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A new
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o
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c
ts,
li
k
e
a
n
e
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e
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c
a
l
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c
ti
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it
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lea
d
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g
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c
re
a
se
s
in
t
h
e
c
h
a
ll
e
n
g
e
s
i
n
a
n
a
ly
z
in
g
th
e
e
lec
tro
e
n
c
e
p
h
a
lo
g
r
a
m
fo
r
o
b
tai
n
in
g
u
se
fu
l
c
li
n
ica
l
i
n
fo
rm
a
ti
o
n
.
In
th
is
p
a
p
e
r,
we
d
o
a
c
o
m
p
a
riso
n
o
f
u
sin
g
two
d
e
c
o
m
p
o
sin
g
m
e
th
o
d
s
(DWT
a
n
d
E
M
D)
wit
h
CCA
tec
h
n
i
q
u
e
o
r
Hig
h
P
a
ss
F
il
ter,
fo
r
th
e
e
li
m
in
a
ti
o
n
o
f
e
y
e
a
rti
fa
c
ts
fro
m
EE
G
.
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e
e
y
e
a
rti
fa
c
ts
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)
sig
n
a
ls
we
re
e
x
tr
a
c
t
e
d
fro
m
th
e
u
n
-
c
lea
n
e
d
o
r
ra
w
EE
G
sig
n
a
ls
b
y
DWT
a
n
d
EM
D
wi
th
CC
A
a
p
p
ro
a
c
h
o
r
H.P
.
F
.
Th
e
ro
o
t
m
e
a
n
s
s
q
u
a
re
e
rro
r
ra
ti
o
o
f
th
e
u
n
c
o
n
tam
in
a
ted
EE
G
sig
n
a
l
to
th
e
c
o
n
tam
in
a
t
e
d
EE
G
sig
n
a
l
wit
h
e
y
e
a
rti
f
a
c
ts
we
re
th
e
p
e
rfo
rm
a
n
c
e
in
d
ica
to
rs
f
o
r
b
o
th
e
li
m
in
a
ti
o
n
m
e
th
o
d
s,
w
h
ich
i
n
d
ica
te
th
a
t
th
e
c
o
m
b
in
e
d
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m
e
th
o
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o
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t
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e
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e
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o
m
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in
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m
e
th
o
d
in
th
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e
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m
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a
ti
o
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o
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e
y
e
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li
n
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i
n
g
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o
n
tam
in
a
ti
o
n
a
rti
fa
c
t
fro
m
t
h
e
EE
G
sig
n
a
l.
K
ey
w
o
r
d
s
:
CCA
DW
T
EEG
EMD
E
OG
H.
P.F
.
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r
th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Fad
ia
No
o
r
i H
u
m
m
a
d
i A
l
-
Nu
aim
y
,
B
io
m
ed
ical
E
n
g
in
ee
r
in
g
Dep
a
r
tm
en
t,
Un
iv
er
s
ity
o
f
B
ag
h
d
a
d
,
B
ag
h
d
ad
,
I
r
aq
.
E
m
ail:
f
ad
ian
o
o
r
i2
0
1
8
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
s
ca
lp
E
E
G
s
ig
n
als
ar
e
u
s
u
ally
in
th
e
r
an
g
e
o
f
1
0
-
1
0
0
µV
.
T
h
ese
lo
w
v
o
ltag
e
s
ig
n
al
s
ar
e
ea
s
ily
ex
p
o
s
ed
to
v
ar
io
u
s
n
o
is
e
c
o
n
tam
in
atio
n
[
1
-
4
]
.
T
h
e
cle
an
ed
/p
u
r
e
E
E
G
s
ig
n
als
ar
e
wid
ely
ap
p
licab
le.
T
h
e
clea
n
ed
E
E
G
s
ig
n
als
ar
e
v
er
y
u
s
ef
u
l
in
r
esear
ch
es
an
d
to
th
e
p
h
y
s
ician
s
[
5
,
6
]
.
I
n
p
r
e
v
io
u
s
s
tu
d
ies,
th
er
e
a
r
e
a
v
ar
iety
o
f
s
im
p
le
an
d
a
d
v
an
ce
d
s
ig
n
al
p
r
o
ce
s
s
in
g
tec
h
n
iq
u
es
th
at
co
u
ld
b
e
u
s
ed
to
elim
in
ate/r
em
o
v
e
th
e
ar
tifa
cts
co
n
tam
in
atin
g
th
e
E
E
G
r
ec
o
r
d
e
d
s
ig
n
als.
T
h
e
E
E
G
ar
tifa
cts
co
u
ld
b
e
a
s
im
p
le
s
ig
n
al
th
at
co
u
ld
ea
s
ily
b
e
r
em
o
v
ed
b
y
s
im
p
le
tech
n
iq
u
es,
s
u
c
h
as
lo
w
p
ass
d
ig
ital
f
ilter
,
b
an
d
p
ass
d
ig
ital
f
ilter
,
an
d
o
th
er
s
.
T
h
ese
tech
n
iq
u
es
a
r
e
ef
f
ec
tiv
e
f
o
r
clea
n
in
g
E
E
G
s
ig
n
als
if
an
d
o
n
ly
if
th
e
ar
tifa
cts
d
id
n
o
t
lie
with
in
th
e
in
f
lu
en
tial sp
ec
tr
u
m
o
f
t
h
e
u
s
ef
u
l E
E
G
s
ig
n
als f
o
r
r
ed
u
ci
n
g
th
e
p
o
wer
lin
e
a
r
tif
ac
ts
an
d
DC
d
r
if
ts
.
Oth
er
wis
e,
th
e
b
io
l
o
g
ical
E
E
G
ar
tifa
cts
ar
e
v
er
y
d
if
f
icu
lt
to
r
em
o
v
e
with
o
u
t
lo
s
in
g
th
e
E
E
G
d
ata/in
f
o
r
m
atio
n
d
u
r
i
n
g
th
e
cl
ea
n
in
g
p
r
o
ce
s
s
.
T
h
is
is
b
ec
au
s
e
th
is
ty
p
e
o
f
E
E
G
ar
tifa
ct
s
h
ar
es
th
e
f
r
eq
u
e
n
cy
s
p
ec
tr
u
m
with
r
aw
E
E
G
s
ig
n
als,
r
en
d
e
r
in
g
it
h
ar
d
to
s
ep
ar
ate
f
r
o
m
t
h
e
d
esire
d
s
p
ec
tr
u
m
.
Ma
n
y
s
ig
n
al
p
r
o
ce
s
s
in
g
clea
n
in
g
tech
n
iq
u
e
s
wer
e
p
r
o
p
o
s
ed
to
s
o
lv
e
th
is
.
An
ad
v
an
ce
d
s
ig
n
al
p
r
o
ce
s
s
in
g
tech
n
iq
u
e
b
ased
on
b
lin
d
s
o
u
r
ce
s
ep
ar
atio
n
(
b
lin
d
s
o
u
r
ce
s
ep
a
r
atio
n
(
B
SS
)
:
p
r
in
cip
al
c
o
m
p
o
n
en
t
a
n
aly
s
is
(
PC
A
)
,
ca
n
o
n
ical
co
r
r
elatio
n
an
aly
s
is
(
CCA
)
[
7
]
,
an
d
I
C
A
c
o
u
ld
b
e
im
p
lem
en
ted
to
r
em
o
v
e
t
h
e
e
y
eb
lin
k
,
E
C
G,
E
MG
,
a
n
d
o
th
er
b
io
lo
g
ical
ar
tifa
cts.
Ot
h
er
tech
n
iq
u
es
s
u
c
h
as
a
d
ap
t
iv
e
d
ig
ital
f
ilter
,
E
MD
tech
n
iq
u
es,
f
ast
f
o
u
r
ier
tr
an
s
f
o
r
m
(
FFT
)
,
W
av
elet
-
b
ased
d
en
o
is
in
g
ar
e
also
a
p
p
licab
le.
I
n
th
is
s
tu
d
y
,
a
n
em
p
ir
ical
m
o
d
e
d
ec
o
m
p
o
s
itio
n
(
E
MD
)
tech
n
i
q
u
e
will b
e
u
s
ed
to
r
em
o
v
e
th
e
ar
tifa
ct
f
r
o
m
t
h
e
r
aw
r
ec
o
r
d
ed
E
E
G
s
ig
n
als.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
A
n
ew elimin
a
tin
g
E
OG
a
r
tifa
cts tec
h
n
iq
u
e
u
s
in
g
c
o
mb
in
ed
…
(
F
a
d
ia
N
o
o
r
i H
u
mma
d
i
A
l
-
N
u
a
imy
)
2581
I
n
o
t
h
er
wo
r
d
s
,
an
E
E
G
s
ig
n
al
is
a
r
ec
o
r
d
o
f
th
e
n
e
u
r
o
n
al
elec
tr
ical
ac
tiv
ity
th
at
is
h
ap
p
en
in
g
as
a
r
esu
lt
o
f
th
e
ac
tiv
ity
o
f
m
a
n
y
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en
d
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ites
th
at
wer
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p
t
ically
ex
cited
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o
n
n
ec
ts
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lar
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e
n
u
m
b
er
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p
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am
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al
n
eu
r
o
n
s
in
t
h
e
ce
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e
b
r
al
co
r
te
x
.
R
ec
o
r
d
i
n
g
s
o
f
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a
w
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E
G
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ig
n
als
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e
n
o
r
m
ally
co
n
tam
in
a
n
ts
with
d
if
f
er
en
t
elec
tr
ical
ar
tifa
ct
s
ig
n
a
ls
.
T
h
ese
elec
tr
ical
ar
tifa
ct
s
ig
n
als
ca
m
e
f
r
o
m
in
ter
n
al
an
d
ex
ter
n
al
s
o
u
r
ce
s
.
T
h
e
in
ter
n
al
ar
tifa
ct
s
o
u
r
ce
s
lik
e
b
io
lo
g
ical
s
o
u
r
ce
s
s
im
ilar
to
E
OG,
E
C
G,
an
d
E
MG
,
wh
ile
ex
ter
n
al
ar
tifa
ct
s
o
u
r
ce
s
lik
e
lin
e
p
o
wer
in
ter
f
er
en
ce
an
d
o
r
lead
s
.
T
h
e
E
O
G
g
en
er
ates
a
s
ig
n
if
ican
t
an
d
af
f
ec
ted
ar
tifa
ct
in
th
e
E
E
G
s
ig
n
als.
T
h
e
v
is
io
n
ac
tio
n
in
th
e
e
y
e
m
atch
ed
an
elec
tr
ic
d
ip
o
le
in
w
h
ich
,
th
e
co
r
n
ea
ac
ts
as
th
e
n
eg
ativ
e
p
ar
t
an
d
th
e
r
etin
a
ac
ts
as
th
e
p
o
s
itiv
e
p
ar
t.
T
h
e
o
cu
lar
ar
tifa
cts
ca
n
b
e
o
b
s
er
v
ed
in
E
E
G
r
ec
o
r
d
s
w
h
ich
ar
e
th
e
ey
e
b
lin
k
s
an
d
t
h
e
ey
e
m
o
v
em
en
ts
wh
ich
h
a
v
e
r
esu
lted
f
r
o
m
th
e
c
h
an
g
es
in
th
e
elec
tr
ical
f
ield
ar
o
u
n
d
th
e
ey
e
d
u
r
in
g
m
o
v
em
en
t a
n
d
b
lin
k
in
g
,
th
is
is
h
o
w
E
OG
ar
tifa
ct
s
ig
n
als g
en
er
ate.
T
h
e
ey
e
b
lin
k
in
g
ca
n
b
e
r
e
p
r
esen
ted
b
y
a
lo
w
-
f
r
eq
u
e
n
cy
s
ig
n
al
(
<
4
Hz)
with
a
h
ig
h
a
m
p
litu
d
e.
T
h
e
ey
e
b
lin
k
in
g
ac
tio
n
m
ai
n
ly
lo
ca
ted
in
t
h
e
f
r
o
n
t
l
o
o
p
elec
tr
o
d
es
(
FP
1
,
FP
2
)
a
n
d
it
is
an
asy
m
m
etr
ical
ac
tiv
ity
with
lo
w
p
r
o
p
ag
atio
n
.
Mo
r
eo
v
er
,
ey
e
m
o
v
e
m
en
t
ca
n
also
b
e
r
ep
r
esen
ted
b
y
a
lo
w
-
f
r
eq
u
e
n
cy
s
ig
n
a
l
(
<
4
Hz)
b
u
t
with
a
h
ig
h
er
p
r
o
p
ag
atio
n
[
8
]
.
T
o
elim
in
ate
o
r
r
em
o
v
e
o
c
u
lar
ar
tifa
cts
(
E
O
G)
in
th
e
r
ec
o
r
d
ed
E
E
G
s
ig
n
als,
m
an
y
m
eth
o
d
s
h
av
e
b
ee
n
r
ep
o
r
ted
an
d
u
s
ed
in
th
e
p
r
ev
i
o
u
s
wo
r
k
s
,
s
u
ch
as
I
C
A,
C
C
A
[
9
]
.
R
eg
r
ess
io
n
-
b
ased
m
eth
o
d
s
,
Hig
h
p
ass
-
f
ilter
in
g
[
1
0
]
a
n
d
Ad
ap
tiv
e
f
ilter
in
g
.
Ho
we
v
er
,
s
o
m
e
E
OG
a
r
tifa
ct
elim
in
atin
g
m
eth
o
d
s
n
ee
d
s
o
m
e
s
p
atial
ca
r
e
lik
e
I
C
A
wh
i
ch
,
ca
n
n
o
t
b
e
ap
p
lied
o
n
lin
e
[
1
1
]
.
Mo
r
e
o
v
er
,
all
o
th
er
ar
tifa
ct
elim
in
atio
n
m
eth
o
d
s
ad
d
c
o
m
p
lex
ity
t
o
th
e
r
ec
o
r
d
ed
s
y
s
tem
[
1
2
]
.
B
ased
o
n
th
at
E
OG
a
r
tifa
cts
g
en
er
al
ly
c
o
n
tain
s
f
r
o
m
l
o
w
-
f
r
eq
u
e
n
cy
c
o
m
p
o
n
en
ts
,
th
er
e
f
o
r
e
u
s
in
g
a
h
ig
h
-
p
ass
f
ilter
will
b
e
u
s
e
f
u
l
to
r
em
o
v
e
m
o
s
t
o
f
th
e
E
OG's
ar
tifa
cts
[
1
0
]
.
Ho
wev
er
,
th
is
E
OG
ar
tifa
c
t
elim
in
atio
n
m
eth
o
d
f
ails
wh
e
n
th
e
u
s
ef
u
l
E
E
G
s
ig
n
al
a
n
d
th
e
E
OG
ar
tifa
ct
o
v
er
lap
s
o
r
lies
i
n
th
e
s
am
e
f
r
eq
u
e
n
cy
b
a
n
d
.
I
n
co
n
s
cio
u
s
o
f
th
at,
a
s
im
p
le
f
ilter
in
g
m
eth
o
d
ca
n
n
o
t
elim
in
ate
o
r
r
em
o
v
e
th
e
E
OG
s
ig
n
al
with
o
u
t
r
em
o
v
in
g
a
p
o
r
tio
n
o
f
E
E
G
[
1
3
]
.
Mo
r
eo
v
e
r
,
ad
ap
ti
v
e
f
ilter
in
g
is
u
s
ef
u
l
f
o
r
th
e
o
n
-
lin
e
r
em
o
v
al
o
f
E
OG,
b
u
t,
E
OG'
s
ar
tifa
cts
elim
in
a
tio
n
m
eth
o
d
s
b
ased
o
n
a
d
ap
tiv
e
f
ilter
in
g
r
eq
u
ir
e
ex
t
r
a
r
ec
o
r
d
in
g
ch
a
n
n
els
wh
ich
in
cr
ea
s
es th
e
co
m
p
le
x
ity
o
f
th
e
r
ec
o
r
d
ed
s
y
s
tem
.
E
OG
s
ig
n
al
cu
r
io
s
ar
e
in
cr
ea
s
in
g
ly
n
o
tewo
r
th
y
wh
ile
g
ath
er
in
g
E
E
G
in
f
o
r
m
atio
n
f
r
o
m
r
ec
o
r
d
in
g
s
y
s
tem
s
.
T
h
ese
an
tiq
u
es
ca
n
s
u
ll
y
th
e
n
atu
r
e
o
f
E
E
G
in
f
o
r
m
atio
n
.
W
h
at'
s
m
o
r
e,
o
n
ac
c
o
u
n
t
o
f
th
e
v
o
lu
m
e
co
n
d
u
ctio
n
im
p
ac
t,
b
o
t
h
v
is
u
a
l
r
elics
an
d
E
E
G
m
o
v
em
e
n
t
s
p
r
ea
d
to
th
e
h
ea
d
s
u
r
f
ac
e
an
d
r
ec
o
r
d
b
y
t
h
e
E
E
G
ter
m
in
als
o
r
elec
tr
o
d
es.
T
h
e
am
p
litu
d
e
o
f
E
OG
is
g
en
er
ally
g
r
ea
ter
th
an
E
E
G
s
ig
n
a
ls
an
d
its
f
r
eq
u
en
cy
is
s
im
ilar
to
th
e
f
r
eq
u
en
cy
o
f
E
E
G
s
ig
n
als.
T
h
u
s
,
th
is
ty
p
e
o
f
ar
tifa
ct
(
E
OG)
will
d
es
tr
o
y
an
d
d
is
to
r
ted
th
e
v
alu
ab
le
r
ec
o
r
d
e
d
E
E
G
s
ig
n
als.
T
h
e
d
is
to
r
ted
E
E
G
s
ig
n
al
will
d
o
n
o
t
h
av
e
a
n
y
u
s
ef
u
l
u
s
e,
it
is
a
waste
o
f
tim
e
an
d
ef
f
o
r
t.
Va
r
io
u
s
s
ig
n
p
r
ep
r
o
ce
s
s
in
g
te
ch
n
iq
u
es
to
elim
in
ate
o
r
r
em
o
v
e
e
y
e
-
b
lin
k
(
E
OG)
ar
tifa
ct
h
av
e
b
ee
n
p
r
o
p
o
s
ed
.
T
h
e
co
m
m
o
n
p
r
o
p
o
s
ed
tech
n
iq
u
e
f
o
r
d
is
p
en
s
in
g
with
a
n
tiq
u
es
th
at
ar
e
p
r
o
d
u
ce
d
b
y
ey
e
d
ev
elo
p
m
e
n
ts
u
s
in
g
C
C
A
an
d
f
ilter
s
.
Ho
wev
er
,
u
s
in
g
d
e
co
m
p
o
s
itio
n
m
et
h
o
d
s
co
m
b
i
n
ed
with
C
C
A
o
r
f
ilter
in
g
clea
n
in
g
tech
n
iq
u
e
i
s
v
er
y
r
ar
e
.
T
h
is
p
a
p
er
in
tr
o
d
u
ce
s
two
m
eth
o
d
s
f
o
r
th
e
elim
in
atio
n
o
f
e
y
e
ar
tifa
cts,
wh
ich
ar
e
b
ased
o
n
th
e
co
m
b
i
n
atio
n
o
f
DW
T
an
d
em
p
ir
ical
m
o
d
e
d
ec
o
m
p
o
s
itio
n
(
E
MD
)
ap
p
r
o
ac
h
es a
n
d
b
y
u
s
in
g
C
C
A
tech
n
iq
u
e
o
f
H.
P.F
.
f
o
r
alim
e
n
tatio
n
o
f
e
y
e
ar
tifa
cts.
2.
M
E
T
H
O
DS
2
.
1
.
Dis
cr
et
e
wa
v
ele
t
t
ra
ns
f
o
rm
(
DWT
)
T
h
e
wav
elet
tr
an
s
f
o
r
m
(
W
T
)
is
a
m
ath
em
atica
l
to
o
l
a
b
le
to
d
ec
o
m
p
o
s
itio
n
a
s
ig
n
a
l
in
to
its
co
m
p
o
n
en
t scale
s
(
f
r
eq
u
e
n
cies)
.
E
ar
lier
ex
a
m
p
les o
f
th
is
s
u
c
c
ess
ca
n
b
e
f
o
u
n
d
in
t
h
e
E
E
G
s
ig
n
als [
1
4
,
1
5
]
.
2
.
2
.
T
he
em
pirica
l mo
de
deco
m
po
s
it
io
n
(
E
M
D)
T
h
e
E
MD
is
a
v
e
r
s
atile
tim
e
-
s
p
ac
e
ex
am
in
atio
n
s
tr
ateg
y
r
e
aso
n
ab
le
f
o
r
h
an
d
li
n
g
a
r
r
an
g
e
m
en
ts
th
at
ar
e
n
o
n
-
s
tatio
n
ar
y
an
d
n
o
n
-
s
t
r
aig
h
t.
E
MD
p
er
f
o
r
m
s
task
s
th
at
s
eg
m
en
t
an
ar
r
an
g
em
e
n
t
i
n
to
'
m
o
d
es'
(
I
MFs
;
I
n
tr
in
s
ic
Mo
d
e
Fu
n
cti
o
n
s
)
wit
h
o
u
t
leav
in
g
th
e
tim
e
a
r
ea
z
o
n
e.
I
t
ten
d
s
t
o
b
e
c
o
n
tr
asted
wit
h
o
th
er
tim
e
-
s
p
ac
e
ex
am
in
atio
n
s
tr
ateg
ies
lik
e
f
o
u
r
ier
tr
an
s
f
o
r
m
s
an
d
wav
elet
d
eter
io
r
atio
n
.
Similar
to
th
ese
tech
n
iq
u
es,
E
MD
di
d
n
o
t
d
e
p
en
d
o
n
m
ater
ial
s
cien
ce
.
I
n
an
y
ca
s
e,
th
e
m
o
d
es
m
ay
g
iv
e
k
n
o
wled
g
e
in
to
d
if
f
er
e
n
t
s
ig
n
s
co
n
tain
ed
in
s
id
e
th
e
in
f
o
r
m
ati
o
n
[
1
6
-
1
8
]
.
2
.
3
.
Ca
no
nica
l
c
o
rr
ela
t
io
n a
na
ly
s
is
(
CCA)
C
an
o
n
ical
co
r
r
elatio
n
an
al
y
s
is
is
an
ac
ce
p
ted
r
elatio
n
s
h
ip
ex
am
in
atio
n
to
d
is
tin
g
u
is
h
an
d
g
a
u
g
e
th
e
r
elatio
n
s
h
ip
am
o
n
g
two
ar
r
an
g
em
en
ts
o
f
f
ac
to
r
s
.
An
ac
ce
p
ted
r
elatio
n
s
h
ip
is
p
r
o
p
er
in
s
im
ilar
cir
cu
m
s
tan
ce
s
wh
er
e
d
if
f
e
r
en
t
r
elap
s
e
wo
u
ld
b
e
,
y
et
th
er
e
a
r
e
v
ar
iatio
n
s
b
etwe
en
co
r
r
esp
o
n
d
ed
r
esu
lt
f
ac
t
o
r
s
.
Au
th
o
r
itativ
e
co
n
n
ec
tio
n
in
v
esti
g
atio
n
d
ec
id
es
a
lo
t
o
f
s
tan
d
ar
d
v
ar
iatio
n
s
,
s
y
m
m
etr
ic
al
d
ir
ec
t
m
ix
es
o
f
th
e
f
ac
to
r
s
in
s
id
e
ea
ch
s
et
th
at
b
est cla
r
if
y
th
e
f
lu
ct
u
atio
n
b
o
t
h
in
s
id
e
an
d
b
etwe
en
s
ets [
1
9
-
2
1
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
1
8
,
No
.
5
,
Octo
b
e
r
2
0
2
0
:
258
0
-
258
6
2582
3.
W
O
RK
AND
M
E
T
H
O
DO
L
O
G
Y
3.
1
.
C
o
llect
ing
E
E
G
da
t
a
I
n
th
is
wo
r
k
we
c
o
llected
(
d
o
wn
lo
ad
ed
)
s
ig
n
al
o
f
E
E
G
d
ata
f
r
o
m
a
r
ec
o
m
m
e
n
d
ed
well
k
n
o
w
n
b
io
m
ed
ical
web
s
ite
(
www.
p
h
y
s
io
n
et.
o
r
g
)
,
with
d
etails:
s
lee
p
in
g
E
E
G
d
ata
with
e
y
e
ar
tifa
ct:
with
(
1
0
-
s
ec
o
n
d
d
u
r
atio
n
,
µV
am
p
litu
d
e,
s
am
p
l
in
g
f
r
e
q
u
en
c
y
1
0
0
s
am
p
le/s
ec
o
n
d
an
d
FP
z
-
C
z
elec
tr
o
d
e)
as
its
s
p
ec
if
icatio
n
s
.
3
.
2
.
E
E
G
s
ig
na
l dec
o
m
po
s
it
io
n
T
h
e
co
llected
E
E
G
d
ata
wer
e
d
ec
o
m
p
o
s
ed
in
two
s
tep
s
:
f
ir
s
t
u
s
in
g
th
e
D
W
T
d
ec
o
m
p
o
s
itio
n
tec
h
n
iq
u
e
a
n
d
s
ec
o
n
d
ly
u
s
in
g
E
MD
tech
n
iq
u
e
as sh
o
wn
b
elo
w:
−
Dec
o
m
p
o
s
itio
n
u
s
in
g
DW
T
W
e
ap
p
lied
th
e
DW
T
d
ec
o
m
p
o
s
in
g
tech
n
iq
u
e
o
n
th
e
E
E
G
th
at
we
s
elec
ted
to
h
av
e
th
e
b
asic
b
r
ain
wav
es
(
g
am
m
a
(
δ
)
,
b
eta
(
β)
,
a
lp
h
a
(
α)
,
t
h
eta
(
θ
)
an
d
d
elta
(
σ
)
wa
v
es
)
.
T
h
e
d
elta
(
σ
)
wav
e
h
a
d
th
e
lo
west
b
an
d
f
r
eq
u
e
n
cies
ac
co
r
d
in
g
to
th
e
DW
T
d
ec
o
m
p
o
s
in
g
.
T
h
u
s
,
an
d
s
in
ce
th
e
ey
e
ar
tifa
ct
h
ad
lo
wer
b
an
d
f
r
eq
u
e
n
cies,
we
u
s
ed
th
e
d
elta
(
σ
)
wav
e
in
t
h
e
d
en
o
is
in
g
p
r
o
c
ess
.
−
E
MD
d
ec
o
m
p
o
s
itio
n
W
e
d
ec
o
m
p
o
s
ed
th
e
d
elta
(
σ
)
wav
e
u
s
in
g
th
e
E
MD
te
ch
n
iq
u
e
an
d
g
ettin
g
th
e
I
M
Fs
co
m
p
o
n
e
n
ts
.
T
h
e
ea
r
lier
two
I
MFs
co
m
p
o
n
en
ts
co
n
tain
th
e
h
i
g
h
est
f
r
e
q
u
en
cies
s
in
ce
th
ey
c
h
an
g
e
d
r
a
p
id
ly
(
f
ast
th
an
o
th
er
s
)
an
d
th
e
ey
e
a
r
tifa
cts [
2
2
]
.
3
.
3
.
E
lim
ina
t
io
n o
f
ey
e
a
rt
if
a
ct
s
E
y
e
ar
tifa
cts
elim
in
atio
n
was
d
o
n
e
v
ia
u
s
in
g
two
tec
h
n
iq
u
e
s
(
H.
P.F
.
VS
C
C
A)
to
co
m
p
a
r
e
th
e
two
tech
n
iq
u
es a
n
d
f
in
d
wh
ich
th
e
b
est ar
e.
−
Fil
ter
in
g
u
s
in
g
(
H.
P.F
.
):
T
h
e
ea
r
lier
two
I
MFs
co
m
p
o
n
en
ts
o
f
th
e
Delta
(
σ
)
wav
e
was
f
ilter
ed
b
y
B
u
tter
wo
r
th
FIR
H.
P.F
.
with
th
e
s
p
ec
if
icatio
n
o
f
(
8
o
r
d
e
r
an
d
cu
to
f
f
f
r
e
q
u
en
c
y
o
f
2
Hz)
to
elim
in
ates
th
e
ey
e
a
r
tifa
cts.
W
e
g
o
t
th
e
f
ilter
ed
two
I
MFs co
m
p
o
n
en
ts
.
−
Den
o
is
in
g
u
s
in
g
C
C
A
tech
n
iq
u
es
W
e
h
ad
ap
p
lied
th
e
C
C
A
tech
n
iq
u
es
f
o
r
d
en
o
is
in
g
o
n
th
e
ea
r
lier
two
I
MFs
co
m
p
o
n
en
ts
o
f
th
e
D
elta
(
σ
)
wav
e
th
em
f
r
o
m
ey
e
ar
tifa
cts.
W
e
g
o
t th
e
d
en
o
is
ed
two
I
MFs co
m
p
o
n
e
n
ts
.
3
.
4
.
Rec
o
ns
t
ruct
io
n pro
ce
s
s
W
e
r
ec
o
n
s
tr
u
cted
th
e
d
ec
o
m
p
o
s
ed
E
E
G
s
ig
n
al
in
to
two
s
tag
es a
s
we
d
ec
o
m
p
o
s
ed
it in
two
s
tag
es:
−
R
ec
o
n
s
tr
u
ctio
n
o
f
t
h
e
I
MFs co
m
p
o
n
e
n
ts
W
e
r
ec
o
n
s
tr
u
ct
ed
th
e
Delta
(
σ
)
wav
e
b
y
s
u
m
m
in
g
th
e
elim
in
ated
ey
e
ar
tifa
cts
o
f
I
MFs
co
m
p
o
n
e
n
ts
with
th
e
o
th
er
I
MFs
co
m
p
o
n
e
n
ts
to
g
et
a
clea
n
Delta
(
σ
)
wav
e
f
r
o
m
e
y
e
ar
tifa
cts
wh
ich
ar
e
(
σ
'
an
d
σ
’’)
f
o
r
th
e
two
tech
n
iq
u
es H.
P.F
.
VS CC
A.
−
R
ec
o
n
s
tr
u
ctio
n
clea
n
f
r
o
m
ey
e
ar
t
if
ac
ts
E
E
G
s
ig
n
al
Usi
n
g
DW
T
r
ec
o
n
s
tr
u
ctio
n
t
ec
h
n
iq
u
e,
we
wer
e
r
ec
o
n
s
tr
u
cted
th
e
E
E
G
s
ig
n
al
a
n
d
we
g
o
t
two
clea
n
ed
E
E
G
s
ig
n
al
f
r
o
m
ey
e
a
r
tifa
cts
d
u
e
to
th
e
two
tech
n
iq
u
es
th
at
we
h
ad
u
s
ed
.
T
h
e
p
ap
er
p
r
o
p
o
s
ed
m
eth
o
d
o
l
o
g
y
b
lo
ck
d
iag
r
am
is
s
h
o
wn
in
F
ig
u
r
e
1
.
Fig
u
r
e
1
.
Pro
p
o
s
ed
m
et
h
o
d
o
lo
g
y
b
lo
c
k
d
iag
r
am
3
.
5
.
P
er
f
o
r
m
a
nce
m
e
a
s
urem
ent
s
Fo
r
f
in
d
in
g
th
e
p
er
f
o
r
m
an
ce
o
f
o
u
r
two
tech
n
iq
u
e
in
th
e
e
lim
in
atio
n
o
f
ey
e
ar
tifa
cts
we
m
ea
s
u
r
ed
th
e
r
o
o
t
m
ea
n
s
q
u
ar
e
er
r
o
r
(
R
MSE
)
b
etwe
en
th
e
r
aw
E
E
G
s
ig
n
al
an
d
th
e
clea
n
ed
E
E
G
s
ig
n
al,
also
we
ca
lcu
lated
two
t
y
p
es
o
f
s
ig
n
al
to
n
o
is
e
r
atio
(
SNR
)
f
o
r
b
o
t
h
tech
n
i
q
u
es
th
at
we
h
a
d
u
s
ed
.
T
h
e
eq
u
atio
n
f
o
r
R
MSE
an
d
th
e
two
ty
p
es o
f
SNR
s
h
o
wn
:
=
(
1
)
√
∑
(
′
(
)
−
^
(
)
)
2
=
1
(
1
)
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
A
n
ew elimin
a
tin
g
E
OG
a
r
tifa
cts tec
h
n
iq
u
e
u
s
in
g
c
o
mb
in
ed
…
(
F
a
d
ia
N
o
o
r
i H
u
mma
d
i
A
l
-
N
u
a
imy
)
2583
′
=
10
10
[
∑
′
2
(
)
=
1
∑
(
′
(
)
−
^
(
)
)
2
=
1
]
(
)
(
2)
′′
=
10
10
[
∑
^
2
(
)
=
1
∑
(
′
(
)
−
^
(
)
)
2
=
1
]
(
)
(
3
)
w
h
er
e
S'
(
n
)
=
r
aw
E
E
G
s
ig
n
al,
S^(
n
)
=
r
esu
lted
E
E
G
s
ig
n
al,
an
d
n
=1
,
2
,
3
,
……
.
So
,
th
at
we
ca
n
co
n
f
ig
u
r
e
wh
ich
clea
n
in
g
tech
n
iq
u
e
o
f
th
e
two
tech
n
iq
u
es
th
at
we
h
ad
u
s
ed
i
n
th
is
wo
r
k
h
ad
b
etter
p
er
f
o
r
m
a
n
ce
s
(
i.e
.
g
iv
en
m
o
r
e
clea
n
ly
f
r
o
m
ey
e
ar
tifa
cts E
E
G
s
ig
n
al)
.
4.
RE
SU
L
T
S
Usi
n
g
th
e
clea
n
in
g
tech
n
i
q
u
e
s
s
h
o
wn
in
F
ig
u
r
e
2
an
d
ex
p
lain
ed
in
s
ec
tio
n
3
,
we
g
o
t
two
clea
n
e
d
E
E
G
s
ig
n
al
ac
co
r
d
in
g
to
t
h
e
c
lean
in
g
tech
n
i
q
u
es
(
C
C
A
&
H.
P.F
.
)
.
Fig
u
r
e
2
s
h
o
wn
th
e
c
lean
ed
E
E
G
s
ig
n
als
an
d
th
e
u
n
-
clea
n
ed
E
E
F
s
ig
n
al.
T
h
e
f
r
eq
u
en
cy
s
p
ec
tr
u
m
o
f
th
e
r
aw
E
E
G
s
ig
n
al
an
d
c
lean
ed
E
E
G
s
ig
n
al
b
y
C
C
A
tech
n
iq
u
e
ca
n
b
e
s
h
o
wn
in
F
ig
u
r
e
3
,
also
th
e
f
r
eq
u
en
cy
s
p
ec
tr
u
m
o
f
th
e
r
aw
E
E
G
s
ig
n
al
an
d
clea
n
ed
E
E
G
s
ig
n
al
b
y
H.
P.F
.
tech
n
i
q
u
e
ca
n
b
e
s
h
o
wn
in
F
ig
u
r
e
4
.
(
a)
(
b
)
(
c)
Fig
u
r
e
2
.
E
E
G
s
ig
n
als
;
(
a)
E
E
G
s
ig
n
al
clea
n
ed
b
y
C
C
A
,
(
b
)
E
E
G
s
ig
n
al
clea
n
e
d
b
y
H.
P.F.
,
(
c)
R
aw
E
E
G
s
ig
n
al
0
50
100
150
200
250
300
350
-
1
0
0
-
8
0
-
6
0
-
4
0
-
2
0
0
20
40
60
80
S
A
M
P
L
E
S
A
M
P
L
I
T
U
D
E
(
M
I
C
R
O
)
0
50
100
150
200
250
300
350
-
8
0
-
6
0
-
4
0
-
2
0
0
20
40
60
80
S
A
M
P
L
E
S
A
M
P
L
I
T
U
D
E
(
M
I
C
R
O
)
0
50
100
150
200
250
300
350
-
1
0
0
-
8
0
-
6
0
-
4
0
-
2
0
0
20
40
60
80
100
S
A
M
P
L
E
S
A
M
P
L
I
T
U
D
E
(
M
I
C
R
O
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
1
8
,
No
.
5
,
Octo
b
e
r
2
0
2
0
:
258
0
-
258
6
2584
Fig
u
r
e
3
.
T
h
e
s
p
ec
tr
u
m
o
f
th
e
u
n
-
clea
n
ed
an
d
t
h
e
clea
n
ed
E
E
G
s
ig
n
al
b
y
C
C
A
tech
n
iq
u
e
Fig
u
r
e
4
.
T
h
e
s
p
ec
tr
u
m
o
f
th
e
u
n
-
clea
n
ed
an
d
t
h
e
clea
n
ed
E
E
G
s
ig
n
al
b
y
H.
P.F
.
tech
n
iq
u
e
T
h
e
p
er
f
o
r
m
an
ce
o
f
th
e
two
te
ch
n
iq
u
es
th
at
we
wer
e
u
s
ed
in
th
is
wo
r
k
in
clea
n
in
g
E
E
G
s
i
g
n
al
f
r
o
m
ey
e
ar
tifa
cts wa
s
ca
lcu
lated
in
s
ec
tio
n
3
-
5
to
f
in
d
th
e
(
R
MSE
,
S
'
NR
an
d
S
''
NR
)
f
o
r
b
o
th
tec
h
n
iq
u
es (
C
C
A
an
d
H.
P.F
.
)
an
d
th
e
r
esu
lts
wer
e
s
h
o
wn
in
T
ab
le
1
.
Mo
r
eo
v
e
r
,
m
an
y
o
f
E
OG'
s
ar
tifa
ct
m
eth
o
d
s
wer
e
u
s
ed
to
elim
in
ate
th
e
E
OG
ar
tifa
cts
th
at
co
m
b
in
e
d
i
n
th
e
u
s
ef
u
l
E
E
G
s
ig
n
a
ls
,
T
ab
le
1
lis
ted
s
o
m
e
o
f
th
ese
elim
in
atio
n
m
eth
o
d
s
r
esu
lts
co
m
p
ar
e
d
with
th
e
p
r
o
p
o
s
ed
m
eth
o
d
s
.
T
ab
le
1
.
T
h
e
p
er
f
o
r
m
a
n
ce
m
e
asu
r
em
en
ts
f
o
r
E
OG
ar
tifa
cts
elim
in
atio
n
Te
c
h
n
i
q
u
e
R
M
S
E
S
'N
R
(
d
B
)
S
''N
R
(
d
B
)
D
W
T+
E
M
D
+
C
C
A
3
2
.
1
1
0
0
.
1
8
8
9
1
.
5
2
9
4
D
W
T+
E
M
D
+
H
.
P
.
F
.
2
9
.
9
7
4
0
.
7
7
7
8
1
.
5
0
5
1
D
W
T+
I
C
A
4
.
2
3
5
2
2
2
.
5
4
8
2
2
.
5
8
7
D
W
T+
C
C
A
5
.
2
1
4
8
1
9
.
8
5
4
2
0
.
1
4
8
EM
D
+
I
C
A
1
1
.
8
2
1
1
2
.
3
5
8
1
1
.
2
5
4
EM
D
+
C
C
A
1
2
.
3
8
7
1
1
.
6
4
7
1
1
.
2
5
4
5.
DIS
CU
SS
I
O
N
T
h
e
co
m
m
o
tio
n
ca
n
in
tr
o
d
u
c
e
a
cr
itical
test
in
ex
am
in
atio
n
an
d
elu
cid
atio
n
o
f
E
E
G
in
f
o
r
m
atio
n
,
r
eq
u
ir
in
g
ef
f
ec
tiv
e
s
y
s
tem
s
f
o
r
clam
o
r
a
v
er
s
io
n
a
n
d
e
x
p
u
ls
i
o
n
.
A
lo
t
o
f
clam
o
r
s
ca
n
b
e
d
o
d
g
e
d
b
y
d
ea
lin
g
with
th
e
f
itti
n
g
ac
c
o
u
n
t
co
n
d
itio
n
an
d
ca
u
tio
u
s
ar
r
an
g
in
g
o
f
ex
am
in
atio
n
s
an
d
r
ec
o
r
d
in
g
s
ess
io
n
s
.
Mo
r
eo
v
er
,
v
ar
io
u
s
tech
n
iq
u
es
an
d
ca
lcu
l
atio
n
s
ca
n
b
e
u
tili
ze
d
t
o
d
is
m
is
s
b
o
is
ter
o
u
s
in
f
o
r
m
atio
n
,
e
v
ac
u
ate
co
m
m
o
tio
n
f
lag
an
d
im
p
r
o
v
e
t
h
e
f
lag
to
-
c
lam
o
r
p
r
o
p
o
r
tio
n
o
f
t
h
e
in
f
o
r
m
atio
n
.
T
o
s
u
cc
ess
f
u
lly
p
ick
an
d
u
tili
z
e
s
tr
ateg
ies
f
o
r
m
a
n
ag
in
g
clam
o
r
,
th
eir
p
o
in
ts
o
f
in
ter
est,
a
n
d
p
r
o
v
o
k
es
s
h
o
u
ld
b
e
co
n
s
id
er
e
d
in
c
o
n
n
ec
tio
n
to
th
e
p
r
o
p
er
ties
o
f
th
e
i
n
f
o
r
m
atio
n
an
d
th
e
s
y
s
tem
atic
in
q
u
ir
i
es
b
ein
g
in
q
u
ir
ed
.
T
o
r
esear
c
h
th
e
ex
ec
u
tio
n
o
f
th
e
p
r
o
p
o
s
ed
s
tr
ateg
y
,
we
co
n
tr
asted
th
is
tech
n
iq
u
e
an
d
an
o
th
er
cu
r
r
en
t
ca
lc
u
latio
n
.
T
h
e
b
len
d
o
f
C
C
A
-
SS
A
an
d
H.
P.F.
(
DW
T
-
E
MD
)
was
u
tili
ze
d
in
th
is
c
o
r
r
elatio
n
task
.
T
o
en
co
u
r
ag
e
th
e
v
iab
ilit
y
co
r
r
elatio
n
,
a
s
im
ilar
2
.
5
6
5
.
1
2
7
.
6
8
1
0
.
2
4
1
2
.
8
1
5
.
3
6
1
7
.
9
2
2
0
.
4
8
2
3
.
0
4
2
5
.
6
2000
4000
6000
8000
10000
12000
HZ
A
M
P
L
I
T
U
D
E
(
M
I
C
R
O
)
un-c
l
e
a
ne
d E
E
G
c
l
e
a
ne
d E
E
G
2
.
5
6
5
.
1
2
7
.
6
8
1
0
.
2
4
1
2
.
8
1
5
.
3
6
1
7
.
9
2
2
0
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4
8
2
3
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0
4
2
5
.
6
2
8
.
1
6
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
HZ
A
M
P
L
I
T
U
D
E
(
M
I
C
R
O
)
un-c
l
e
a
ne
d E
E
G
c
l
e
a
ne
d E
E
G
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
A
n
ew elimin
a
tin
g
E
OG
a
r
tifa
cts tec
h
n
iq
u
e
u
s
in
g
c
o
mb
in
ed
…
(
F
a
d
ia
N
o
o
r
i H
u
mma
d
i
A
l
-
N
u
a
imy
)
2585
E
E
G
d
ataset
was
co
n
n
ec
te
d
to
th
is
s
tr
ate
g
y
.
I
n
th
e
f
i
r
s
t
p
lace
,
b
y
ap
p
ly
in
g
C
C
A
-
SS
A,
th
e
cr
u
d
e
E
E
G
in
f
o
r
m
atio
n
was
s
ep
ar
ated
in
to
th
e
ce
r
eb
r
al
ac
tio
n
a
n
d
th
e
v
er
y
n
o
n
-
s
tatio
n
ar
y
E
OG
p
a
r
ts
.
Seco
n
d
,
th
e
E
OG
was r
ec
r
ea
ted
f
r
o
m
th
e
d
is
tin
g
u
is
h
ed
E
OG
p
ar
ts
b
y
t
h
e
E
M
D
ca
lcu
latio
n
.
W
e
h
ad
u
s
ed
in
t
h
is
wo
r
k
two
d
ec
o
m
p
o
s
itio
n
m
eth
o
d
s
to
lo
o
k
in
g
i
n
s
id
e
th
e
u
n
-
clea
n
ed
E
E
G
s
ig
n
al
d
ee
p
ly
an
d
ca
n
f
in
d
th
e
f
r
e
q
u
en
cies
co
m
p
o
n
en
ts
with
r
an
g
e
(
<
4
Hz)
,
th
en
we
d
e
n
o
is
ed
th
is
b
an
d
o
f
f
r
eq
u
e
n
cies
b
y
C
C
A
tech
n
iq
u
e,
to
elim
in
atin
g
e
y
e
ar
tifa
cts an
d
n
o
t
h
ar
m
o
r
e
f
f
ec
t
t
h
e
o
th
er
b
an
d
s
o
f
th
e
E
E
G
s
ig
n
al.
Als
o
,
we
h
ad
u
s
ed
th
e
H.
P.F
.
tech
n
iq
u
e
f
o
r
f
ilter
in
g
t
h
e
(
<
4
Hz)
f
r
e
q
u
en
cies
b
a
n
d
o
f
th
e
d
ec
o
m
p
o
s
ed
(
b
y
th
e
s
am
e
d
ec
o
m
p
o
s
itio
n
m
eth
o
d
s
ab
o
v
e)
E
E
G
s
ig
n
a
l
f
o
r
elim
in
atin
g
ey
e
ar
tifa
ct
s
.
W
e
d
id
th
is
in
th
e
o
r
d
er
we
co
u
ld
co
m
p
ar
e
th
e
two
m
eth
o
d
o
lo
g
ies
an
d
f
i
n
d
th
e
b
est
m
eth
o
d
f
o
r
elim
i
n
atin
g
ey
e
ar
tifa
cts
b
etwe
en
th
em
th
at
we
u
s
ed
.
T
h
e
elim
in
atio
n
o
f
th
e
f
r
e
q
u
en
cies
co
m
p
o
n
e
n
ts
with
r
an
g
e
(
<
4
Hz)
in
th
e
u
n
-
clea
n
e
d
E
E
G
s
ig
n
al,
c
an
b
e
s
ee
n
clea
r
ly
f
o
r
th
e
C
C
A
tech
n
iq
u
e
in
F
ig
u
r
e
3
an
d
H.
P.F
.
tech
n
iq
u
e
in
F
ig
u
r
e
4
r
esp
ec
tiv
ely
.
T
h
u
s
,
l
ed
to
th
e
clea
n
ed
E
E
G
s
ig
n
al
wh
ich
was
s
h
o
wn
in
F
ig
u
r
e
2
(
a)
f
o
r
th
e
C
C
A
tech
n
iq
u
e
an
d
F
ig
u
r
e
2
(b
)
f
o
r
th
e
H.
P.F
.
tech
n
iq
u
e
co
m
p
ar
ed
with
th
e
u
n
-
clea
n
ed
E
E
G
s
ig
n
al
s
h
o
wn
in
F
ig
u
r
e
2
(
c)
.
Fu
r
th
er
m
o
r
e,
t
h
e
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
em
en
t
f
o
r
clea
n
in
g
E
E
G
s
ig
n
als
f
r
o
m
ey
e
ar
tifa
cts,
w
h
ich
wer
e
s
h
o
wn
in
T
a
b
le
1
g
i
v
en
u
s
th
e
R
MSE
,
S
'
NR
an
d
S
''
NR
f
o
r
b
o
th
u
s
ed
tech
n
iq
u
es in
th
is
wo
r
k
[
2
3
-
2
5
]
.
6.
CO
NCLU
SI
O
NS
A
s
u
cc
ess
f
u
l
m
eth
o
d
o
lo
g
y
is
p
r
o
p
o
s
ed
in
th
is
p
a
p
er
t
o
a
d
d
r
ess
th
e
is
s
u
e
o
f
v
is
u
al
a
n
cien
t
r
ar
ity
ex
p
u
ls
io
n
f
r
o
m
cr
u
d
e
E
E
G
r
ec
o
r
d
in
g
.
T
o
ex
tr
icate
ar
tifa
ctu
al
s
o
u
r
ce
s
f
r
o
m
th
e
cr
u
d
e
E
E
G
r
ec
o
r
d
in
g
,
we
h
av
e
u
tili
ze
d
th
e
s
tatio
n
ar
y
s
u
b
s
p
ac
e
in
v
esti
g
atio
n
ca
lcu
latio
n
,
wh
ich
ca
n
m
o
v
e
r
elics
in
f
ewe
r
s
eg
m
en
ts
th
an
t
h
e
ag
en
t
d
az
zle
s
o
u
r
ce
d
etac
h
m
en
t
s
tr
ateg
ies.
At
th
at
p
o
in
t
th
e
ar
tifa
ctu
al
p
ar
ts
ar
e
an
ticip
ated
b
ac
k
to
b
e
s
u
b
tr
ac
ted
f
r
o
m
E
E
G
s
ig
n
als,
cr
ea
tin
g
th
e
s
p
o
tles
s
E
E
G
in
f
o
r
m
atio
n
in
ev
itab
ly
.
T
h
e
te
s
t
r
esu
lts
o
n
b
o
th
th
e
m
is
lead
in
g
ly
tain
ted
E
E
G
in
f
o
r
m
atio
n
a
n
d
g
en
u
in
e
E
E
G
in
f
o
r
m
atio
n
h
a
v
e
ex
h
ib
ited
th
e
v
iab
ilit
y
o
f
th
e
p
r
o
p
o
s
ed
tech
n
iq
u
e,
s
p
ec
if
ically
f
o
r
th
e
s
itu
atio
n
s
wh
er
e
s
et
th
e
n
u
m
b
er
o
f
an
o
d
e
s
ar
e
u
tili
ze
d
f
o
r
th
e
ch
r
o
n
icle,
j
u
s
t
as
wh
en
th
e
an
tiq
u
e
d
e
b
ased
f
lag
is
e
x
ce
p
tio
n
ally
n
o
n
-
s
tatio
n
ar
y
a
n
d
th
e
f
u
n
d
am
e
n
tal
s
o
u
r
ce
s
ca
n
n
o
t
b
e
th
o
u
g
h
t t
o
b
e
f
r
ee
o
r
u
n
co
r
r
elate
d
.
W
e
co
u
ld
h
av
e
co
n
clu
d
e
d
f
r
o
m
o
u
r
r
esu
lts
th
at
u
s
in
g
th
e
t
wo
d
ec
o
m
p
o
s
in
g
m
et
h
o
d
s
th
at
we
h
ad
u
s
ed
g
av
e
u
s
a
g
o
o
d
v
iew
in
s
id
e
(
lo
o
k
d
ee
p
ly
)
th
e
u
n
-
clea
n
ed
o
r
r
aw
E
E
G
s
ig
n
al
to
f
in
d
th
e
lo
we
r
f
r
eq
u
e
n
cies
co
m
p
o
n
en
ts
o
f
th
e
u
n
-
clea
n
ed
E
E
G
s
ig
n
al
to
clea
n
it.
T
h
e
r
esu
lts
h
av
e
s
h
o
w
n
th
at
th
e
co
m
p
en
s
atio
n
o
f
th
e
two
d
ec
o
m
p
o
s
in
g
m
eth
o
d
s
an
d
t
h
e
C
C
A
tech
n
iq
u
e
h
ad
th
e
b
est
p
er
f
o
r
m
an
ce
in
clea
n
in
g
th
e
u
n
-
clea
n
e
d
E
E
G
s
ig
n
al
f
r
o
m
ar
tifa
cts
with
(
S
''
N
R
=
1
.
5
2
9
4
an
d
R
MSE
=3
2
.
1
1
0
1
)
is
co
m
p
ar
ed
with
th
e
o
th
e
r
way
th
at
we
u
s
ed
h
er
e
.
Fig
u
r
es
an
d
r
esu
lts
th
at
we
h
ad
f
r
o
m
th
is
wo
r
k
s
h
o
w
th
at
th
e
p
r
o
p
o
s
ed
m
eth
o
d
(
th
e
two
d
ec
o
m
p
o
s
in
g
m
eth
o
d
s
an
d
t
h
e
C
C
A
tech
n
iq
u
e)
g
i
v
en
a
g
o
o
d
clea
n
e
d
f
r
o
m
ey
e
ar
tifa
ct
s
E
E
G
s
ig
n
al.
RE
F
E
R
E
NC
E
S
[1
]
V.
Bo
n
o
,
S
.
Da
s,
W.
Ja
m
a
l,
a
n
d
K.
M
a
h
a
ra
tn
a
,
"
Hy
b
rid
wa
v
e
let
a
n
d
EM
D/ICA
a
p
p
ro
a
c
h
f
o
r
a
rti
fa
c
t
su
p
p
re
ss
io
n
i
n
p
e
rv
a
siv
e
EE
G
,
"
J
o
u
rn
a
l
o
f
Ne
u
r
o
sc
ien
c
e
M
e
th
o
ds
,
v
o
l
.
2
6
7
,
p
p
.
8
9
-
1
0
7
,
2
0
1
6
.
[2
]
M
.
S
h
a
h
b
a
k
h
ti
,
M
.
Ba
v
i,
a
n
d
M
.
Eslam
iza
d
e
h
,
"
E
li
m
in
a
ti
o
n
o
f
Bli
n
k
fro
m
EE
G
By
A
d
a
p
ti
v
e
F
il
terin
g
with
o
u
t
Us
in
g
Ar
ti
fa
c
t
Re
fe
re
n
c
e
,
"
2
0
1
3
4
t
h
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
In
tell
ig
e
n
t
S
y
ste
ms
,
M
o
d
e
ll
i
n
g
a
n
d
S
im
u
la
ti
o
n
,
p
p
.
1
9
0
-
194
,
2
0
1
3
.
[3
]
M
.
A.
Ja
to
i,
N.
Ka
m
e
l,
A.
S
.
M
a
li
k
,
I.
F
a
y
e
,
a
n
d
T
.
Be
g
u
m
,
"
A
su
rv
e
y
o
f
m
e
th
o
d
s
u
se
d
f
o
r
s
o
u
rc
e
lo
c
a
li
z
a
ti
o
n
u
sin
g
EE
G
sig
n
a
ls,"
Bi
o
me
d
ica
l
S
ig
n
a
l
Pr
o
c
e
ss
in
g
a
n
d
Co
n
tro
l
,
v
o
l
.
1
1
,
p
p
.
4
2
-
5
2
,
2
0
1
4
.
[4
]
G
.
J.
F
e
ist,
“
T
h
e
p
s
y
c
h
o
lo
g
y
o
f
sc
ien
c
e
a
n
d
t
h
e
o
rig
i
n
s
o
f
th
e
sc
ien
ti
fic
m
in
d
:
th
e
p
sy
c
h
o
l
o
g
y
o
f
sc
ien
c
e
,
”
Ya
le
Un
iv
e
rsity
P
re
ss
,
2
0
0
8
.
[5
]
M
.
T
.
A
l
-
m
a
q
t
a
r
i
,
Z
.
Ta
h
a
,
a
n
d
M
.
M
o
g
h
a
v
v
e
m
i
,
"
S
t
e
a
d
y
s
t
a
te
-
V
E
P
b
a
s
e
d
B
C
I
f
o
r
c
o
n
t
r
o
l
g
r
i
p
p
i
n
g
o
f
a
r
o
b
o
t
i
c
h
a
n
d
,
"
2
0
0
9
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
f
o
r
T
e
c
h
n
i
c
a
l
P
o
s
t
g
r
a
d
u
a
t
e
s
(
T
E
C
H
P
O
S
)
,
p
p
.
1
-
3
,
2
0
0
9
.
[6
]
I.
A.
Ib
ra
h
im,
F
.
N.
AlNu
a
imy
,
a
n
d
C.
E.
Ah
m
e
d
,
"
De
sig
n
An
d
Im
p
lem
e
n
tatio
n
Of
A
Bi
o
m
e
d
ica
l
S
ig
n
a
ls
G
e
n
e
r
a
to
r
Ba
se
d
On
M
icro
c
o
n
t
ro
ll
e
r,
"
J
o
u
r
n
a
l
o
f
E
n
g
i
n
e
e
rin
g
a
n
d
S
u
st
a
i
n
a
b
le
De
v
e
lo
p
me
n
t
,
v
o
l.
1
7
,
n
o
.
6
,
p
p
.
1
8
6
-
2
0
0
,
2
0
1
3
.
[7
]
K.
T.
S
we
e
n
e
y
,
S
.
F
.
M
c
Lo
o
n
e
,
a
n
d
T.
E.
Ward
,
"
Th
e
u
se
o
f
e
n
se
m
b
le
e
m
p
iri
c
a
l
m
o
d
e
d
e
c
o
m
p
o
siti
o
n
wi
t
h
c
a
n
o
n
ica
l
c
o
rre
latio
n
a
n
a
l
y
sis
a
s
a
n
o
v
e
l
a
rti
fa
c
t
re
m
o
v
a
l
t
e
c
h
n
iq
u
e
,
"
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
B
io
me
d
ica
l
En
g
i
n
e
e
rin
g
,
v
o
l.
6
0
,
p
p
.
9
7
-
1
0
5
,
2
0
1
3
.
[8
]
J.
F
.
G
a
o
,
Y.
Ya
n
g
,
P
.
Li
n
,
P
.
W
a
n
g
,
a
n
d
C.
X
.
Zh
e
n
g
,
"
Au
t
o
m
a
ti
c
re
m
o
v
a
l
o
f
e
y
e
-
m
o
v
e
m
e
n
t
a
n
d
b
li
n
k
a
rti
fa
c
ts
fro
m
EE
G
sig
n
a
ls,"
Bra
i
n
T
o
p
o
g
r
a
p
h
y
,
v
o
l.
2
3
,
p
p
.
1
0
5
-
1
1
4
,
2
0
1
0
.
[9
]
G
.
G
e
e
th
a
a
n
d
S
.
G
e
e
th
a
lak
sh
m
i,
"
S
c
ru
t
in
izi
n
g
d
iffere
n
t
tec
h
n
iq
u
e
s
fo
r
a
rti
fa
c
t
re
m
o
v
a
l
fro
m
EE
G
sig
n
a
ls,"
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
n
g
in
e
e
rin
g
S
c
ien
c
e
a
n
d
T
e
c
h
n
o
lo
g
y
(IJ
E
S
T
)
,
v
o
l
.
3
,
n
o
.
2
,
p
p
.
1
1
6
7
-
1
1
7
2
,
2
0
1
1
.
[1
0
]
V.
Krish
n
a
v
e
n
i,
S
.
Ja
y
a
ra
m
a
n
,
S
.
Ara
v
in
d
,
V.
Ha
rih
a
ra
su
d
h
a
n
,
a
n
d
K
.
Ra
m
a
d
o
ss
,
"
Au
t
o
m
a
ti
c
id
e
n
ti
fica
ti
o
n
a
n
d
Re
m
o
v
a
l
o
f
o
c
u
lar
a
rt
ifac
ts
fro
m
EE
G
u
sin
g
Wav
e
let
t
ra
n
sfo
r
m
,
"
M
e
a
su
re
me
n
t
S
c
ien
c
e
Rev
ie
w
,
v
o
l.
6
,
n
o
.
4
,
p
p
.
4
5
-
5
7
,
2
0
0
6
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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2586
[1
1
]
J.
G
a
o
,
H.
S
u
lt
a
n
,
J.
Hu
,
a
n
d
W.
-
W.
T
u
n
g
,
"
De
n
o
isi
n
g
n
o
n
li
n
e
a
r
ti
m
e
se
ries
b
y
a
d
a
p
ti
v
e
fi
lt
e
rin
g
a
n
d
wa
v
e
let
sh
rin
k
a
g
e
:
a
c
o
m
p
a
riso
n
,
"
IEE
E
S
ig
n
a
l
Pr
o
c
e
ss
in
g
L
e
tt
e
rs
,
v
o
l
.
1
7
,
n
o
.
3
,
p
p
.
2
3
7
-
2
4
0
,
2
0
1
0
.
[1
2
]
E.
Kro
u
p
i,
A
.
Ya
z
d
a
n
i,
J.
-
M
.
Ve
sin
,
a
n
d
T
.
Eb
ra
h
imi,
"
Oc
u
lar
a
rti
fa
c
t
re
m
o
v
a
l
fro
m
EE
G
:
a
c
o
m
p
a
riso
n
o
f
su
b
sp
a
c
e
p
r
o
jec
ti
o
n
a
n
d
a
d
a
p
ti
v
e
fil
teri
n
g
m
e
th
o
d
s,"
2
0
1
1
1
9
th
Eu
r
o
p
e
a
n
S
ig
n
a
l
Pr
o
c
e
ss
in
g
C
o
n
fer
e
n
c
e
,
p
p
.
1
3
9
5
-
1
3
9
9
,
2
0
1
1
.
[1
3
]
A.
Ro
m
a
n
o
v
,
E.
S
h
a
r
o
v
a
,
O.
Ku
z
n
e
tso
v
a
,
L.
Ok
n
in
a
,
P
.
Vo
l
y
n
sk
ii
,
a
n
d
G
.
S
h
c
h
e
k
u
ti
e
v
,
"
P
o
ten
ti
a
l
o
f
a
wa
v
e
let
sy
n
c
h
r
o
n
iza
ti
o
n
m
e
th
o
d
f
o
r
a
ss
e
ss
in
g
t
h
e
l
o
n
g
-
late
n
c
y
c
o
m
p
o
n
e
n
ts
o
f
a
u
d
it
o
r
y
e
v
o
k
e
d
p
o
ten
ti
a
ls
in
h
e
a
lt
h
y
h
u
m
a
n
s,"
Ne
u
ro
sc
ien
c
e
a
n
d
Beh
a
v
io
ra
l
P
h
y
sio
l
o
g
y
,
v
o
l
.
4
2
,
p
p
.
5
8
8
-
5
9
3
,
2
0
1
2
.
[1
4
]
G
.
Ka
ise
r,
“
A fri
e
n
d
ly
g
u
id
e
t
o
w
a
v
e
lets
,”
S
p
ri
n
g
e
r S
c
ien
c
e
&
B
u
sin
e
ss
M
e
d
ia
,
2
0
1
0
.
[1
5
]
C.
He
m
a
n
th
,
A.
S
.
RAM,
N.
Krish
n
a
,
a
n
d
P
.
Bra
h
m
a
n
a
n
d
a
m
,
"
No
n
Li
n
e
a
r
a
n
d
N
o
n
-
S
tatio
n
a
ry
Da
ta
An
a
ly
sis
u
sin
g
Hilb
e
rt
-
Hu
a
n
g
Tran
sf
o
rm
,
"
J
o
u
rn
a
l
o
f
T
h
e
o
re
ti
c
a
l
a
n
d
A
p
p
li
e
d
In
f
o
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
2
9
,
n
o
.
2
,
p
p
.
7
4
-
84
,
2
0
1
1
.
[1
6
]
M
.
Na
ji
,
M
.
F
iro
o
z
a
b
a
d
i,
a
n
d
S
.
Ka
h
rizi,
"
T
h
e
A
p
p
li
c
a
ti
o
n
o
f
E
m
p
iri
c
a
l
M
o
d
e
De
c
o
m
p
o
siti
o
n
i
n
El
imi
n
a
ti
o
n
o
f
ECG
c
o
n
tam
in
a
ti
o
n
fr
o
m
EM
G
sig
n
a
ls,"
2
0
1
1
1
8
t
h
Ir
a
n
i
a
n
C
o
n
fer
e
n
c
e
o
f
Bi
o
me
d
ica
l
E
n
g
i
n
e
e
rin
g
(ICB
M
E)
,
p
p
.
7
7
-
80
,
2
0
1
1
.
[1
7
]
M
.
M
a
n
j
u
la,
S
.
M
ish
ra
,
a
n
d
A.
S
a
rm
a
,
"
Emp
iri
c
a
l
m
o
d
e
d
e
c
o
m
p
o
siti
o
n
wit
h
Hil
b
e
rt
tran
sfo
rm
fo
r
c
las
sifica
ti
o
n
o
f
v
o
lt
a
g
e
sa
g
c
a
u
se
s
u
sin
g
p
r
o
b
a
b
il
isti
c
n
e
u
ra
l
n
e
two
r
k
,
"
I
n
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
Po
we
r
&
En
e
rg
y
S
y
ste
ms
,
v
o
l.
4
4
,
n
o
.
1
,
p
p
.
5
9
7
-
6
0
3
,
2
0
1
3
.
[1
8
]
C.
Ku
fs,
“
S
tats
with
c
a
ts:
Th
e
d
o
m
e
stica
ted
g
u
id
e
to
sta
ti
stics
,
m
o
d
e
ls,
g
ra
p
h
s
,
a
n
d
o
th
e
r
b
re
e
d
s
o
f
d
a
ta
a
n
a
ly
sis
,”
W
h
e
a
tma
rk
In
c
.
,
2
0
1
1
.
[1
9
]
F
.
R
o
e
m
e
r,
G
.
De
l
G
a
ld
o
,
a
n
d
M
.
Ha
a
rd
t,
"
Te
n
so
r
-
b
a
se
d
a
lg
o
rit
h
m
s
f
o
r
lea
rn
in
g
m
u
lt
id
ime
n
sio
n
a
l
se
p
a
ra
b
le
d
ictio
n
a
ries
,
"
2
0
1
4
IEE
E
In
ter
n
a
t
i
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
Aco
u
st
ics
,
S
p
e
e
c
h
a
n
d
S
i
g
n
a
l
Pr
o
c
e
ss
in
g
(IC
AS
S
P)
,
p
p
.
3
9
6
3
-
3
9
6
7
,
2
0
1
4
.
[
2
0
]
X
.
C
h
e
n
,
C
.
H
e
,
a
n
d
H
.
P
e
n
g
,
"
R
e
m
o
v
a
l
o
f
m
u
s
c
l
e
a
r
t
i
f
a
c
t
s
f
r
o
m
s
i
n
g
l
e
-
c
h
a
n
n
e
l
E
E
G
b
a
s
e
d
o
n
e
n
s
e
m
b
l
e
e
m
p
i
r
i
c
a
l
m
o
d
e
d
e
c
o
m
p
o
s
i
t
i
o
n
a
n
d
m
u
l
t
i
s
e
t
c
a
n
o
n
i
c
a
l
c
o
r
r
e
l
a
t
i
o
n
a
n
a
l
y
s
i
s
,
"
J
o
u
r
n
a
l
o
f
A
p
p
l
i
e
d
M
a
t
h
e
m
a
t
i
c
s
,
v
o
l
.
2
0
1
4
,
2
0
1
4
.
[2
1
]
E.
No
h
a
n
d
V.
R.
De
S
a
,
"
Ca
n
o
n
ica
l
c
o
rre
latio
n
a
p
p
ro
a
c
h
t
o
c
o
m
m
o
n
sp
a
ti
a
l
p
a
tt
e
r
n
s,"
2
0
1
3
6
th
In
ter
n
a
ti
o
n
a
l
IEE
E/
EM
BS
C
o
n
fer
e
n
c
e
o
n
Ne
u
r
a
l
E
n
g
i
n
e
e
rin
g
(N
ER
)
,
p
p
.
6
6
9
-
6
7
2
,
2
0
1
3
.
[2
2
]
I.
A.
Ib
ra
h
im,
H.
-
N.
T
in
g
,
a
n
d
M
.
M
o
g
h
a
v
v
e
m
i,
"
T
h
e
e
ffe
c
ts
o
f
a
u
d
io
stim
u
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