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a
u
s
s
ia
n
it
y
i
n
o
r
d
er
to
s
ep
ar
ate
th
e
s
ig
n
als
,
w
h
er
e
th
er
e
ar
e
m
a
n
y
m
et
h
o
d
s
f
o
r
m
ea
s
u
r
in
g
t
h
e
g
a
u
s
s
ian
it
y
(
k
u
r
to
s
i
s
[
3
]
,
n
eg
en
tr
p
y
[
4
]
)
.
I
n
o
u
r
p
ap
er
w
e
co
m
b
in
e
th
e
ad
v
an
ta
g
e
o
f
t
h
e
g
a
u
s
s
ian
it
y
a
n
d
s
p
ar
s
it
y
o
f
t
h
e
s
o
u
r
ce
s
ig
n
al,
in
o
r
d
e
r
to
s
ep
ar
ate,
r
ec
o
v
er
in
g
an
d
es
ti
m
ati
n
g
s
o
u
r
ce
s
ig
n
als.
T
o
v
alid
ate
o
u
r
p
r
o
p
o
s
ed
m
e
th
o
d
,
w
e
w
i
ll
u
s
e
au
d
io
s
ig
n
als
f
o
r
r
o
b
o
tic
h
u
m
a
n
o
id
ap
p
licatio
n
s
.
Sp
ar
s
e
d
ec
o
m
p
o
s
itio
n
s
tech
n
i
q
u
es
w
ill
b
e
s
tu
d
ied
in
o
r
d
er
t
o
ch
o
o
s
e
a
s
u
itab
le
alg
o
r
ith
m
w
it
h
b
etter
q
u
a
lit
y
o
f
s
i
g
n
al
s
ep
ar
atio
n
.
2.
T
H
E
P
RO
P
O
SE
D
M
E
T
H
O
D
2
.
1
.
G
a
us
s
ia
nity
ba
s
ed
M
et
ho
ds
f
o
r
Sig
na
l Sepa
ra
t
io
n Alg
o
ri
t
h
m
s
2
.
1
.
1
.
G
ener
a
l M
o
del o
f
B
SS
T
h
e
g
o
al
o
f
t
h
e
B
li
n
d
s
i
g
n
a
l
s
ep
ar
atio
n
(
B
SS
)
is
to
r
ec
o
v
er
a
s
et
o
f
N
u
n
k
n
o
w
n
s
o
u
r
ce
s
f
r
o
m
M
o
b
s
er
v
atio
n
s
r
esu
ltin
g
f
r
o
m
t
h
e
m
i
x
t
u
r
e
o
f
th
e
s
e
s
o
u
r
ce
s
t
h
r
o
u
g
h
u
n
k
n
o
w
n
tr
an
s
m
i
s
s
io
n
c
h
an
n
el
s
.
T
h
e
B
SS
p
r
o
b
lem
is
p
r
esen
t in
m
a
n
y
r
e
al
-
w
o
r
ld
ap
p
licatio
n
s
,
s
u
ch
a
s
b
io
m
ed
ical,
telec
o
m
m
u
n
icatio
n
an
d
s
p
ee
ch
[
5
].
L
et
a
s
et
o
f
t
h
e
s
o
u
r
ce
s
i
g
n
als
d
en
o
ted
b
y
a
v
ec
to
r
s
=[
s
1
(
t)
,
…,
s
N
(
t)
]
T
,
th
e
o
b
s
er
v
atio
n
s
o
r
t
h
e
r
ec
o
r
d
e
d
s
ig
n
al
s
ar
e
x
=
[
x
1
(
t)
,
….
,
x
M
(
t)
]
T
.
T
h
e
m
i
x
t
u
r
e
m
o
d
el
f
o
r
a
b
asic
b
lin
d
s
ig
n
al
s
ep
ar
atio
n
p
r
o
b
lem
is
r
ep
r
esen
ted
b
y
:
(
t
)
A
.
s
(
t
)
x
(
1
)
W
h
er
e
A
(
a
ij
)
is
an
u
n
k
n
o
w
n
Nx
N
i
n
v
er
tib
le
m
i
x
i
n
g
m
atr
i
x
.
I
n
o
r
d
er
to
s
tu
d
y
th
e
s
ig
n
al
s
e
p
ar
atio
n
m
eth
o
d
s
b
ased
o
n
g
a
u
s
s
ian
it
y
,
w
e
co
n
s
id
er
th
e
s
i
m
p
le
ca
s
e,
w
h
er
e
t
h
e
n
u
m
b
er
o
f
s
o
u
r
ce
s
is
eq
u
al
to
th
e
n
u
m
b
er
o
f
s
en
s
o
r
s
(
N
=
M)
,
in
th
is
ca
s
e
th
e
r
o
le
o
f
t
h
e
B
SS
is
to
d
eter
m
i
n
e
a
Nx
N
s
ep
ar
ati
n
g
m
atr
i
x
W
(
w
ij
)
s
u
ch
t
h
at:
(
)
.
(
)
.
(
)
y
t
W
x
t
G
s
t
(
2
)
W
h
er
e
y
is
an
esti
m
ate
o
f
th
e
s
o
u
r
ce
s
ig
n
als
.
2
.
1
.
2
.
I
nd
epe
nd
e
nt
Co
m
po
nent
An
a
ly
s
is
(
I
CA)
I
n
d
ep
en
d
en
t
C
o
m
p
o
n
en
t
An
al
y
s
i
s
(
I
C
A
)
is
a
f
a
m
o
u
s
an
d
class
ical
m
e
th
o
d
u
s
ed
to
s
ep
ar
ate
s
ig
n
als
f
r
o
m
a
lin
ea
r
m
ix
t
u
r
es
o
f
s
ta
tis
tical
i
n
d
ep
en
d
en
t
co
m
p
o
n
e
n
t
.
T
h
e
p
r
in
cip
al
ap
p
licatio
n
s
o
f
I
C
A
ar
e
b
lin
d
s
ig
n
al
(
s
o
u
r
ce
s
)
s
ep
ar
atio
n
an
d
f
ea
tu
r
e
ex
tr
ac
tio
n
(
B
ell
an
d
Sej
n
o
w
s
k
i 1
9
9
6
)
[
6
]
.
A
ll t
h
e
ap
p
licatio
n
s
ca
n
b
e
f
o
r
m
u
lated
in
a
u
n
i
f
ied
m
a
th
e
m
at
ical
f
r
a
m
e
w
o
r
k
:
W
e
o
b
s
er
v
e
n
r
an
d
o
m
v
ar
iab
le
s
x
1
, x
2
, …, x
n
w
h
ic
h
ar
e
lin
ea
r
co
m
b
i
n
atio
n
s
o
f
n
late
n
t v
ar
ia
b
les
s
1
, s
2
, …, s
n
as:
x
i
= a
i1
s
1
+ a
i2
s
2
+ …
+ a
in
s
n
f
o
r
all
i =
1
,
…,
n
W
h
er
e
a
ij
,
1
,
.
.
.
,
n
j
ar
e
s
o
m
e
r
ea
l c
o
ef
f
icien
t
s
.
B
y
d
ef
i
n
it
io
n
,
th
e
s
o
u
r
ce
s
s
i
ar
e
s
tatis
ticall
y
in
d
ep
en
d
e
n
t.
T
h
e
“
la
ten
t
v
ar
iab
les”
ar
e
th
e
s
o
u
r
ce
s
s
i
,
w
h
ic
h
ar
e
al
s
o
ca
lled
th
e
i
n
d
ep
en
d
en
t
co
m
p
o
n
en
ts
.
T
h
e
y
ar
e
ca
lled
“
late
n
t”
b
ec
a
u
s
e
th
e
y
ca
n
n
o
t
d
ir
ec
tl
y
b
e
o
b
s
er
v
ed
o
r
m
ea
s
u
r
ed
.
B
o
th
th
e
i
n
d
ep
en
d
en
t
co
m
p
o
n
e
n
ts
,
s
i
,
an
d
th
e
m
ix
i
n
g
co
ef
f
icie
n
t
s
,
a
ij
,
ar
e
n
o
t
k
n
o
wn
an
d
m
u
s
t b
e
d
eter
m
i
n
ed
(
o
r
esti
m
ated
)
u
s
in
g
o
n
l
y
t
h
e
o
b
s
er
v
ed
d
ata
x
i
[
7
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
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:
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8
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I
J
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C
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Vo
l.
7
,
No
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4
,
A
u
g
u
s
t
2017
:
1
9
0
6
–
1
9
1
4
1908
T
h
e
I
C
A
late
n
t v
ar
iab
le
s
m
o
d
el
is
b
etter
r
ep
r
esen
ted
in
m
atr
ix
f
o
r
m
.
I
f
12
[
,
,
.
.
.
,
]
T
n
S
s
s
s
r
ep
r
esen
ts
th
e
o
r
ig
i
n
al,
m
u
lti
v
ar
iate
d
ata
th
at
is
tr
a
n
s
f
o
r
m
ed
t
h
r
o
u
g
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s
o
m
e
tr
an
s
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m
atio
n
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atr
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p
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g
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ch
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at
:
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H
S
.
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h
en
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C
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tr
ies to
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a
n
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i
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g
m
atr
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ch
t
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at
:
1
WH
.
So
th
at
th
e
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es
u
lt
in
g
m
atr
ix
Y
is
:
()
Y
W
S
W
H
S
S
S
(
s
in
ce
1
WH
)
.
As
w
e
alr
ea
d
y
k
n
o
w
,
t
h
e
o
n
l
y
th
in
g
li
n
ea
r
I
C
A
d
e
m
an
d
s
i
s
t
h
at
th
e
o
r
ig
i
n
al
s
i
g
n
als
12
,
s
.
.
.
,
n
ss
m
u
s
t
b
e
at
an
y
ti
m
e
t
s
tati
s
tical
l
y
i
n
d
ep
en
d
en
t
an
d
th
e
m
i
x
i
n
g
o
f
t
h
e
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u
r
ce
s
b
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li
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ea
r
.
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i
m
p
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r
tan
t
p
r
ep
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tep
b
ef
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e
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en
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ata
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t
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al
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ith
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h
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ep
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n
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elate
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h
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w
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estab
lis
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ed
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l f
o
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m
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k
i
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g
s
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s
e
o
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d
i
m
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l d
ata
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y
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ed
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h
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m
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m
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to
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g
.
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ea
n
s
th
at
its
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m
p
o
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e
n
t
s
ar
e
u
n
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r
r
elate
d
an
d
th
eir
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ar
ia
n
ce
eq
u
al
s
u
n
it
y
.
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h
at
is
,
th
e
co
v
ar
ia
n
ce
m
a
tr
ix
o
f
X
eq
u
als t
h
e
id
en
tit
y
m
atr
ix
I
:
{}
T
E
X
X
I
Fo
r
o
u
r
m
ix
ed
d
ata
X
,
w
h
iten
in
g
m
ea
n
s
th
at
w
e
lin
ea
r
l
y
tr
an
s
f
o
r
m
it
b
y
m
u
ltip
l
y
i
n
g
w
it
h
a
m
atr
i
x
(
s
a
y
V
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s
u
ch
t
h
at
t
h
e
r
esu
l
tin
g
m
atr
ix
Z
is
w
h
ite
:
()
Z
V
X
V
H
S
H
S
.
An
i
m
p
o
r
tan
t
r
esu
lt
o
f
w
h
ite
n
in
g
p
r
o
ce
s
s
is
t
h
at
t
h
e
n
e
w
m
i
x
in
g
m
atr
i
x
H
,
is
o
r
th
o
g
o
n
al
(
i.e
.
its
in
v
er
s
e
is
eq
u
a
l
to
its
tr
an
s
p
o
s
e)
.
I
t
is
i
m
p
o
r
tan
t
to
n
o
te
th
a
t
th
e
w
h
ite
n
in
g
(
o
r
s
p
h
er
in
g
)
p
r
o
ce
s
s
alo
n
e
d
o
es
n
o
t e
n
s
u
r
e
s
tat
is
tical
i
n
d
ep
en
d
en
ce
o
f
X
b
u
t it
p
la
y
s
an
i
m
p
o
r
t
an
t ste
p
i
n
th
e
s
ep
ar
atio
n
p
r
o
c
ess
[
8
]
.
I
n
o
r
d
er
to
u
s
e
t
h
e
n
o
n
g
a
u
s
s
ia
n
it
y
o
f
late
n
t
v
ar
iab
les,
w
e
h
a
v
e
to
m
ea
s
u
r
e
t
h
e
n
o
n
g
au
s
s
ia
n
it
y
i
n
I
C
A
,
w
e
u
s
ed
s
o
m
e
q
u
a
n
tita
tiv
e
m
e
asu
r
e
o
f
n
o
n
g
a
u
s
s
ian
i
t
y
,
li
k
e
Ku
r
to
s
is
(
ab
s
o
l
u
te
v
alu
e)
o
r
it
s
s
q
u
ar
e
v
alu
e.
T
h
e
y
v
an
i
s
h
f
o
r
a
Gau
s
s
ia
n
v
ar
iab
le
,
an
d
th
e
y
ar
e
p
o
s
iti
v
e
f
o
r
m
o
s
t n
o
n
g
au
s
s
ia
n
r
an
d
o
m
v
ar
iab
le
s
[
9
]
.
T
h
e
k
u
r
to
s
i
s
o
r
t
h
e
f
o
u
r
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f
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An
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.
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I
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g
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W
h
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d
i
f
f
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tial e
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l
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I
n
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k
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s
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it
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d
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en
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Gau
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r
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ati
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[
1
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ased
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1
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,
th
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m
b
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eq
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al
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t
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en
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o
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
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I
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N:
2
0
8
8
-
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A
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2
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1
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Def
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T
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Fig
u
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1
.
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p
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Fig
u
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[
1
3
]
.
2
.
2
.
3
.
E
x
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m
ple o
f
us
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ng
S
pa
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Audi
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d
as:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
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8
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I
J
E
C
E
Vo
l.
7
,
No
.
4
,
A
u
g
u
s
t
2017
:
1
9
0
6
–
1
9
1
4
1910
(
)
.
(
)
(
)
x
t
A
s
t
n
t
(
8
)
W
ith
A
is
th
e
NM
m
i
x
in
g
m
atr
ix
an
d
t
h
e
n
o
is
e
()
nt
.
So
th
e
g
o
a
l w
ill
b
e
t
o
esti
m
ate
a
m
ix
in
g
m
atr
ix
A
an
d
th
e
s
o
u
r
ce
s
ig
n
als
()
st
.
No
t
e
th
at
,
m
an
y
s
ig
n
als ca
n
b
e
s
p
ar
s
ely
r
e
p
r
es
en
te
d
u
s
in
g
a
p
r
o
p
er
s
ig
n
al
d
ic
ti
o
n
ar
y
.
T
h
e
s
ca
lar
f
u
n
c
tio
n
ar
e
ca
lled
ato
m
s
o
r
ele
m
e
n
ts
o
f
t
h
e
d
icti
o
n
ar
y
(
th
er
e
ar
e
also
w
a
v
elet
-
r
elate
d
d
ictio
n
ar
ies)
w
h
ic
h
h
a
v
e
to
b
e
g
r
ea
ter
th
an
th
e
s
i
g
n
al
s
ize.
Un
lik
e
i
n
d
ep
en
d
en
t
co
m
p
o
n
e
n
t
a
n
al
y
s
i
s
,
th
e
s
e
ele
m
e
n
ts
d
o
n
o
t
h
av
e
to
b
e
lin
ea
r
l
y
i
n
d
ep
en
d
en
t
[
1
4
]
.
Fig
u
r
e
2
.
R
ep
r
esen
tatio
n
o
f
a
s
p
ar
s
e
s
ig
n
al
u
s
i
n
g
a
Fo
u
r
ier
b
asis
3.
RE
S
E
ARCH
M
E
T
H
O
D
I
n
th
i
s
p
ap
er
,
o
u
r
p
r
o
p
o
s
ed
m
eth
o
d
is
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ased
o
n
co
m
b
i
n
i
n
g
o
f
t
w
o
p
r
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cip
les,
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n
e
is
s
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ar
s
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’
s
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ased
s
tep
,
it
is
u
s
ed
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ep
r
o
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s
s
in
g
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o
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s
s
i
n
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r
d
er
to
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eso
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e
th
e
p
r
o
b
le
m
o
f
t
h
e
u
n
d
er
d
eter
m
i
n
ed
m
i
x
t
u
r
e,
w
h
ic
h
is
co
n
s
id
er
ed
o
n
e
o
f
th
e
g
r
ea
t a
d
v
an
ta
g
es o
f
th
e
s
p
ar
s
i
t
y
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ased
m
et
h
o
d
f
o
r
s
ig
n
al
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s
e
p
ar
a
tio
n
.
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h
e
Gau
s
s
ia
n
it
y
is
u
s
ed
to
s
e
p
ar
ate
th
e
s
ig
n
als
f
r
o
m
t
h
eir
m
i
x
tu
r
e
s
,
s
tar
ti
n
g
to
esti
m
ate
th
e
m
ix
i
n
g
m
atr
i
x
,
th
e
n
m
o
v
i
n
g
to
p
r
o
ce
ed
a
s
ig
n
als
s
ep
ar
atio
n
s
p
r
o
ce
s
s
u
s
in
g
o
f
co
u
r
s
e
t
h
e
es
ti
m
ate
d
m
ix
in
g
m
atr
ix
.
I
f
w
e
r
ec
ei
v
e
m
o
r
e
s
o
u
r
ce
s
t
h
a
n
m
i
x
tu
r
e
s
,
t
h
en
th
e
p
r
o
b
lem
to
esti
m
ate
th
e
m
i
x
i
n
g
m
atr
i
x
a
n
d
th
e
esti
m
ated
s
o
u
r
ce
s
is
co
n
s
id
er
ed
as a
d
if
f
i
cu
lt
m
u
l
tiv
ar
iate
o
p
ti
m
izatio
n
p
r
o
b
lem
[
1
5
].
T
h
e
s
ec
o
n
d
b
lo
ck
i
s
b
ased
o
n
g
au
s
s
ia
n
it
y
(
o
r
n
o
n
g
a
u
s
s
ia
n
it
y
)
,
u
s
ed
as
p
o
s
t
p
r
o
ce
s
s
i
n
g
s
tep
(
o
r
f
in
a
l
s
tep
)
f
o
r
th
e
o
b
s
er
v
ed
s
ig
n
al
s
[
1
6
].
T
h
e
alg
o
r
ith
m
s
b
ased
o
n
s
p
ar
s
it
y
f
o
r
s
ig
n
al
s
ep
ar
atio
n
is
lar
g
el
y
d
i
f
f
er
in
g
f
r
o
m
t
h
e
class
ical
ass
u
m
p
tio
n
o
f
t
h
e
s
tati
s
tic
al
i
n
d
ep
en
d
en
ce
o
f
th
e
s
ig
n
al
s
.
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
F
ig
u
r
e
3
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ep
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s
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h
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o
r
ig
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a
l
s
o
u
r
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s
tah
t
h
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v
e
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ee
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d
u
r
i
n
g
t
h
e
p
r
esen
t
e
x
p
er
i
m
e
n
t,
u
s
i
n
g
au
d
io
s
p
ac
e
s
ig
n
als
ta
k
in
g
f
r
o
m
I
C
AL
A
B
,
th
e
r
es
u
lt
s
ee
n
in
t
h
e
F
i
g
u
r
e
4
,
af
ter
u
s
in
g
th
e
p
r
o
p
o
s
ed
m
et
h
o
d
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
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I
SS
N:
2
0
8
8
-
8708
A
N
o
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o
d
b
a
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Ga
u
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ia
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ig
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a
l S
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a
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tio
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lg
o
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ith
ms (
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u
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u
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Fig
u
r
e
3
.
T
h
e
o
r
ig
in
al
s
p
ar
s
e
s
o
u
r
ce
s
Fig
u
r
e
4
.
FP
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C
A
est
i
m
a
ted
o
u
tp
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ts
T
o
d
escr
i
b
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th
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p
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e
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f
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C
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a
lg
o
r
it
h
m
,
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e
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s
e
n
o
t
o
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l
y
t
h
e
es
ti
m
ated
m
ix
i
n
g
m
atr
i
x
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u
t
w
e
h
av
e
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s
e
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d
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ep
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ith
m
,
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s
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tte
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in
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Sig
n
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F
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g
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r
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m
o
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at
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at:
Fig
u
r
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5
.
Sig
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atio
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S
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s1
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I
SS
N
:
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0
8
8
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I
J
E
C
E
Vo
l.
7
,
No
.
4
,
A
u
g
u
s
t
2017
:
1
9
0
6
–
1
9
1
4
1912
Hig
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f
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ea
n
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h
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ith
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ig
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ea
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er
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ith
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u
r
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6
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u
r
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6
.
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ter
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R
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r
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th
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m
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d
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=
0
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0
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4
T
h
e
s
ca
tter
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f
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ated
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n
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ig
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r
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7
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:
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u
r
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.
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ated
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.
7
3
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B
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
J
E
C
E
I
SS
N:
2
0
8
8
-
8708
A
N
o
ve
l Meth
o
d
b
a
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ith
ms (
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id
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5.
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r
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s
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h
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et
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e
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ate
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s
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ar
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d
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A
a
lg
o
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it
h
m
f
o
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d
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s
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g
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al
s
.
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h
is
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ld
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f
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in
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ice
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ed
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o
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test
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g
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h
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q
u
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d
t
h
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p
er
f
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m
an
ce
o
f
th
e
s
ep
ar
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n
,
w
h
i
c
h
r
ev
ea
le
d
th
e
p
o
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f
u
s
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is
t
w
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m
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h
o
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s
to
g
et
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er
as a
co
m
m
o
n
p
o
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f
u
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ch
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iq
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e.
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h
e
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u
m
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to
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s
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eth
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licatio
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u
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id
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o
t.
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E
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NC
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S
[1
]
Ka
y
o
d
e
F
.
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in
g
b
a
d
e
a
n
d
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k
a
A
.
A
li
m
,
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p
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ra
ti
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f
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d
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e
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l
g
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h
m
”
,
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ter
n
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ti
o
n
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l
J
o
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rn
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l
o
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e
c
trica
l
a
n
d
Co
mp
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En
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(
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)
,
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l.
4
,
n
o
.
4
,
p
p
.
5
5
7
-
560
,
2
0
1
4
.
[2
]
Y.
Ch
e
n
,
J.
M
e
n
g
,
“
S
tu
d
y
o
n
BS
S
A
lg
o
rit
h
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se
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o
n
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a
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lt
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g
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e
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NI
KA
In
d
o
n
e
sia
n
J
o
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rn
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l
o
f
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trica
l
En
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rin
g
,
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o
l.
1
1
,
n
o
.
6,
pp.
2
9
4
2
-
2
9
4
7
,
2
0
1
3
.
[3
]
Ré
m
i
G
rib
o
n
v
a
l,
S
y
lv
a
in
L
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sa
g
e
,
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S
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rv
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p
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rs
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m
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t
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lys
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in
d
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c
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s”
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ES
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,
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3
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7
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[4
]
Yu
a
n
q
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L
i,
A
n
d
rz
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c
k
i,
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h
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n
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a
ri,
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p
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mp
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lys
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f
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r
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d
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ti
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wit
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les
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S
e
n
so
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n
S
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th
In
tern
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ti
n
a
l
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m
p
o
siu
m
o
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In
d
e
p
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n
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t
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ly
sis
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n
d
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n
d
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ig
n
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3
),
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p
ri
l
2
0
0
3
,
Na
ra
,
Ja
p
a
n
.
[5
]
J
.
-
L
.
S
tarc
k
,
M
.
El
a
d
,
D.
L
.
D
o
n
o
h
o
,
“
Re
d
u
n
d
a
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m
u
lt
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a
le
tr
a
n
sf
o
rm
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th
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li
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ti
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f
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r
M
o
rp
h
o
l
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ica
l
Co
m
p
o
n
e
n
t
A
n
a
ly
sis,”
J
o
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rn
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l
o
f
Ad
v
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n
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e
s i
n
Ima
g
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tro
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s
,
v
o
l
.
1
3
2
,
p
p
.
2
8
7
–
3
4
8
,
2
0
0
4
.
[6
]
S
.
Krs
tu
l
o
v
ic,
R.
G
rib
o
n
v
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l
,
“
M
P
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M
a
tch
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P
u
rsu
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t
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d
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T
r
a
c
tab
le,”
in
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ro
c
.
I
n
t.
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.
A
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.
S
p
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h
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ig
n
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P
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s.
[7
]
O.
Yilm
a
z
,
S
.
Rick
a
rd
,
”
Bli
n
d
S
e
p
a
ra
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f
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ix
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v
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m
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-
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re
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y
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”
,
IEE
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ra
n
s
a
a
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ti
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n
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l
Pro
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v
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2
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7
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1
8
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0
–
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8
4
7
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2
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4
.
[8
]
P
.
G
.
G
e
o
rg
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v
,
F
.
T
h
e
is,
A
.
Cich
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k
i,
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S
p
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f
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d
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term
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d
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ix
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re
s”
,
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E
T
ra
n
sa
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ti
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r
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l
Ne
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4
,
p
p
.
9
9
2
–
9
9
6
,
2
0
0
5
.
[9
]
F.
J.
T
h
e
is,
A
.
Ju
n
g
,
C.
G
.
P
u
n
t
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,
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a
n
g
E.
W
.
“
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in
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r
g
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tri
c
I
C
A
:
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m
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tals
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n
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l
g
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rit
h
m
s”
,
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ra
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mp
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ti
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,
1
5
(2
):
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1
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-
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3
9
,
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e
b
ru
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ry
2
0
0
3
.
[1
0
]
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.
Ik
h
le
f
,
D.
L
e
G
u
e
n
n
e
c
,
“
A
S
im
p
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f
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sta
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o
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lu
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A
lg
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ls
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Crit
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n
w
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rn
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1
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J.
F.
Ca
rd
o
so
,
A
.
S
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lo
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m
iac
,
“
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li
n
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on
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ian
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ig
n
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ls”
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IEE
PR
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–
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v
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l.
1
4
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,
n
o.
6,
De
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e
m
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.
[1
2
]
S
.
M
a
k
in
o
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.
-
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e
,
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S
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w
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d
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,
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n
d
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p
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h
S
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p
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ra
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”
,
S
p
ri
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g
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r
,
2
0
0
7
.
[1
3
]
A.
A
is
sa
-
El
-
Be
y
,
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Re
p
ré
se
n
tatio
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s
P
a
rc
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p
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tag
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,
HD
R
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.
[1
4
]
V
.
M
a
ti
c
,
W
.
De
b
u
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,
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mp
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ris
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o
f
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A
l
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th
ms
fo
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CG
Art
if
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c
t
Rem
o
v
a
l
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m
EE
G
S
ig
n
a
ls”
,
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E
-
EM
BS
Be
n
e
lu
x
Ch
a
p
ter S
y
m
p
o
siu
m
,
2
0
0
9
.
[1
5
]
O.
C
h
a
k
k
o
r,
Ca
rlo
s
Ga
r
c
ia
P
u
n
to
n
e
t,
M
o
h
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m
m
e
d
Ess
a
a
d
i,
“
A
S
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f
S
ig
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l
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ra
ti
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lg
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m
s
”,
In
ter
n
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t
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l
J
o
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rn
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n
s
,
v
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5
4
,
n
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8
,
2
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1
2
.
[1
6
]
H.
A
b
o
u
z
id
,
O.
Ch
a
k
k
o
r,
“
Bli
n
d
A
u
d
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rt”,
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.
4
,
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2
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5
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