an
d
win
d
o
ws.
B
y
th
e
co
m
p
ar
is
o
n
o
f
th
e
r
esu
lts
o
f
th
e
r
o
b
u
s
t
p
r
o
p
o
s
ed
m
eth
o
d
as
co
m
p
ar
ed
with
co
n
v
en
tio
n
al
m
e
th
o
d
s
,
we
ca
n
en
u
m
er
ate
th
e
f
o
llo
win
g
co
n
clu
s
io
n
s
:
o
u
r
r
esu
lts
s
h
o
w
th
at
th
e
R
V
tech
n
iq
u
e
g
iv
es
th
e
o
p
tim
al
ap
p
r
o
x
im
atio
n
o
f
t
h
e
m
o
d
el
o
r
d
er
am
o
n
g
th
e
o
th
er
s
u
g
g
ested
s
tu
d
ie
d
tech
n
iq
u
es,
r
eg
ar
d
less
o
f
th
e
ty
p
e
o
f
m
u
s
cles
an
d
in
v
esti
g
atio
n
tim
e
th
at
was
n
o
t
c
o
n
s
id
er
ed
b
y
b
aselin
e
s
tu
d
ies.
W
h
ite
n
o
is
e
er
r
o
r
o
f
th
e
s
im
u
lated
E
MG
s
ig
n
al
h
as
s
lig
h
t
p
r
o
g
r
ess
o
v
er
th
e
p
o
wer
s
p
ec
tr
u
m
esti
m
atio
n
.
C
o
n
s
eq
u
en
tly
,
t
h
e
weig
h
ted
f
ilter
in
g
f
u
n
ctio
n
'
s
s
ig
n
if
ican
ce
r
elate
d
to
o
n
e
o
f
th
e
s
y
m
m
etr
ical
d
is
tr
ib
u
tio
n
is
k
n
o
wn
as
th
e
ex
tr
em
e
lar
g
est
d
is
tr
ib
u
tio
n
.
Me
an
wh
ile,
th
e
ass
u
m
p
tio
n
o
f
n
o
r
m
ality
to
th
e
s
im
u
lated
wh
ite
n
o
is
e
er
r
o
r
s
ig
n
al
h
as
y
ield
ed
.
P
r
o
g
r
ess
at
4
0
0
m
s
ec
win
d
o
w.
T
h
is
im
p
r
o
v
em
e
n
t
th
at
th
e
f
ilter
in
g
o
f
asy
m
m
etr
ical
ty
p
e
o
f
co
n
tam
i
n
atio
n
d
is
tr
ib
u
tio
n
(
ex
tr
em
e
v
al
u
e
d
is
tr
ib
u
tio
n
-
lar
g
est
v
alu
es)
an
d
th
e
m
o
d
if
icatio
n
th
at
th
e
ass
u
m
p
tio
n
o
f
n
o
r
m
ality
f
o
r
th
e
p
r
e
-
wh
ite
n
o
is
e
h
as
b
ee
n
s
tr
en
g
t
h
ed
.
T
h
e
s
u
g
g
ested
r
o
b
u
s
t
m
eth
o
d
im
p
r
o
v
ed
t
h
e
p
r
in
cip
le
o
f
r
o
b
u
s
tn
ess
.
T
h
e
o
b
tain
ed
r
esu
lts
ag
r
ee
with
t
h
at
o
f
co
n
v
en
tio
n
al
r
esu
lts
,
th
e
win
d
o
w
o
f
th
e
s
tu
d
ied
ca
s
es;
m
ea
n
wh
ile,
it
g
iv
es
m
o
r
e
ac
cu
r
ate
r
esu
lts
th
an
th
e
tr
ad
itio
n
a
l
m
eth
o
d
.
RE
F
E
R
E
NC
E
S
[
1
]
M
.
G
o
n
z
a
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z
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a
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.
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C
a
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d
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.
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s
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