I
nte
rna
t
io
na
l J
o
urna
l o
f
E
lect
rica
l a
nd
Co
m
p
ute
r
E
ng
in
ee
ring
(
I
J
E
CE
)
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t
201
8
,
p
p
.
2
4
9
4
~
2
5
0
2
I
SS
N:
2088
-
8708
,
DOI
: 1
0
.
1
1
5
9
1
/
i
j
ec
e
.
v
8
i
4
.
p
p
2
4
9
4
-
2502
2494
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ia
e
s
co
r
e
.
co
m/
jo
u
r
n
a
ls
/in
d
ex
.
p
h
p
/
I
JE
C
E
K
-
N
N Clas
sifi
ca
ti
o
n of Bra
in Do
m
i
na
nce
K
ha
irul A
m
riza
l A
b
u Na
w
a
s
,
M
a
hfuza
h
M
us
t
a
f
a
,
Ro
s
di
y
a
na
Sa
m
a
d
,
Dw
i P
ebria
nti,
No
r
Rul H
a
s
m
a
A
bd
ul
la
h
F
a
c
u
lt
y
o
f
El
e
c
tri
c
a
l
&
El
e
c
tro
n
ics
En
g
in
e
e
rin
g
,
Un
iv
e
rsiti
M
a
lay
sia
P
a
h
a
n
g
,
M
a
lay
sia
Art
icle
I
nfo
AB
ST
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Mar
9
,
2
0
1
8
R
ev
i
s
ed
J
u
n
1
2
,
2
0
1
8
A
cc
ep
ted
J
u
n
1
9
,
2
0
1
8
T
h
e
b
ra
in
d
o
m
in
a
n
c
e
is
re
f
e
rre
d
t
o
rig
h
t
b
ra
i
n
a
n
d
lef
t
b
ra
i
n
.
T
h
e
b
ra
in
d
o
m
in
a
n
c
e
c
a
n
b
e
o
b
se
rv
e
d
w
it
h
a
n
El
e
c
tro
e
n
c
e
p
h
a
lo
g
ra
m
(
EE
G
)
sig
n
a
l
to
id
e
n
ti
f
y
d
iffere
n
t
t
y
p
e
s
o
f
e
lec
tri
c
a
l
p
a
tt
e
rn
in
th
e
b
ra
in
a
n
d
w
il
l
f
o
r
m
th
e
f
o
u
n
d
a
ti
o
n
o
f
o
n
e
‟s
p
e
rso
n
a
li
ty
.
T
h
e
o
b
jec
ti
v
e
o
f
th
is
p
ro
jec
t
is
to
a
n
a
ly
z
e
b
ra
in
d
o
m
in
a
n
c
e
b
y
u
sin
g
W
a
v
e
l
e
t
a
n
a
ly
sis.
T
h
e
W
a
v
e
let
a
n
a
l
y
sis
is
d
o
n
e
i
n
2
-
D
Ga
b
o
r
W
a
v
e
let
a
n
d
th
e
re
su
lt
o
f
2
-
D
Ga
b
o
r
W
a
v
e
let
is
v
a
li
d
a
ted
w
it
h
an
e
sta
b
li
sh
b
ra
in
d
o
m
in
a
n
c
e
q
u
e
stio
n
n
a
ire.
T
we
n
ty
-
one
sa
m
p
les
f
ro
m
Un
iv
e
rsit
y
M
a
la
y
si
a
P
a
h
a
n
g
(U
M
P
)
stu
d
e
n
t
a
re
re
q
u
ire
d
to
a
n
sw
e
r
th
e
e
sta
b
li
sh
b
ra
i
n
d
o
m
in
a
n
c
e
q
u
e
stio
n
n
a
ire
h
a
s
b
e
e
n
c
o
ll
e
c
ted
in
th
is
e
x
p
e
ri
m
e
n
t.
T
h
e
n
,
b
ra
in
w
a
v
e
si
g
n
a
l
w
il
l
re
c
o
rd
u
sin
g
Em
o
ti
v
d
e
v
ice
.
T
h
e
t
h
re
sh
o
l
d
v
a
lu
e
is
u
se
d
to
re
m
o
v
e
th
e
a
rti
f
a
c
t
a
n
d
n
o
ise
f
ro
m
d
a
ta
c
o
ll
e
c
ted
to
a
c
q
u
ire
a
sm
o
o
th
e
r
sig
n
a
l.
Ne
x
t,
th
e
Ba
n
d
-
p
a
ss
f
il
ter
is
a
p
p
li
e
d
t
o
th
e
sig
n
a
l
to
e
x
trac
t
th
e
su
b
-
b
a
n
d
f
re
q
u
e
n
c
y
c
o
m
p
o
n
e
n
ts
f
ro
m
De
lt
a
,
T
h
e
ta,
A
lp
h
a
,
a
n
d
Be
ta.
Af
ter
th
a
t,
it
w
il
l
e
x
trac
t
th
e
e
n
e
rg
y
o
f
th
e
sig
n
a
l
f
ro
m
i
m
a
g
e
f
e
a
tu
re
e
x
trac
ti
o
n
p
ro
c
e
ss
.
Ne
x
t
th
e
f
e
a
tu
re
s
w
e
re
c
las
sif
i
e
d
b
y
u
sin
g
K
-
Ne
a
re
st
Ne
ig
h
b
o
r
(K
-
NN
)
i
n
tw
o
ra
ti
o
s
w
h
ich
7
0
:
3
0
a
n
d
8
0
:2
0
t
h
a
t
a
re
t
ra
in
in
g
se
t
a
n
d
tes
ti
n
g
se
t
(train
i
n
g
:
tes
ti
n
g
).
T
h
e
ra
ti
o
o
f
7
0
:3
0
g
a
v
e
th
e
h
ig
h
e
st
p
e
rc
e
n
tag
e
o
f
8
3
%
a
c
c
u
ra
c
y
w
h
il
e
a
ra
ti
o
o
f
8
0
:2
0
g
a
v
e
1
0
0
%
a
c
c
u
ra
c
y
.
T
h
e
re
su
lt
sh
o
w
s
th
a
t
2
-
D
Ga
b
o
r
W
a
v
e
let
w
a
s
a
b
le
to
c
las
si
fy
b
ra
in
d
o
m
in
a
n
c
e
w
it
h
a
c
c
u
ra
c
y
8
3
%
to
1
0
0
%
.
K
ey
w
o
r
d
:
B
r
ain
d
o
m
i
n
a
n
ce
K
-
NN
W
av
elet
Co
p
y
rig
h
t
©
2
0
1
8
In
stit
u
te o
f
A
d
v
a
n
c
e
d
E
n
g
i
n
e
e
rin
g
a
n
d
S
c
ien
c
e
.
Al
l
rig
h
ts
re
se
rv
e
d
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Ma
h
f
u
za
h
Mu
s
ta
f
a
,
Facu
lt
y
o
f
E
lectr
ical
&
E
lectr
o
n
ics
E
n
g
i
n
ee
r
in
g
,
Un
i
v
er
s
iti
Ma
la
y
s
ia
P
ah
an
g
,
P
ek
an
C
a
m
p
u
s
,
2
6
6
0
0
P
ek
an
,
P
ah
an
g
,
Ma
la
y
s
ia.
E
m
ail:
m
a
h
f
u
za
h
@
u
m
p
.
ed
u
.
m
y
1.
I
NT
RO
D
UCT
I
O
N
T
h
is
p
r
o
j
ec
t
is
ca
r
r
ied
to
p
r
o
v
id
e
m
o
r
e
p
r
ec
is
e
m
eth
o
d
f
o
r
b
r
ain
d
o
m
in
a
n
ce
cla
s
s
i
f
ica
tio
n
b
y
u
s
in
g
W
av
elet
an
al
y
s
i
s
.
T
h
e
id
ea
is
to
p
r
o
v
id
e
n
e
w
a
n
al
y
s
i
s
m
et
h
o
d
to
d
eter
m
in
e
t
h
e
b
r
ain
w
a
v
es
s
i
g
n
al
o
f
b
r
ain
d
o
m
i
n
a
n
ce
f
o
r
th
e
p
er
s
o
n
ali
t
y
o
f
p
er
s
o
n
in
ter
m
s
o
f
f
o
u
r
s
u
b
-
b
an
d
f
r
eq
u
e
n
cie
s
w
h
ic
h
Delta
,
T
h
eta,
A
lp
h
a
an
d
B
eta.
I
n
th
is
p
r
o
j
ec
t,
th
er
e
ar
e
f
o
u
r
t
y
p
e
s
o
f
b
asic
b
an
d
s
is
u
s
ed
to
d
eter
m
i
n
e
th
e
d
o
m
i
n
an
ce
o
f
b
r
ain
w
a
v
es.
ac
h
o
f
th
e
b
an
d
s
ar
e
d
if
f
er
en
t
in
f
r
eq
u
en
cie
s
r
an
g
e
w
h
er
e
elta
is
z
–
z
T
h
eta
is
z
–
z
lp
h
a
is
z
–
z
an
d
eta
is
m
o
r
e
th
an
z.
T
h
ese
f
o
u
r
b
an
d
s
w
o
u
ld
r
esu
lt
a
p
atter
n
t
h
at
u
s
ed
to
d
eter
m
i
n
e
th
e
b
r
ain
d
o
m
i
n
an
ce
b
y
s
i
g
n
al
p
r
o
ce
s
s
in
g
.
E
E
G
s
i
g
n
al
w
ill
b
e
a
n
al
y
zin
g
b
y
u
s
in
g
T
w
o
-
Di
m
e
n
s
io
n
al
W
a
v
elet
tec
h
n
iq
u
e.
Ou
r
i
n
itial
ex
p
er
ie
m
e
n
t
i
s
d
o
n
e
u
s
i
n
g
P
o
w
er
Sp
ec
tr
al
De
n
s
it
y
(
P
SD)
a
n
d
E
n
er
g
y
Sp
ec
tr
al
Den
s
it
y
(
P
SD)
[1
]
,
[
2
].
T
h
is
p
ap
er
is
to
ex
p
lo
r
e
m
o
r
e
tech
n
iq
u
e
to
an
al
y
s
is
E
E
G
s
ig
n
al
i
n
b
r
ain
d
o
m
i
n
a
n
ce
ap
p
licatio
n
.
B
est
ex
tr
ac
ted
f
ea
t
u
r
e
w
ill
b
e
p
r
o
ce
ed
e
d
to
class
if
icatio
n
b
y
u
s
in
g
K
-
Nea
r
est
Ne
ig
h
b
o
u
r
(
K
-
NN)
class
i
f
icatio
n
.
T
h
is
c
lass
if
ica
ti
o
n
w
ill
b
e
g
r
o
u
p
i
n
g
a
n
d
clas
s
i
f
y
t
h
e
d
ata
f
r
o
m
W
a
v
elet
a
n
al
y
s
i
s
w
i
th
estab
li
s
h
qu
esti
o
n
n
air
e
to
o
b
tain
th
e
ac
cu
r
ac
y
p
er
ce
n
ta
g
e
[
3
]
.
A
t
th
e
en
d
o
f
an
al
y
s
is
,
t
h
e
ac
cu
r
ac
y
f
r
o
m
clas
s
i
f
icatio
n
w
il
l s
h
o
w
s
t
h
e
b
r
ain
d
o
m
in
a
n
c
e
f
o
r
ea
ch
s
a
m
p
le.
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
-
8708
K
-
N
N
C
la
s
s
ifica
tio
n
o
f B
r
a
in
Do
min
a
n
ce
(
K
h
a
ir
u
l A
mri
z
a
l
A
b
u
N
a
w
a
s
)
2495
I
n
class
ical,
b
r
ain
d
o
m
i
n
an
ce
ca
n
b
e
d
eter
m
in
ed
b
y
e
s
tab
lis
h
q
u
es
tio
n
n
air
e.
B
r
ain
w
av
e
s
h
av
e
s
e
v
er
al
r
h
y
t
h
m
f
r
eq
u
e
n
cie
s
th
at
ca
n
b
e
m
ea
s
u
r
ed
b
y
d
ev
ice
ca
lled
a
s
E
E
G.
W
h
en
to
an
al
y
ze
th
e
s
i
g
n
al,
t
h
er
e
ar
e
a
lo
t
o
f
tech
n
iq
u
e
b
ac
k
t
h
en
s
u
c
h
Fas
t
Fo
u
r
ier
T
r
an
s
f
o
r
m
(
F
F
T
)
,
P
o
w
er
Sp
ec
tr
al
Den
s
it
y
(
P
SD)
an
d
o
th
er
s
.
Ho
w
e
v
er
,
th
o
s
e
m
et
h
o
d
s
s
ti
ll
n
o
t
e
n
o
u
g
h
f
o
r
a
n
E
E
G
s
i
g
n
a
l
s
as
th
e
f
ea
tu
r
es
ex
tr
ac
tio
n
.
T
h
is
is
b
ec
au
s
e
FF
T
an
d
P
SD d
eter
m
in
e
th
e
p
atter
n
o
f
b
r
ain
w
av
e
b
y
h
i
g
h
est p
ea
k
v
al
u
e
o
f
th
e
s
i
g
n
a
l a
n
d
tr
an
s
p
o
r
tatio
n
s
ig
n
als ar
e
n
o
n
-
s
tat
io
n
ar
y
.
Mo
r
eo
v
er
,
ti
m
es
an
d
f
r
eq
u
e
n
c
y
in
f
o
r
m
at
io
n
ca
n
n
o
t
b
e
s
ee
n
at
th
e
s
a
m
e
ti
m
e.
I
t
is
d
if
f
er
en
c
e
w
it
h
W
av
ele
t
an
al
y
s
i
s
w
h
er
e
it
to
o
k
th
e
w
h
o
le
s
i
g
n
al
to
e
x
tr
ac
t
th
e
e
n
er
g
y
v
a
lu
e
o
f
t
h
e
s
ig
n
al.
T
h
er
ef
o
r
e,
W
av
elet
an
al
y
s
is
is
p
r
ef
er
r
ed
.
T
h
is
is
also
W
av
elet
ca
n
p
er
f
o
r
m
m
u
lti r
eso
l
u
tio
n
ti
m
e
-
f
r
eq
u
en
c
y
a
n
al
y
s
i
s
.
R
esear
ch
h
a
s
i
n
d
icate
d
t
h
at
m
o
s
t
p
eo
p
le
ar
e
d
o
m
in
a
n
t
in
o
n
e
b
r
ain
h
e
m
i
s
p
h
er
e.
De
ter
m
i
n
in
g
f
o
r
d
o
m
i
n
a
n
t
b
r
ain
h
e
m
i
s
p
h
er
e
c
an
p
la
y
a
r
o
le
in
d
eter
m
i
n
i
n
g
h
o
w
t
h
e
p
eo
p
le
lear
n
b
est
an
d
h
o
w
h
is
r
elate
to
o
th
er
s
.
B
u
t,
an
y
in
v
e
n
to
r
y
is
j
u
s
t
a
g
u
id
e.
P
eo
p
le
ar
e
m
o
s
t
s
u
cc
e
s
s
f
u
l
w
h
e
n
t
h
e
y
i
n
te
g
r
at
e
an
d
d
ev
elo
p
b
o
th
s
id
es
o
f
th
e
b
r
ain
.
Fro
m
t
h
e
Her
r
m
an
n
b
r
ain
d
o
m
i
n
an
ce
q
u
esti
o
n
n
a
ir
e
th
at
it
ca
n
e
s
tab
l
is
h
w
h
ic
h
s
id
e
th
e
b
r
ain
f
o
r
s
o
m
e
p
er
s
o
n
[
4
].
I
t
is
also
u
s
e
f
u
l
to
co
n
s
id
er
th
e
f
ac
e
v
alid
it
y
o
f
t
h
e
co
n
ce
p
t
o
f
b
r
ain
d
o
m
in
a
n
c
e
m
ea
s
u
r
e
m
e
n
t
t
o
ex
p
er
ts
in
s
ci
en
ti
f
ic
f
ield
s
ass
o
ciate
d
w
i
th
t
h
e
b
r
ain
.
Her
e
it
is
s
af
e
to
s
ay
th
at
th
e
v
er
y
id
ea
o
f
lef
t b
r
ain
-
r
i
g
h
t b
r
ain
d
o
m
in
an
ce
r
e
m
ai
n
s
s
o
m
e
w
h
at
co
n
tr
o
v
er
s
ial.
Ho
w
e
v
er
,
th
o
s
e
h
a
v
e
s
o
m
e
an
o
th
er
tec
h
n
iq
u
e
to
d
eter
m
i
n
e
b
r
ain
d
o
m
i
n
a
n
ce
th
a
t
is
t
h
r
o
u
g
h
b
y
b
r
ain
w
a
v
e
[
5
].
I
n
o
th
er
ter
m
,
b
r
ain
w
a
v
e
m
a
y
ca
l
l
as
n
e
u
r
al
o
s
cillatio
n
.
I
t
is
r
h
y
th
m
ic
o
r
r
ep
etitiv
e
n
eu
r
al
ac
tiv
it
y
in
t
h
e
ce
n
tr
al
n
er
v
o
u
s
s
y
s
te
m
w
h
ich
also
k
n
o
w
n
a
s
b
r
ain
.
T
h
is
k
in
d
o
f
o
s
cillatio
n
ca
n
b
e
o
b
s
er
v
ed
in
th
e
E
E
G.
T
h
e
E
E
G
i
s
t
h
e
r
ec
o
r
d
in
g
o
f
e
lectr
ical
ac
ti
v
it
y
al
o
n
g
t
h
e
s
ca
lp
.
T
h
u
s
,
d
o
m
in
a
n
ce
b
r
ain
w
av
e
is
o
n
e
o
f
th
e
b
r
ain
s
ac
ti
v
it
ies
t
h
at
f
l
o
w
s
w
i
th
i
n
t
h
e
n
e
u
r
o
n
s
o
f
t
h
e
b
r
ain
th
at
ca
n
b
e
class
i
f
y
b
y
E
E
G
[
6
].
Fr
o
m
t
h
e
E
m
o
tiv
e
E
P
OC
d
ev
ice,
th
a
t
ca
n
u
s
e
f
o
r
co
llectin
g
t
h
e
d
ata
f
r
o
m
b
r
ain
w
av
e.
I
t
w
ill
b
e
p
r
e
-
p
r
o
ce
s
s
ed
an
d
ex
tr
ac
ted
f
r
eq
u
e
n
c
y
b
a
n
d
in
s
o
m
e
o
f
r
an
g
e
clas
s
i
f
icatio
n
w
h
e
th
er
in
Del
ta,
T
h
eta,
A
lp
h
a
a
n
d
B
eta.
E
m
o
tiv
E
P
OC
w
i
th
1
4
elec
tr
o
d
es
in
clu
d
e
w
it
h
t
w
o
r
ef
er
e
n
ce
s
ar
e
m
o
s
t
co
m
m
o
n
l
y
as
s
h
o
w
n
in
Fig
u
r
e
1
(
a)
an
d
Fig
u
r
e
1
(
b
)
to
d
etec
t
E
E
G
s
ig
n
al.
No
r
m
all
y
,
th
e
E
E
G
is
d
eter
m
in
ed
th
r
o
u
g
h
AF3
an
d
A
F4
as
s
h
o
w
n
i
n
Fi
g
u
r
e
2
.
A
p
p
ar
en
tl
y
,
th
ese
t
w
o
ch
a
n
n
e
ls
also
k
n
o
w
n
as
Fp
1
an
d
Fp
2
th
at
b
ee
n
p
r
o
p
o
s
ed
in
m
o
s
t
o
f
p
r
o
j
ec
ts
an
d
r
esear
ch
es.
E
E
G
ca
n
b
e
a
n
al
y
ze
d
i
n
ti
m
e
d
o
m
ai
n
,
f
r
eq
u
en
c
y
d
o
m
a
in
an
d
e
v
en
ti
m
e
-
f
r
eq
u
e
n
c
y
d
o
m
ai
n
.
Ho
w
e
v
er
,
m
o
s
t
o
f
p
r
o
j
ec
ts
an
d
r
esear
ch
es
ca
r
r
ied
p
r
ev
io
u
s
l
y
,
t
h
e
y
w
er
e
a
n
al
y
zin
g
i
n
eit
h
er
ti
m
e
d
o
m
ai
n
o
r
f
r
eq
u
en
c
y
d
o
m
ain
.
I
t
is
s
eld
o
m
h
ap
p
en
ed
to
b
e
ti
m
e
-
f
r
eq
u
e
n
c
y
d
o
m
a
in
d
u
e
to
its
li
m
i
ted
tech
n
iq
u
e
th
at
f
o
u
n
d
cu
r
r
en
tl
y
.
(
a)
(
b
)
Fig
u
r
e
1
.
(
a)
E
m
o
tiv
E
P
OC
d
e
v
ice
[
7
]
,
(
b
)
E
m
o
ti
v
E
P
OC
c
h
an
n
el
[
7
]
E
E
G
s
ig
n
al
th
at
g
e
t
f
r
o
m
E
m
o
tiv
E
p
o
c
d
ev
ice
i
s
i
n
n
o
n
-
s
ta
tio
n
ar
y
s
i
g
n
al.
Fo
r
n
o
n
-
s
tatio
n
ar
y
s
i
g
n
al,
th
er
e
ar
e
n
ee
d
in
f
o
r
m
at
io
n
in
b
o
th
th
e
f
r
eq
u
en
c
y
an
d
ti
m
e
d
o
m
ai
n
s
at
o
n
ce
[
8
].
Fo
u
r
ier
T
r
an
s
f
o
r
m
(
FT
)
is
n
o
r
m
all
y
u
s
e
s
f
o
r
tr
an
s
f
o
r
m
at
io
n
s
i
g
n
al
tec
h
n
iq
u
e.
B
u
t,
t
h
e
ti
m
e
s
a
n
d
f
r
eq
u
e
n
c
y
i
n
f
o
r
m
a
tio
n
ca
n
n
o
t
b
e
s
ee
n
at
th
e
s
a
m
e
ti
m
e.
T
h
at
o
n
l
y
g
i
v
es
th
e
f
r
eq
u
e
n
c
y
ex
is
t
in
th
e
s
ig
n
al.
T
h
er
ef
o
r
e,
Fo
u
r
ier
a
n
al
y
s
i
s
i
s
o
lates
w
e
ll i
n
f
r
eq
u
en
c
y
,
b
u
t
n
o
t in
ti
m
e.
T
h
e
av
elet
an
aly
s
is
th
a
t
s
u
p
p
o
r
t
th
e
f
in
ite
s
i
g
n
al
b
ec
au
s
e
av
elets
ar
e
lo
ca
lized
w
a
v
es
alth
o
u
g
h
s
o
m
e
av
elet
s
d
o
n
o
t
h
av
e
co
m
p
ac
t
s
u
p
p
o
r
t
co
m
p
ar
e
w
it
h
T
.
n
th
is
ca
s
e
t
h
e
p
er
f
o
r
m
a
n
ce
o
f
o
u
b
ec
h
ies
d
b
d
ec
o
m
p
o
s
itio
n
is
e
x
ac
t
d
u
e
to
a
g
r
ea
t
s
i
m
ilar
it
y
b
et
w
ee
n
t
h
e
a
n
al
y
ze
d
s
i
g
n
al
an
d
th
e
W
av
ele
t
it
s
elf
as
s
h
o
w
n
i
n
Fig
u
r
e
2
[9
].
T
h
e
d
ec
lar
atio
n
is
i
m
p
o
r
tan
ce
to
ch
o
o
s
e
o
f
W
av
elet
f
o
r
t
h
e
d
e
co
m
p
o
s
i
tio
n
o
f
t
h
e
s
ig
n
al
an
d
d
en
o
is
i
n
g
tech
n
iq
u
e.
Gen
er
all
y
,
ch
o
o
s
i
n
g
lo
n
g
er
W
av
elets
l
ea
d
s
to
a
b
etter
f
r
eq
u
en
c
y
r
eso
l
u
tio
n
b
u
t a
w
o
r
s
e
ti
m
e
r
eso
l
u
tio
n
[9
].
2
-
D
w
a
v
elet
a
n
al
y
s
i
s
is
th
e
m
eth
o
d
to
d
etec
t
th
e
ed
g
e
o
f
in
f
o
r
m
atio
n
s
i
g
n
al
b
ased
o
n
th
e
f
ea
tu
r
e
o
f
i
m
a
g
e
tex
t
u
r
e
[
10
]
.
Fre
q
u
en
c
y
a
n
d
o
r
ien
tatio
n
r
ep
r
esen
tat
i
o
n
s
o
f
Gab
o
r
f
ilter
ar
e
lik
e
th
o
s
e
o
f
th
e
h
u
m
a
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t
201
8
:
2
4
9
4
–
2
5
0
2
2496
v
is
u
al
s
y
s
te
m
,
an
d
th
e
y
h
a
v
e
b
ee
n
f
o
u
n
d
to
b
e
p
a
r
ticu
l
ar
l
y
ap
p
r
o
p
r
iate
f
o
r
tex
tu
r
e
r
ep
r
esen
tatio
n
an
d
d
is
cr
i
m
i
n
atio
n
.
Gab
o
r
f
u
n
ct
io
n
p
r
o
v
id
es
t
h
e
s
p
ec
tr
al
e
n
er
g
y
d
en
s
it
y
co
n
ce
n
tr
ated
ar
o
u
n
d
a
g
i
v
en
p
o
s
itio
n
an
d
f
r
eq
u
en
c
y
i
n
a
ce
r
tain
d
ir
ec
tio
n
.
Mo
r
eo
v
er
,
th
e
p
o
p
u
lar
Gab
o
r
p
ar
am
eter
s
,
5
s
ca
les X
8
o
r
ien
tatio
n
s
is
t
h
e
b
est
ch
o
ice
in
m
a
n
y
s
tu
d
ie
s
an
d
th
at
w
i
ll
ap
p
ly
to
th
i
s
Gab
o
r
f
u
n
ctio
n
[
1
1
].
T
h
er
ef
o
r
e,
Gab
o
r
W
av
elet
is
p
r
ef
er
ab
le
as it c
an
ex
tr
ac
t
m
o
s
t o
f
t
h
e
f
ea
t
u
r
es
f
r
o
m
a
s
i
g
n
a
l
s
u
c
h
as a
m
p
li
tu
d
e
an
d
e
n
er
g
y
[
1
1
].
K
-
Nea
r
est
Nei
g
h
b
o
r
s
(
K
-
NN)
is
th
e
m
et
h
o
d
th
at
u
s
e
f
o
r
c
lass
i
f
y
in
g
th
e
b
r
ain
d
o
m
i
n
an
ce
an
d
t
o
d
eter
m
in
e
w
h
ic
h
f
r
eq
u
e
n
c
y
b
a
n
d
o
f
t
h
e
E
E
G
P
o
w
er
Sp
ec
tr
u
m
w
h
et
h
er
th
at
is
Del
ta,
T
h
eta,
A
lp
h
a,
an
d
B
eta.
T
h
e
class
i
f
ier
w
o
r
k
s
b
y
a
co
m
p
ar
i
n
g
a
n
e
w
s
a
m
p
le
(
test
in
g
d
ata)
w
it
h
th
e
b
aseli
n
e
d
ata
(
tr
ain
i
n
g
d
ata
)
[1
2
].
T
h
e
class
if
ier
w
i
ll
d
eter
m
in
e
w
it
h
k
n
ei
g
h
b
o
u
r
h
o
o
d
in
th
e
tr
ain
in
g
d
ata
an
d
ass
ig
n
class
w
h
ic
h
ap
p
ea
r
m
o
r
e
f
r
eq
u
en
tl
y
i
n
t
h
e
n
ei
g
h
b
o
u
r
h
o
o
d
o
f
k
[1
3
]
,
[
1
4
].
Fig
u
r
e
2
.
W
av
elet
d
ec
o
m
p
o
s
it
io
n
tr
ee
u
s
ed
f
o
r
th
e
r
ea
l
E
E
G
d
ata
s
et
an
d
u
s
ed
to
r
ec
o
n
s
tr
u
c
t th
e
b
r
ain
w
a
v
es
[
9
]
K
-
NN
w
as
w
id
el
y
u
s
ed
b
y
s
e
v
er
al
r
esear
ch
es
a
n
d
p
r
o
j
ec
ts
f
o
r
th
e
class
i
f
icatio
n
p
u
r
p
o
s
e.
T
h
is
is
d
u
e
to
K
-
NN
i
s
v
er
y
ea
s
y
to
u
n
d
er
s
tan
d
an
d
s
i
m
p
le
m
et
h
o
d
th
at
w
o
u
ld
r
et
u
r
n
a
g
o
o
d
ac
cu
r
ac
y
.
o
r
ex
a
m
p
le
tr
ain
i
n
g
p
o
in
t
o
f
s
a
m
p
le
th
at
w
il
l
b
e
u
s
ed
to
class
i
f
ied
s
a
m
p
le
p
o
in
t
wh
er
e
m
ea
n
to
b
e
p
o
s
itiv
e
o
r
n
eg
ati
v
e.
L
et
as
s
u
m
e
th
a
t
s
a
m
p
le
p
o
in
t,
X=
[
2
6
]
an
d
p
u
t
in
to
clas
s
i
f
ier
w
it
h
tr
ai
n
i
n
g
p
o
in
t,
Y
=
[
1
,
5
]
.
T
h
en
,
th
e
class
i
f
ie
r
w
ill
clas
s
if
y
th
e
v
al
u
e
o
f
X
s
u
c
h
as
2
to
th
e
n
ea
r
est
v
alu
e
o
f
Y
an
d
p
u
t
th
e
m
in
to
th
e
g
r
o
u
p
.
T
h
er
ef
o
r
e,
w
h
e
r
e
v
alu
e
o
f
X
is
eq
u
al
to
2
,
it
is
n
ea
r
est
to
v
al
u
e
o
f
Y
eq
u
a
l
t
o
1
.
So
,
v
alu
e
o
f
X
eq
u
al
to
2
w
ill cla
s
s
i
f
y
in
to
t
h
at
g
r
o
u
p
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
ex
p
er
i
m
en
t
s
ta
g
e
is
d
i
v
id
ed
in
to
d
ata
co
llectio
n
,
p
r
e
-
p
r
o
ce
s
s
i
n
g
,
2
-
D
W
av
elet
a
n
d
K
-
N
N
class
i
f
icatio
n
.
T
h
e
r
esear
ch
m
eth
o
d
w
il
l b
e
d
is
cu
s
s
ed
in
t
h
e
n
ex
t
s
ec
tio
n
.
2
.
1
.
Da
t
a
c
o
llect
io
n
P
ar
ticip
an
ts
w
er
e
v
o
l
u
n
teer
in
g
u
n
d
er
g
r
ad
u
ate
s
t
u
d
en
t
s
f
r
o
m
Un
i
v
er
s
i
ti
Ma
la
y
s
ia
P
ah
a
n
g
.
T
o
tal
p
ar
ticip
an
ts
w
er
e
2
1
am
o
n
g
6
m
ales
a
n
d
1
5
f
e
m
ales
.
T
h
e
E
E
G
s
ig
n
als
w
a
s
d
o
w
n
lo
ad
in
g
o
f
f
li
n
e
f
r
o
m
E
m
o
ti
v
T
est B
en
ch
a
f
ter
t
h
e
p
ar
ticip
a
n
t a
n
s
w
er
b
r
ai
n
d
o
m
i
n
a
n
ce
q
u
esti
o
n
n
air
e
a
n
d
th
e
y
w
er
e
g
i
v
e
n
r
est
2
to
5
m
in
u
te
b
ef
o
r
e
E
E
G
d
ata
ac
q
u
i
s
itio
n
.
T
h
e
b
r
ain
w
a
v
e
s
i
g
n
a
l
i
s
r
ec
o
r
d
ed
u
s
i
n
g
1
6
ch
a
n
n
els
in
c
lu
d
i
n
g
t
w
o
r
e
f
er
en
ce
s
i
n
E
E
G
ch
an
n
el.
T
h
e
p
er
io
d
p
r
o
t
o
co
l
o
f
th
e
e
x
p
er
i
m
e
n
t
is
s
h
o
w
n
i
n
Fi
g
u
r
e
3
.
T
h
e
to
tal
ti
m
e
r
eq
u
ir
e
d
f
o
r
ea
ch
p
ar
ticip
an
t
is
ap
p
r
o
x
i
m
atel
y
1
5
to
2
0
m
in
u
te
s
.
I
n
i
tiall
y
,
p
ar
ticip
an
t
r
ested
f
o
r
2
m
in
u
tes
w
h
i
le
E
E
G
ex
p
er
i
m
e
n
tal
p
r
o
ce
d
u
r
es
w
er
e
ca
r
r
ied
o
u
t.
C
o
n
s
eq
u
e
n
tl
y
,
E
E
G
s
i
g
n
a
l
w
er
e
r
ec
o
r
d
ed
co
n
t
i
n
u
o
u
s
l
y
f
o
r
5
m
i
n
u
tes d
u
r
in
g
e
y
e
s
clo
s
ed
.
B
r
ain
w
a
v
e
s
i
g
n
al
w
ill
r
ec
o
r
d
b
y
u
s
i
n
g
E
m
o
t
iv
d
ev
ice
a
n
d
it
h
as
1
6
ch
an
n
els,
b
u
t
i
n
th
i
s
an
al
y
s
i
s
r
eq
u
ir
ed
o
n
l
y
t
w
o
o
u
t
o
f
1
6
ch
an
n
el
s
.
T
h
at
i
s
Fp
1
a
n
d
Fp
2
ch
a
n
n
el
w
h
ic
h
c
h
a
n
n
e
ls
co
n
tai
n
s
t
h
e
m
o
s
t
f
ea
t
u
r
es
th
at
h
elp
in
d
eter
m
i
n
atio
n
o
f
b
r
ain
d
o
m
i
n
a
n
ce
b
ec
au
s
e
t
h
at
ar
e
in
n
ea
r
o
f
lef
t
an
d
r
ig
h
t
f
r
o
n
tal
b
r
ain
.
T
h
e
r
ec
o
r
d
ed
b
r
ain
w
a
v
e
s
i
g
n
a
l
w
il
l b
e
s
av
ed
in
ed
f
f
o
r
m
a
t.
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
-
8708
K
-
N
N
C
la
s
s
ifica
tio
n
o
f B
r
a
in
Do
min
a
n
ce
(
K
h
a
ir
u
l A
mri
z
a
l
A
b
u
N
a
w
a
s
)
2497
10
-
1
5
mi
n
u
t
e
s
2
m
i
n
u
t
e
s
5
m
i
n
u
t
e
s
P
sy
c
h
o
a
n
a
l
y
si
s T
e
st
(
a
n
sw
e
r
t
h
e
1
5
i
t
e
m b
r
a
i
n
d
o
m
i
n
a
n
c
e
q
u
e
st
i
o
n
n
a
i
r
e
s)
R
e
st
d
u
r
i
n
g
e
l
e
c
t
r
o
d
e
s p
l
a
c
e
me
n
t
EEG
d
a
t
a
a
c
q
u
i
si
t
i
o
n
Fig
u
r
e
3
.
P
er
io
d
p
r
o
to
co
l
o
f
b
r
ain
d
o
m
i
n
an
ce
K
-
NN
cla
s
s
i
f
ic
atio
n
ex
p
er
i
m
en
t
2
.
2
.
P
re
-
pro
ce
s
s
ing
P
r
e
-
p
r
o
ce
s
s
in
g
w
as
ca
r
r
ied
o
u
t
to
r
e
m
o
v
e
t
h
e
u
n
n
ec
e
s
s
ar
y
s
i
g
n
al
o
r
ca
lled
as
ar
t
if
ac
t
f
r
o
m
E
E
G
s
ig
n
al.
I
n
p
r
e
-
p
r
o
ce
s
s
i
n
g
,
t
h
er
e
ar
e
t
w
o
p
h
ase
s
t
h
at
is
th
r
es
h
o
ld
an
d
b
an
d
p
ass
f
ilter
.
T
h
e
s
ig
n
a
ls
w
er
e
f
u
r
t
h
er
p
r
o
ce
s
s
ed
u
s
i
n
g
a
s
p
ec
if
ic
alg
o
r
ith
m
o
f
f
iltra
ti
o
n
to
r
ej
ec
t
ar
tif
ac
t
a
n
d
to
allo
w
o
n
l
y
t
h
e
i
n
f
o
r
m
atio
n
s
i
g
n
a
l
f
r
o
m
t
h
e
b
r
ain
w
a
v
e
to
p
ass
th
r
o
u
g
h
th
e
co
r
r
elatio
n
a
n
al
y
s
is
.
No
is
e
f
r
o
m
a
s
i
g
n
al
is
r
es
u
lti
n
g
w
h
e
n
th
e
p
ar
ticip
an
t
d
o
es
an
an
y
m
i
n
o
r
m
o
v
e
m
e
n
t,
e
y
e
b
lin
k
i
n
g
,
w
h
e
n
h
i
s
b
r
ea
th
an
d
s
w
ea
ti
n
g
.
T
h
e
an
al
y
s
i
s
w
o
u
ld
n
ee
d
o
n
l
y
s
i
g
n
a
l.
T
h
er
ef
o
r
e
o
th
er
th
an
s
ig
n
al
th
e
y
ar
e
ass
u
m
ed
as
a
n
o
is
e
an
d
ar
tif
ac
t
to
w
ar
d
s
th
e
s
i
g
n
al.
T
o
r
em
o
v
e
all
th
e
u
n
n
ec
es
s
ar
y
ar
te
f
ac
ts
o
r
n
o
is
e
f
r
o
m
a
s
i
g
n
al
th
a
t
w
ill
b
e
u
s
e
a
t
h
r
es
h
o
ld
to
o
u
tb
o
u
n
d
f
r
o
m
a
ce
r
tain
r
an
g
e
o
f
v
al
u
e
.
As
t
h
e
E
E
G
w
a
s
m
ea
s
u
r
ed
in
1
6
ch
an
n
els.
T
h
e
r
an
g
e
o
f
E
E
G
v
alu
e
is
w
i
th
i
n
-
μ
V
to
μ
V
in
a
m
p
litu
d
e.
T
h
u
s
th
e
s
i
g
n
a
l
i
n
ch
a
n
n
el
p
1
an
d
Fp
2
w
as t
h
r
es
h
o
ld
w
it
h
i
n
th
e
r
an
g
e
s
o
th
at
t
h
e
s
i
g
n
al
co
n
tai
n
s
co
r
r
ec
t E
E
G
s
ig
n
al.
I
n
th
i
s
p
r
o
j
ec
t,
it
r
eq
u
ir
ed
f
o
u
r
s
u
b
-
b
an
d
f
r
eq
u
en
c
ies
f
o
r
an
al
y
s
i
s
.
T
h
e
y
ar
e
Delta,
T
h
eta,
A
lp
h
a
an
d
B
eta.
E
ac
h
o
f
t
h
e
b
r
ain
r
ep
r
esen
ts
d
if
f
er
e
n
t
s
tate
o
f
co
n
s
cio
u
s
n
es
s
w
h
er
e
t
h
e
b
a
n
d
w
av
e
w
ill
ch
a
n
g
e
ac
co
r
d
in
g
to
th
e
ac
tiv
it
y
th
e
y
ar
e
d
o
in
g
.
I
n
th
e
MA
T
L
A
B
s
o
f
t
w
ar
e,
th
e
B
u
t
ter
w
o
r
t
h
lo
w
p
ass
an
d
b
an
d
p
ass
f
ilter
to
id
e
n
ti
f
y
t
h
e
s
ig
n
al
w
h
eth
er
o
f
f
r
eq
u
e
n
c
y
s
u
b
-
b
an
d
.
T
h
e
s
ig
n
al
w
as
s
eg
m
e
n
t
ed
in
to
i
n
d
ep
en
d
en
t
f
o
u
r
s
u
b
-
b
an
d
s
ac
co
r
d
in
g
to
th
eir
o
w
n
f
r
eq
u
e
n
c
y
r
a
n
g
e
a
s
s
tated
b
elo
w
w
it
h
th
e
s
a
m
e
te
ch
n
iq
u
e
w
h
er
e
t
h
e
r
an
g
e
o
f
f
r
e
q
u
en
c
y
f
o
r
th
e
f
ilt
er
w
a
s
ch
a
n
g
ed
ac
co
r
d
in
g
th
e
T
a
b
le
1
.
t
is
ap
p
lied
to
all
c
h
an
n
el
s
as
w
ell
in
Fp
1
an
d
Fp
2.
T
ab
le
1
.
B
r
ain
w
a
v
e
S
ub
-
b
an
d
P
atter
n
D
escr
ip
tio
n
[1
5
]
B
r
a
i
n
w
a
v
e
F
r
e
q
u
e
n
c
y
(
H
z
)
mp
l
i
t
u
d
e
μV
D
e
scri
p
t
i
o
n
B
e
t
a
>
1
3
l
o
w
e
st
A
w
a
k
e
A
l
p
h
a
8
-
13
l
o
w
R
e
l
a
x
e
d
T
h
e
t
a
4
–
8
h
i
g
h
T
i
r
e
d
D
e
l
t
a
0
.
5
-
4
h
i
g
h
e
st
D
e
e
p
S
l
e
e
p
2
.
3
.
2
-
D
w
a
v
elet
T
h
e
ti
m
e
-
d
o
m
ai
n
an
a
l
y
s
is
in
b
io
m
ed
ical
s
i
g
n
a
ls
s
u
c
h
a
s
E
E
G
d
o
es
n
o
t
s
ee
n
t
h
e
t
i
m
e
-
f
r
eq
u
en
c
y
at
th
e
s
a
m
e
ti
m
e
[1
6
]
.
Sp
ec
tr
al
o
r
f
r
eq
u
en
c
y
-
d
o
m
ai
n
an
a
l
y
s
i
s
w
o
u
ld
b
e
v
er
y
h
elp
f
u
l
in
t
h
is
ca
s
e.
Ho
w
e
v
er
,
s
p
ec
tr
al
an
al
y
s
i
s
d
o
es
n
o
t
s
h
o
w
u
s
at
w
h
at
ti
m
es
t
h
e
f
r
eq
u
e
n
c
y
ch
a
n
g
es
o
cc
u
r
.
T
h
e
W
av
elet
tech
n
iq
u
e
w
ill
s
o
lv
e
t
h
e
p
r
o
b
le
m
o
f
r
e
s
o
lu
ti
o
n
b
y
u
s
in
g
Mu
l
ti
-
r
e
s
o
lu
tio
n
an
al
y
s
is
.
T
h
e
W
av
elet
is
to
o
ls
t
h
at
ta
k
e
th
e
d
ata,
f
u
n
ctio
n
o
r
o
p
e
r
ato
r
in
to
d
if
f
e
r
en
t
f
r
eq
u
e
n
c
y
co
m
p
o
n
e
n
t
s
,
an
d
th
en
s
t
u
d
ies
ea
c
h
co
m
p
o
n
e
n
t,
an
d
th
e
n
s
tu
d
ie
s
ea
ch
co
m
p
o
n
e
n
t
w
it
h
a
r
eso
lu
t
io
n
m
atc
h
ed
to
its
s
ca
le.
T
h
is
p
r
o
j
ec
t
u
s
es
2
-
D
Gab
o
r
W
av
elet
to
ex
tr
ac
t
th
e
e
x
p
r
ess
io
n
f
ea
t
u
r
e
f
r
o
m
s
u
b
-
r
eg
io
n
s
o
f
ex
p
r
ess
io
n
i
m
ag
e
s
.
A
cc
o
r
d
in
g
to
a
n
al
y
ze
a
n
d
co
m
p
ar
e
t
h
e
ex
p
r
es
s
io
n
f
ea
t
u
r
es
e
x
tr
a
cted
f
r
o
m
d
i
f
f
er
e
n
t
i
m
a
g
es
te
x
t
u
r
e
w
ith
d
i
f
f
er
en
t
f
r
eq
u
en
c
y
b
an
d
an
d
d
if
f
er
en
t
s
a
m
p
le,
th
at
h
av
e
o
b
tain
ed
s
ati
s
f
ac
to
r
y
ex
p
er
i
m
e
n
tal
r
es
u
lt
s
th
a
t
d
e
m
o
n
s
tr
ates
t
h
e
e
f
f
icie
n
c
y
o
f
o
u
r
alg
o
r
ith
m
.
Gab
o
r
tr
an
s
f
er
f
u
n
ctio
n
(
t
f
r
g
ab
o
r
)
is
u
s
ed
to
g
et
co
ef
f
icien
t
co
n
tain
s
an
in
f
o
r
m
atio
n
r
elativ
e
to
th
e
ti
m
e
-
f
r
eq
u
e
n
c
y
co
n
ten
t
o
f
th
e
s
ig
n
al
ar
o
u
n
d
th
e
ti
m
e
-
f
r
eq
u
en
c
y
lo
ca
tio
n
.
Ge
n
er
all
y
,
s
o
m
e
d
eg
r
ee
o
f
o
v
e
r
s
a
m
p
li
n
g
i
s
co
n
s
id
er
ed
(
x
<
1
)
,
w
h
ic
h
in
tr
o
d
u
ce
s
r
ed
u
n
d
an
c
y
i
n
t
h
e
co
ef
f
icie
n
t
s
to
„
s
m
o
o
t
h
‟
th
e
b
io
r
th
o
n
o
r
m
al
w
i
n
d
o
w
h
,
f
o
r
th
e
s
ak
e
o
f
n
u
m
er
ical
s
tab
ilit
y
.
2
-
D
Gab
o
r
W
av
elet
th
at
e
x
tr
ac
t
t
h
e
i
m
a
g
e
i
n
R
,
G,
B
co
lo
u
r
.
I
n
th
i
s
p
r
o
j
ec
t,
o
u
r
f
ea
t
u
r
e
ex
tr
ac
tio
n
h
as
s
i
m
ilar
s
ize
o
f
i
m
a
g
e
te
x
t
u
r
e
th
at
is
5
6
0
X
4
2
0
p
ix
els.
T
h
at
w
i
ll
r
e
m
o
v
e
th
e
s
ca
le,
ax
e
s
,
an
d
titl
e
o
f
i
m
a
g
e
b
y
u
s
i
n
g
a
u
to
cr
o
p
d
ec
lar
atio
n
in
M
A
T
L
A
B
.
T
h
e
r
e
m
o
v
in
g
w
as
d
o
in
g
b
ec
a
u
s
e
t
h
at
o
n
l
y
an
al
y
ze
a
n
d
s
eg
m
e
n
ted
th
e
in
f
o
r
m
a
tio
n
e
x
tr
ac
ti
o
n
.
B
ef
o
r
e
to
g
et
m
ea
n
a
m
p
lit
u
d
e
an
d
m
ea
n
en
er
g
y
f
r
o
m
t
h
e
i
m
ag
e,
th
a
t
i
m
a
g
e
w
i
ll
c
h
a
n
g
e
i
n
to
g
r
a
y
-
s
ca
le
b
ec
au
s
e
t
h
e
Gab
o
r
f
u
n
c
tio
n
u
s
ed
to
ex
tr
ac
t
t
h
e
f
ea
t
u
r
e
f
r
o
m
t
h
e
Gab
o
r
i
m
a
g
e
an
d
t
h
at
o
n
l
y
ex
tr
ac
t
f
r
o
m
th
e
g
r
a
y
-
s
ca
le
i
m
a
g
e.
T
h
is
ex
tr
ac
tio
n
i
s
s
e
g
m
e
n
te
d
t
h
e
s
u
b
-
r
e
g
io
n
s
f
r
o
m
a
n
ex
p
r
ess
io
n
i
m
a
g
e
an
d
t
h
at
h
a
v
in
g
g
r
ea
tl
y
co
n
tai
n
i
n
g
e
x
p
r
ess
io
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t
201
8
:
2
4
9
4
–
2
5
0
2
2498
2
-
D
Gab
o
r
W
av
elet
w
i
ll
g
i
v
e
th
e
v
al
u
e
o
f
m
ea
n
a
m
p
lit
u
d
e
an
d
s
q
u
ar
ed
e
n
er
g
y
a
f
ter
th
e
i
m
a
g
e
tu
r
n
ed
i
n
to
g
r
a
y
-
s
ca
le.
Fro
m
t
h
e
v
alu
e,
th
at
w
ill
o
b
tai
n
t
h
e
f
r
eq
u
en
c
y
b
a
n
d
w
h
ich
is
t
h
e
b
r
ain
d
o
m
in
a
n
ce
o
f
th
e
p
er
s
o
n
.
T
h
at
w
ill
d
etec
t
t
h
e
ed
g
e
o
f
i
n
f
o
r
m
atio
n
i
n
to
t
h
e
i
m
a
g
e.
P
h
ase
s
y
m
m
etr
y
(
p
h
ases
y
m
)
f
u
n
ctio
n
w
il
l
u
s
e
to
co
m
p
u
te
a
n
d
ca
lcu
late
Gab
o
r
f
ea
tu
r
es
f
r
o
m
t
h
e
g
r
ay
-
s
ca
le
i
m
ag
e
to
g
et
t
h
e
v
al
u
e
o
f
m
ea
n
s
q
u
ar
ed
en
er
g
y
a
n
d
m
ea
n
a
m
p
litu
d
e
i
n
au
to
m
atica
ll
y
b
y
u
s
i
n
g
M
A
T
L
A
B
.
Ho
w
ev
er
,
ap
ar
t
f
r
o
m
t
h
e
Gab
o
r
i
m
a
g
e
p
r
o
ce
s
s
in
g
h
as p
ar
a
m
e
ter
s
to
b
e
s
e
t th
at
i
s
s
ca
le
a
n
d
o
r
ien
tati
o
n
.
Mo
r
eo
v
er
,
th
e
p
o
p
u
lar
Gab
o
r
p
ar
am
e
ter
s
i
s
5
s
ca
le
s
x
8
o
r
ien
tatio
n
s
,
h
a
v
e
b
ee
n
as
s
u
m
e
to
b
e
th
e
b
est
c
h
o
ice
in
m
a
n
y
s
t
u
d
ies
w
it
h
o
u
t
ca
r
ef
u
l
d
is
cu
s
s
io
n
an
d
ex
a
m
i
n
atio
n
o
n
th
eir
p
er
f
o
r
m
an
ce
X
.
T
h
e
n
o
r
m
aliza
t
io
n
is
u
s
ed
to
ch
an
g
e
th
e
e
n
er
g
y
v
al
u
e
i
n
to
s
ev
e
r
al
r
an
g
es
t
h
at
is
„
‟
to
„
‟
.
His
to
g
r
a
m
ch
ar
t
i
n
Mic
r
o
s
o
f
t
E
x
ce
l
w
a
s
u
s
ed
to
o
b
tain
an
d
a
n
al
y
s
e
th
e
p
at
ter
n
s
o
f
b
r
ain
d
o
m
i
n
a
n
ce
w
i
th
f
r
e
q
u
en
c
y
b
an
d
(
Del
ta,
T
h
eta,
A
lp
h
a,
an
d
B
eta)
af
ter
n
o
r
m
alize
d
t
h
e
en
er
g
y
v
alu
e
X
.
2
.
4
.
K
-
NN
c
la
s
s
if
ica
t
io
n
Af
t
er
f
ea
tu
r
e
ex
tr
ac
tio
n
f
r
o
m
2
-
D
Gab
o
r
W
av
elet,
th
e
f
ea
t
u
r
es
w
er
e
clas
s
i
f
ied
b
y
u
s
in
g
K
-
Nea
r
est
Neig
h
b
o
r
(
K
-
NN)
.
T
h
e
ac
cu
r
ac
y
f
r
o
m
cla
s
s
i
f
icat
io
n
w
ill
s
h
o
w
s
t
h
e
b
r
ain
d
o
m
in
a
n
ce
f
o
r
ea
ch
s
a
m
p
le.
I
t
s
h
o
w
s
th
e
ac
c
u
r
ac
y
o
f
t
h
e
a
n
a
l
y
s
i
s
b
ee
n
t
h
r
o
u
g
h
.
So
,
K
-
NN
w
a
s
u
s
ed
to
clas
s
i
f
y
t
h
e
m
.
I
n
K
-
NN,
t
h
er
e
ar
e
th
r
ee
t
h
in
g
=
9
d
s
d
9
9
9
n
ee
d
t
o
u
n
d
er
s
ta
n
d
i
n
ad
v
a
n
ce
d
.
T
h
er
e
ar
e
test
i
n
g
s
et,
tr
ain
i
n
g
s
et
a
n
d
g
r
o
u
p
s
e
t.
T
esti
n
g
s
et
i
s
th
e
d
ata
to
cla
s
s
if
y
w
it
h
ap
p
r
o
ac
h
o
f
tr
ai
n
in
g
s
et.
T
r
a
in
i
n
g
s
et
ar
e
th
e
d
ata
th
at
u
s
ed
to
co
m
p
ar
e
w
it
h
th
e
s
a
m
p
le
s
et
to
class
if
y
th
e
te
s
ti
n
g
s
et
in
ce
r
t
ain
t
h
at
b
ee
n
s
et
i
n
g
r
o
u
p
s
et
w
h
et
h
er
lef
t
d
o
m
in
a
n
ce
a
n
d
r
ig
h
t
d
o
m
i
n
a
n
ce
o
f
b
r
ain
.
Gr
o
u
p
s
et
ca
n
o
n
l
y
b
e
d
ef
i
n
ed
in
n
u
m
b
er
in
s
tead
o
f
ch
ar
ac
ter
.
Fo
r
ex
a
m
p
le,
r
ig
h
t
b
r
ain
d
o
m
in
a
n
ce
s
et
n
u
m
b
er
a
s
„
‟
le
f
t
b
r
ain
d
o
m
i
n
an
ce
s
et
n
u
m
b
er
as
„
‟
a
n
d
te
s
ti
n
g
w
i
l
l
s
et
a
s
n
u
m
b
er
„
‟
.
T
h
at
ca
n
ea
s
e
to
o
b
tain
th
e
ac
cu
r
ac
y
o
f
d
ata
f
r
o
m
2
-
D
Gab
o
r
W
av
elet.
m
ea
n
s
th
at
3
0
p
er
ce
n
t
o
u
t
o
f
2
0
s
a
m
p
les b
ec
o
m
e
te
s
ti
n
g
s
et
an
d
7
0
p
er
ce
n
t o
f
2
0
s
am
p
le
s
b
ec
o
m
e
tr
ai
n
i
n
g
s
et.
I
t sa
m
e
g
o
e
s
f
o
r
8
0
:2
0
,
th
at
is
2
0
p
er
ce
n
t
o
f
2
0
s
am
p
les
b
ec
o
m
e
te
s
ti
n
g
s
et
an
d
8
0
p
er
ce
n
t
o
f
2
0
s
a
m
p
les
b
ec
o
m
e
tr
ain
i
n
g
s
et.
Hen
ce
,
t
h
e
d
ata
w
as c
la
s
s
i
f
ied
b
ased
o
n
t
h
ese
t
w
o
r
atio
s
an
d
it r
et
u
r
n
ed
a
p
er
ce
n
tag
e
o
f
ac
cu
r
ac
y
o
f
cl
ass
i
f
icatio
n
.
L
ast
l
y
,
th
e
test
in
g
s
et
w
a
s
cla
s
s
if
ied
w
it
h
k
f
r
o
m
1
to
1
5
s
e
t
v
alu
e
o
f
tr
ain
in
g
s
et.
Fo
r
e
x
a
m
p
le,
7
0
:3
0
m
ea
n
s
t
h
at
m
y
s
a
m
p
le
s
et
is
6
o
u
t
o
f
2
0
s
a
m
p
les
w
h
ile
tr
a
in
i
n
g
s
et
is
1
4
o
u
t
o
f
2
0
s
a
m
p
les.
T
h
er
ef
o
r
e,
th
at
w
il
l
b
e
class
i
f
ied
t
h
e
s
a
m
p
le
s
et
f
r
o
m
k
=
1
to
k
=
1
5
f
o
r
p
u
r
p
o
s
e
to
o
b
tain
w
h
ich
k
r
etu
r
n
s
m
e
h
i
g
h
e
s
t
p
er
ce
n
tag
e
o
f
ac
c
u
r
ac
y
.
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
T
h
e
E
E
G
s
ig
n
als
co
llected
t
o
o
b
tain
f
o
u
r
f
r
eq
u
en
c
y
b
an
d
(
Delta,
T
h
eta,
A
lp
h
a,
B
eta)
f
r
o
m
t
w
o
ch
an
n
el
s
.
T
h
er
e
w
er
e
2
1
s
a
m
p
le
f
r
o
m
UM
P
s
t
u
d
en
t
a
n
d
al
l
E
E
G
s
ig
n
al
h
a
s
b
ee
n
r
ec
o
r
d
ed
u
s
i
n
g
E
m
o
ti
v
e
af
ter
ea
ch
o
f
s
t
u
d
en
t
a
n
s
w
e
r
in
g
t
h
e
q
u
esti
o
n
n
a
ir
e.
T
h
er
e
ar
e
tw
o
ch
a
n
n
els
to
u
s
e
f
o
r
co
m
p
leti
n
g
th
e
o
b
s
e
r
v
atio
n
an
d
an
a
l
y
s
ed
,
th
at
is
Fp
1
an
d
Fp
2
.
T
h
e
MA
T
L
A
B
s
o
f
t
w
ar
e
h
as b
ee
n
u
s
ed
to
p
r
o
ce
s
s
th
e
d
ata.
T
ab
le
2
s
h
o
w
s
t
h
e
b
r
ain
d
o
m
in
an
ce
q
u
est
io
n
n
air
e
r
esu
lts
.
T
h
e
o
b
s
er
v
at
io
n
f
o
r
le
f
t
an
d
r
ig
h
t
b
r
ai
n
d
o
m
i
n
a
n
ce
u
s
i
n
g
t
h
is
q
u
est
io
n
n
air
e
also
s
i
m
ilar
w
it
h
ca
s
e
s
t
u
d
y
b
e
f
o
r
e
w
h
er
e
w
h
e
n
t
h
e
p
er
s
o
n
s
tr
o
n
g
in
m
at
h
e
m
a
tics
a
n
d
s
cien
ce
t
h
er
e
ar
e
m
o
r
e
to
lef
t
-
b
r
ain
d
o
m
i
n
a
n
ce
in
e
n
g
in
ee
r
i
n
g
s
t
u
d
en
t.
T
ab
le
2
.
B
r
ain
Do
m
in
a
n
ce
Q
u
esti
o
n
n
air
e
R
es
u
lt
s
N
o
.
o
f
samp
l
e
s
B
r
a
i
n
D
o
mi
n
a
n
c
e
7
R
13
L
1
B
i
l
a
t
e
r
a
l
T
w
o
-
Di
m
en
s
io
n
al
W
av
e
let
is
th
e
o
th
er
tech
n
iq
u
e
w
h
er
e
to
d
eter
m
i
n
e
s
u
b
-
b
an
d
f
r
eq
u
en
c
y
o
f
b
r
ain
d
o
m
i
n
a
n
ce
a
n
d
s
h
o
w
t
h
e
r
e
s
u
lt
f
o
r
Fp
1
an
d
Fp
2
ch
a
n
n
el
in
Gab
o
r
W
av
elet.
T
h
e
2
D
Gab
o
r
f
u
n
c
tio
n
s
p
r
o
p
o
s
ed
ar
e
lo
ca
l
s
p
atial
b
an
d
p
ass
f
il
ter
s
th
a
t
ac
h
ie
v
e
th
e
th
eo
r
etica
l
li
m
it
f
o
r
co
n
j
o
in
t
r
eso
lu
tio
n
o
f
in
f
o
r
m
atio
n
in
th
e
2
D
s
p
atia
l
an
d
2
D
Fo
u
r
ier
d
o
m
ain
s
.
T
h
e
Fig
u
r
e
4
to
Fi
g
u
r
e
7
s
h
o
w
t
h
e
f
ea
t
u
r
e
an
d
in
f
o
r
m
atio
n
o
f
th
e
i
m
a
g
e
f
o
r
e
ac
h
s
u
b
-
b
an
d
f
r
eq
u
en
c
y
w
h
er
e
th
e
ch
a
n
n
e
l o
f
Fp
1
.
Af
ter
t
h
at,
t
h
e
f
ea
tu
r
e
s
ar
e
ex
t
r
ac
ted
th
r
o
u
g
h
t
h
e
i
m
a
g
es.
B
u
t,
th
e
i
m
a
g
es
n
ee
d
to
m
o
d
i
f
y
i
n
ad
v
a
n
ce
b
ef
o
r
e
ex
tr
ac
tio
n
.
T
h
is
b
ec
au
s
e
th
at
th
e
f
u
n
ct
io
n
ap
p
lied
o
n
l
y
ab
le
to
e
x
tr
ac
t
t
h
e
f
ea
tu
r
e
s
f
r
o
m
a
g
r
a
y
-
s
ca
le
f
o
r
m
.
A
n
d
ev
e
n
t
h
e
i
m
a
g
es
m
u
s
t
b
e
ex
cl
u
d
in
g
t
h
e
a
x
es
an
d
o
th
er
s
af
ter
t
h
e
ax
es.
T
h
er
ef
o
r
e,
cr
o
p
im
a
g
e
p
r
o
ce
s
s
w
as d
o
n
e
f
o
r
th
at
p
u
r
p
o
s
e
an
d
th
e
n
th
e
i
m
a
g
es
w
er
e
t
u
r
n
i
n
to
g
r
a
y
-
s
ca
le.
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
-
8708
K
-
N
N
C
la
s
s
ifica
tio
n
o
f B
r
a
in
Do
min
a
n
ce
(
K
h
a
ir
u
l A
mri
z
a
l
A
b
u
N
a
w
a
s
)
2499
Fig
u
r
e
4
.
Fp
1
Delta
-
b
an
d
f
o
r
s
a
m
p
le
n
o
.
1
9
Fig
u
r
e
5
.
Fp
1
T
h
eta
-
b
an
d
f
o
r
s
a
m
p
le
n
o
.
1
9
Fig
u
r
e
6
.
Fp
1
A
lp
h
a
-
b
an
d
f
o
r
s
a
m
p
le
n
o
.
1
9
Fig
u
r
e
7
.
Fp
1
B
eta
-
b
an
d
f
o
r
s
a
m
p
le
n
o
.
1
9
Fig
u
r
e
8
.
Av
er
ag
e
n
o
r
m
aliza
ti
o
n
f
o
r
Fp
1
ch
an
n
el.
b
eta
-
b
an
d
s
h
o
w
t
h
e
h
ig
h
es
t
wh
er
e
to
in
d
icate
lef
t
-
b
r
ain
Fig
u
r
e
9
.
Av
er
ag
e
n
o
r
m
aliza
ti
o
n
f
o
r
Fp
2
ch
an
n
el.
th
eta
-
b
an
d
s
h
o
w
t
h
e
h
ig
h
e
s
t
wh
er
e
to
in
d
icate
r
ig
h
t
-
br
ain
B
ased
o
n
Fig
u
r
e
8
an
d
Fig
u
r
e
9
,
th
e
av
er
ag
e
d
ata
af
ter
n
o
r
m
aliza
tio
n
en
er
g
y
ca
n
b
e
u
ti
lize
d
th
e
lef
t
-
b
r
ain
an
d
r
i
g
h
t
-
b
r
ai
n
d
o
m
i
n
a
n
ce
b
y
r
ef
er
s
th
e
b
o
th
c
h
a
n
n
el
an
d
t
h
e
h
i
g
h
e
s
t
h
i
s
to
g
r
a
m
f
o
r
ea
ch
s
u
b
-
b
a
n
d
f
r
eq
u
en
c
y
.
T
h
e
Fp
1
ch
a
n
n
el
as
t
h
e
le
f
t
-
b
r
ain
d
o
m
in
a
n
ce
i
s
in
d
icate
B
eta
-
b
an
d
w
h
er
ea
s
Fp
2
ch
a
n
n
el
as
th
e
r
ig
h
t
-
b
r
ain
d
o
m
in
a
n
ce
is
i
n
d
i
ca
te
T
h
eta
-
b
an
d
.
Fo
r
b
ilater
al
ca
s
es,
it
ca
n
n
o
t
in
d
icate
t
h
e
s
ub
-
b
an
d
f
r
eq
u
e
n
c
y
b
ec
au
s
e
th
er
e
i
s
o
n
l
y
o
n
e
s
a
m
p
le.
T
h
e
r
e
is
p
o
s
s
ib
ilit
y
o
f
2
-
D
W
a
v
elet
r
es
u
lt
s
i
s
m
o
r
e
p
r
ec
is
e
b
ec
au
s
e
th
at
it a
n
al
y
s
e
en
er
g
y
o
f
s
ig
n
al
in
s
ca
le
„
s
‟
o
r
ien
tatio
n
„
θ
„
an
d
p
h
y
s
ical
lo
ca
tio
n
(
x
,
y
)
.
T
o
p
r
o
v
e
th
is
a
n
al
y
s
is
,
t
h
at
w
il
l
r
ef
er
th
e
b
r
ain
d
o
m
i
n
a
n
ce
cr
iter
ia.
T
h
e
b
r
ain
d
o
m
i
n
a
n
ce
h
as
m
e
n
tio
n
wh
er
e
r
ig
h
t
-
b
r
ain
p
eo
p
le
ar
e
m
o
r
e
cr
ea
tiv
e
an
d
in
t
u
iti
v
e.
T
h
e
m
ed
itatio
n
an
al
y
s
i
s
,
Delta
-
b
a
n
d
s
ig
n
al
ar
e
ass
o
ciate
d
w
it
h
th
e
d
ee
p
est
lev
e
ls
o
f
r
elax
atio
n
an
d
r
esto
r
ativ
e,
h
ea
li
n
g
s
leep
.
T
h
at
is
n
o
t
s
i
m
ilar
f
o
r
r
ig
h
t
-
b
r
ai
n
d
o
m
in
a
n
ce
cr
iter
ia.
T
h
e
T
h
eta
-
b
an
d
f
r
eq
u
en
c
y
r
an
g
e
i
s
i
n
v
o
l
v
ed
in
d
a
y
d
r
ea
m
i
n
g
a
n
d
m
ak
e
„
h
i
g
h
l
y
s
u
g
g
e
s
tib
le‟
b
ec
a
u
s
e
t
h
e
y
ar
e
in
a
d
ee
p
ly
r
elax
ed
s
e
m
i
-
h
y
p
n
o
tic
s
tate.
T
h
at
is
h
elp
in
g
to
i
m
p
r
o
v
e
o
u
r
in
tu
itio
n
,
c
r
ea
tiv
it
y
a
n
d
m
a
k
es
p
er
s
o
n
m
o
r
e
n
atu
r
al.
T
h
ese
cr
iter
ia
also
s
u
itab
le
a
n
d
r
elate
d
w
it
h
r
ig
h
t
-
b
r
ain
d
o
m
i
n
an
ce
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t
201
8
:
2
4
9
4
–
2
5
0
2
2500
K
-
NN
is
t
h
e
tec
h
n
iq
u
e
th
at
ca
n
u
s
e
to
a
n
al
y
s
e
t
h
e
r
e
s
u
l
t
f
r
o
m
2
-
D
W
a
v
elet
a
n
d
to
p
r
o
v
e
t
h
is
an
al
y
s
is
b
ased
o
n
th
e
h
i
g
h
est
ac
cu
r
ac
y
p
er
ce
n
ta
g
e.
K
-
NN
w
as
d
o
n
e
in
t
w
o
o
f
r
atio
s
an
d
t
h
e
v
a
lu
e
o
f
k
.
T
h
er
e
ar
e
7
0
:3
0
an
d
8
0
:2
0
f
o
r
r
atio
s
w
h
i
le
th
e
m
a
x
i
m
u
m
k
f
o
r
b
o
th
r
atio
s
is
1
5
.
Fig
u
r
e
1
0
an
d
Fig
u
r
e
1
1
s
h
o
w
t
h
e
r
esu
lt
in
to
t
w
o
cla
s
s
i
f
ica
tio
n
s
o
f
r
ati
o
.
Fro
m
th
e
c
lass
if
icatio
n
,
t
h
e
r
esu
lt
o
b
tai
n
ed
b
ased
o
n
d
ata
co
r
r
ec
tio
n
w
h
ich
m
ea
n
s
th
at
in
ce
r
tai
n
v
alu
e
o
f
k
,
it
g
a
v
e
ce
r
tai
n
n
u
m
b
er
o
f
co
r
r
ec
t c
lass
i
f
icatio
n
f
o
r
th
e
te
s
ti
n
g
s
et.
Fo
r
ex
a
m
p
le,
in
F
ig
u
r
e
1
0
,
w
h
e
n
k
=
4
,
th
e
r
esu
lt
s
h
o
w
s
th
a
t 5
o
u
t o
f
6
test
i
n
g
s
et
w
er
e
co
r
r
ec
t in
th
e
cla
s
s
i
f
icatio
n
.
Fig
u
r
e
1
0
.
Sh
o
w
ac
c
u
r
ac
y
p
er
ce
n
tag
e
f
o
r
r
atio
7
0
:3
0
.
T
h
e
k
is
v
ar
ied
f
r
o
m
1
to
1
5
.
Fro
m
t
h
e
f
ig
u
r
e,
th
e
h
ig
h
e
s
t a
cc
u
r
ac
y
is
o
b
tain
ed
f
r
o
m
k
=
4
,
w
i
th
ac
cu
r
ac
y
8
3
%
Fig
u
r
e
1
1
.
Sh
o
w
ac
c
u
r
ac
y
p
er
ce
n
tag
e
f
o
r
r
atio
8
0
:2
0
.
T
h
e
k
is
v
ar
ied
f
r
o
m
1
to
1
5
.
Fro
m
t
h
e
f
ig
u
r
e,
th
e
h
ig
h
e
s
t a
cc
u
r
ac
y
is
o
b
tain
ed
f
r
o
m
k
=2
,
w
it
h
ac
c
u
r
ac
y
1
00%
T
h
e
r
esu
lt
f
r
o
m
Fi
g
u
r
e
1
1
s
h
o
w
th
e
h
i
g
h
est
p
er
ce
n
tag
e
ac
cu
r
ac
y
w
h
e
n
k
=
2
it
g
a
v
e
1
0
0
%
o
f
ac
cu
r
ac
y
.
T
h
at
is
t
h
e
b
est o
f
d
ata
an
al
y
s
is
.
T
h
e
m
ea
n
s
o
f
t
h
is
r
esu
lt a
ls
o
s
h
o
w
s
t
h
at
i
f
t
h
e
a
m
o
u
n
t o
f
d
ata
s
et
i
s
h
ig
h
er
,
t
h
en
th
e
ac
c
u
r
ac
y
o
f
d
ata
m
a
y
g
o
h
ig
h
er
t
h
an
th
i
s
r
esu
lt.
T
h
is
i
s
b
ec
au
s
e
w
h
en
t
h
e
r
atio
is
c
h
an
g
ed
8
0
:2
0
,
it
r
esu
lts
1
0
0
%
w
h
er
e
i
n
cr
ea
s
e
ar
o
u
n
d
1
7
%
co
m
p
ar
e
d
to
r
atio
o
f
7
0
:3
0
.
As
a
co
n
cl
u
s
io
n
,
t
h
e
ac
c
u
r
ac
y
w
il
l b
e
in
cr
ea
s
e
w
h
en
t
h
e
a
m
o
u
n
t
o
f
tr
ain
i
n
g
s
et
g
o
es h
i
g
h
er
.
4.
CO
NCLU
SI
O
N
T
h
e
p
r
o
j
ec
t
ab
le
to
class
if
y
b
r
ain
d
o
m
in
a
n
ce
b
ased
o
n
E
E
G
s
i
g
n
al
r
ef
er
r
ed
to
b
r
ain
d
o
m
i
n
a
n
ce
q
u
esti
o
n
n
air
e.
T
h
e
2
-
D
Gab
o
r
W
av
elet
co
u
ld
an
al
y
ze
b
r
ain
d
o
m
i
n
an
ce
w
i
th
ac
c
u
r
ac
y
8
3
%
to
1
0
0
%
th
at
o
b
tain
ed
f
r
o
m
K
-
NN
clas
s
i
f
ic
atio
n
.
Fo
r
th
e
r
ec
o
m
m
en
d
atio
n
an
d
f
u
tu
r
e
d
ev
elo
p
m
e
n
t,
th
i
s
s
u
g
g
esti
o
n
ca
n
u
p
g
r
ad
e
to
m
ak
e
t
h
is
an
al
y
s
i
s
is
m
o
r
e
in
ter
ac
tiv
e
an
d
v
al
u
a
b
le
.
T
h
e
E
E
G
d
ata
ca
n
b
e
i
m
p
r
o
v
ed
w
h
en
r
ec
o
r
d
in
g
th
e
b
r
ain
w
a
v
e
s
ig
n
al
in
to
th
e
o
n
li
n
e
s
y
s
te
m
.
Fro
m
t
h
e
b
r
ain
w
a
v
e
s
ig
n
al
th
a
t c
a
n
s
h
o
w
th
er
e
b
r
ain
d
o
m
i
n
an
ce
r
esu
lt i
n
to
s
m
ar
t p
h
o
n
e
b
y
u
s
i
n
g
GSM
s
y
s
te
m
.
T
h
e
p
ar
en
t
o
r
lectu
r
er
ca
n
d
o
w
n
lo
ad
t
h
e
ap
p
licatio
n
a
n
d
tr
y
to
i
m
p
le
m
e
n
t
f
o
r
ch
ild
r
en
w
h
o
ar
e
ca
n
n
o
t r
ea
d
o
r
w
r
ite
t
o
ch
an
g
e
t
h
eir
s
t
u
d
y
tec
h
n
iq
u
e
b
ased
o
n
b
r
ain
d
o
m
i
n
an
ce
cla
s
s
i
f
icatio
n
.
T
h
e
W
av
elet
tec
h
n
iq
u
e
u
s
ed
in
t
h
i
s
p
r
o
j
ec
t
in
o
r
d
er
to
an
al
y
ze
t
h
e
E
E
G
s
i
g
n
al
g
av
e
a
s
u
cc
e
s
s
f
u
l
r
esu
lt
w
h
en
t
h
at
ca
n
cla
s
s
i
f
y
t
h
e
b
r
ain
d
o
m
in
a
n
ce
o
f
a
p
er
s
o
n
.
T
h
at
it
b
ec
au
s
e
th
e
W
av
e
let
ca
n
an
al
y
ze
th
e
b
r
ain
s
ig
n
al
b
ased
o
n
s
ca
le
a
n
d
o
r
ien
tatio
n
.
Ho
w
e
v
er
,
h
id
d
en
in
f
o
r
m
atio
n
o
f
b
r
ain
d
o
m
i
n
an
ce
i
n
ter
m
s
o
f
b
r
ain
w
a
v
e
ca
n
b
e
ex
p
lo
r
ed
in
f
u
t
u
r
e
r
esear
ch
.
A
t
t
h
e
last
,
t
h
e
r
esu
l
t
ca
n
b
e
i
m
p
r
o
v
ed
w
h
en
to
u
s
e
Ne
u
r
o
s
k
y
Min
d
s
et
d
ev
ice
b
ec
a
u
s
e
t
h
e
d
ev
ice
is
m
o
r
e
ac
cu
r
ate
to
ca
p
tu
r
e
th
e
b
r
ain
s
i
g
n
a
l c
o
m
p
ar
ed
w
ith
E
m
o
t
iv
d
ev
ice.
ACK
NO
WL
E
D
G
E
M
E
NT
S
T
h
is
r
esear
ch
w
as s
u
p
p
o
r
ted
b
y
a
Gr
an
t
at
t
h
e
Un
iv
er
s
iti Ma
l
a
y
s
ia
P
ah
a
n
g
(
R
D
U1
7
0365
).
RE
F
E
R
E
NC
E
S
[1
]
N.
S
.
H.
B.
A
.
Ha
m
id
.
2
0
1
5
,
“
Br
a
in
Do
m
in
a
n
c
e
Us
in
g
Bra
in
w
a
v
e
S
ig
n
a
l
”
,
Ba
c
h
e
lo
r,
T
h
e
sis,
Un
iv
e
rsit
y
M
a
la
y
sia
P
a
h
a
n
g
,
P
a
h
a
n
g
.
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
-
8708
K
-
N
N
C
la
s
s
ifica
tio
n
o
f B
r
a
in
Do
min
a
n
ce
(
K
h
a
ir
u
l A
mri
z
a
l
A
b
u
N
a
w
a
s
)
2501
[2
]
M
.
M
u
sta
f
a
,
e
t
a
l
.
,
“
ra
i
n
d
o
m
in
a
n
c
e
u
sin
g
b
ra
in
w
a
v
e
sig
n
a
l
”
2
0
1
5
I
EE
E
I
n
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
C
o
n
tr
o
l
S
y
ste
m,
Co
mp
u
ti
n
g
a
n
d
En
g
i
n
e
e
rin
g
(
ICCS
CE).
2
0
1
5
.
p
p
.
2
9
8
-
3
0
2
.
[3
]
P
.
S
h
a
rm
a
,
e
t
a
l
.
“
a
u
lt
e
tec
ti
o
n
a
n
d
C
las
sif
ica
ti
o
n
in
T
ra
n
sm
iss
io
n
L
in
e
Us
in
g
W
a
v
e
let
T
ra
n
s
f
o
rm
a
n
d
NN
”
Bu
ll
e
ti
n
o
f
En
g
i
n
e
e
rin
g
a
n
d
In
fo
r
ma
ti
c
s
, v
o
l.
5
n
o
.
3
,
p
p
.
2
8
4
-
2
9
5
,
2
0
1
6
.
[4
]
N.
S
u
laim
a
n
,
e
t
a
l
.
,
"
EE
G
-
b
a
se
d
S
tres
s
F
e
a
tu
re
s
Us
in
g
S
p
e
c
tral
Ce
n
tro
id
s
T
e
c
h
n
iq
u
e
a
n
d
k
-
Ne
a
re
st
Ne
ig
h
b
o
r
Clas
sif
ier,
"
in
Co
mp
u
ter
M
o
d
e
ll
i
n
g
a
n
d
S
imu
l
a
ti
o
n
(
UKS
im),
2
0
1
1
Uk
S
im
1
3
t
h
In
ter
n
a
ti
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
,
2
0
1
1
,
p
p
.
6
9
-
7
4
.
[5
]
H.
A
.
S
h
e
d
e
e
d
,
"
A
n
e
w
m
e
th
o
d
f
o
r
p
e
rso
n
id
e
n
ti
f
ica
ti
o
n
i
n
a
b
i
o
m
e
tri
c
se
c
u
rit
y
s
y
st
e
m
b
a
se
d
o
n
b
r
a
in
EE
G
sig
n
a
l
p
ro
c
e
ss
in
g
,
"
in
In
fo
rm
a
ti
o
n
a
n
d
Co
mm
u
n
ica
ti
o
n
T
e
c
h
n
o
l
o
g
ies
(W
ICT
),
2
0
1
1
W
o
rld
Co
n
g
re
ss
o
n
,
2
0
1
1
,
p
p
.
1
2
0
5
-
1
2
1
0
.
[6
]
H.
Xu
,
e
t
a
l
.
,
"
Hu
m
a
n
id
e
n
ti
f
ica
ti
o
n
w
it
h
e
lec
tro
e
n
c
e
p
h
a
l
o
g
ra
m
(EE
G
)
sig
n
a
l
p
ro
c
e
ss
in
g
,
"
in
C
o
mm
u
n
ica
ti
o
n
s
a
n
d
In
f
o
rm
a
t
io
n
T
e
c
h
n
o
l
o
g
ies
(
IS
CIT
),
2
0
1
2
In
ter
n
a
ti
o
n
a
l
S
y
mp
o
si
u
m
o
n
,
2
0
1
2
,
p
p
.
1
0
2
1
-
1
0
2
6
.
[7
]
R.
M
a
sk
e
li
u
n
a
s,
e
t
a
l
.
,
"
Co
n
su
m
e
r
-
g
ra
d
e
EE
G
d
e
v
ic
e
s:
a
re
th
e
y
u
s
a
b
le
f
o
r
c
o
n
tro
l
tas
k
s?
,
"
P
e
e
rJ
,
v
o
l.
4
,
p
.
e
1
7
4
6
,
2
0
1
6
.
[8
]
N.
H.
A
.
Ha
m
id
,
e
t
a
l
.
,
"
Ev
a
lu
a
ti
o
n
o
f
h
u
m
a
n
stre
s
s
u
sin
g
EE
G
P
o
w
e
r
S
p
e
c
tru
m
,
"
in
S
i
g
n
a
l
Pr
o
c
e
ss
in
g
a
n
d
Its
Ap
p
li
c
a
ti
o
n
s (
CS
PA
),
2
0
1
0
6
t
h
I
n
ter
n
a
ti
o
n
a
l
Co
ll
o
q
u
i
u
m o
n
,
2
0
1
0
,
p
p
.
1
-
4.
[9
]
F
.
Eb
ra
h
im
i,
e
t
a
l
.
,
"
A
u
to
m
a
ti
c
sle
e
p
sta
g
e
c
las
sif
i
c
a
ti
o
n
b
a
se
d
o
n
EE
G
sig
n
a
ls
b
y
u
sin
g
n
e
u
ra
l
n
e
tw
o
rk
s
a
n
d
w
a
v
e
let
p
a
c
k
e
t
c
o
e
ff
ici
e
n
ts,
"
in
En
g
i
n
e
e
rin
g
in
M
e
d
icin
e
a
n
d
Bi
o
lo
g
y
S
o
c
iety
,
2
0
0
8
.
EM
B
S
2
0
0
8
.
3
0
t
h
A
n
n
u
a
l
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
f
th
e
I
EE
E,
2
0
0
8
,
p
p
.
1
1
5
1
-
1
1
5
4
.
[1
0
]
G
.
X
iao
-
Jin
g
,
e
t
a
l
.,
“
p
p
li
c
a
ti
o
n
o
f
a
v
e
let
n
a
l
y
sis
in
e
tec
ti
n
g
Ru
n
w
a
y
o
re
ig
n
Ob
jec
t
e
b
ris
”
T
EL
KOM
NIKA
(
T
e
lec
o
mm
u
n
ica
t
io
n
,
Co
mp
u
ti
n
g
El
e
c
tro
n
ics
a
n
d
Co
n
tro
l)
,
v
o
l
.
1
1
,
n
o
.
4
,
p
p
.
7
5
9
-
7
6
6
,
2
0
1
3
.
[1
1
]
T
.
Z.
a
.
B.
-
L
.
L
u
,
"
S
e
lec
ti
n
g
Op
ti
m
a
l
Orie
n
tatio
n
s
o
f
G
a
b
o
r
W
a
v
e
let
F
il
ters
f
o
r
F
a
c
ial
Im
a
g
e
An
a
ly
sis,
"
p
.
1
0
,
2
0
0
5
.
[1
2
]
M
.
M
u
ru
g
a
p
p
a
n
,
e
t
a
l
.
,
"
Clas
sif
ic
a
ti
o
n
o
f
h
u
m
a
n
e
m
o
ti
o
n
f
ro
m
EE
G
u
sin
g
d
isc
re
te
w
a
v
e
let
tran
sf
o
r
m
,
"
J
o
u
rn
a
l
o
f
Bi
o
me
d
ica
l
S
c
ien
c
e
a
n
d
En
g
in
e
e
r
in
g
,
v
o
l.
0
3
,
n
o
.
0
4
,
p
.
7
,
2
0
1
0
.
[1
3
]
C.
V
.
B
u
n
d
e
rso
n
.
(
1
9
8
6
,
1
0
Oc
t
2
0
1
5
).
T
h
e
Va
li
d
it
y
o
f
T
h
e
He
rr
ma
n
n
Br
a
in
D
o
min
a
n
c
e
In
stru
me
n
t
[
O
n
li
n
e
].
Av
a
il
a
b
le:h
tt
p
:/
/w
ww
.
h
b
d
i.
c
o
m
/u
p
lo
a
d
s/
1
0
0
0
1
7
_
d
isse
rtati
o
n
s/1
0
0
1
8
7
.
p
d
f
[1
4
]
.
S
e
ti
a
w
a
n
a
n
d
.
M
u
tt
a
q
in
“
m
p
le
m
e
n
tatio
n
o
f
K
-
Ne
a
re
st
Ne
ig
h
b
o
rs
F
a
c
e
re
c
o
g
n
it
io
n
o
n
L
o
w
-
p
o
w
e
r
P
r
o
c
e
ss
o
r
”
T
EL
KOM
NIKA
(
T
e
le
c
o
mm
u
n
ica
t
io
n
,
Co
mp
u
ti
n
g
E
lec
tro
n
ics
a
n
d
Co
n
tro
l)
,
v
o
l.
13
,
n
o.
3
,
p
p
.
9
4
9
-
9
5
4
,
2
0
1
5
.
[1
5
]
H.
G
a
o
,
e
t
a
l
.
,
"
A
n
a
l
y
sis
o
f
EE
G
a
c
ti
v
it
y
in
re
sp
o
n
se
to
b
i
n
a
u
ra
l
b
e
a
ts
w
it
h
d
if
fe
re
n
t
f
re
q
u
e
n
c
ies
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Psy
c
h
o
p
h
y
sio
lo
g
y
,
v
o
l.
9
4
,
p
p
.
3
9
9
-
4
0
6
,
1
2
//
2
0
1
4
.
[1
6
]
C.
L
iu
a
n
d
H.
W
e
c
h
sle
r,
"
G
a
b
o
r
fe
a
tu
re
b
a
se
d
c
las
si
f
ica
ti
o
n
u
sin
g
th
e
e
n
h
a
n
c
e
d
f
ish
e
r
li
n
e
a
r
d
isc
rim
i
n
a
n
t
m
o
d
e
l
f
o
r
f
a
c
e
re
c
o
g
n
it
io
n
,
"
Ima
g
e
p
ro
c
e
ss
in
g
,
IEE
E
T
ra
n
s
a
c
ti
o
n
s o
n
,
v
o
l
.
1
1
,
p
p
.
4
6
7
-
4
7
6
,
2
0
0
2
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
K
h
a
iru
l
A
m
r
iz
a
l
Abu
N
a
w
a
s
wa
s
b
o
rn
a
t
A
lo
r
G
a
jah
,
M
e
lak
a
,
o
n
A
u
g
u
st
1
3
,
1
9
9
0
.
He
f
in
ish
e
d
h
is
h
ig
h
sc
h
o
o
l
e
d
u
c
a
ti
o
n
a
t
P
o
li
t
e
k
n
ik
M
e
rli
m
a
u
M
e
la
k
a
in
Dip
lo
m
a
o
f
El
e
c
tro
n
ic
En
g
in
e
e
rin
g
a
t
2
0
1
1
.
He
th
e
n
j
o
in
e
d
U
n
iv
e
rsiti
M
a
la
y
sia
P
a
h
a
n
g
in
S
e
p
tem
b
e
r
2
0
1
2
a
n
d
g
ra
d
u
a
ted
w
it
h
Ba
c
h
e
lo
r
o
f
De
g
re
e
in
El
e
c
tri
c
a
n
d
E
lec
tro
n
ic
i
n
Ju
ly
2
0
1
6
.
He
c
u
rre
n
tl
y
w
o
rk
e
d
in
T
o
sh
ib
a
T
e
c
(M
)
a
t
Jo
h
o
r
b
ra
n
c
h
sin
c
e
2
0
1
6
a
s
S
e
rv
i
c
e
En
g
in
e
e
r
a
n
d
re
sp
o
n
sib
le
to
d
e
v
e
lo
p
g
o
o
d
tec
h
n
ica
l
tec
h
n
iq
u
e
th
a
t
w
il
l
a
ss
ist
in
d
iag
n
o
sin
g
d
if
f
icu
lt
p
r
o
b
lem
s.
L
i
k
e
w
ise
,
h
e
p
r
o
v
id
e
s
q
u
a
li
ty
se
rv
ic
e
a
n
d
su
p
p
o
rt
f
o
r
m
o
st
t
y
p
e
s
o
f
e
q
u
ip
m
e
n
t
w
it
h
m
in
ima
l
a
ss
ist
a
n
c
e
b
a
se
d
o
n
se
rv
ice
r
e
q
u
e
st
b
y
c
u
sto
m
e
rs
a
n
d
a
ss
ist
th
e
f
ield
S
u
p
e
rv
iso
rs t
o
h
a
n
d
le m
a
jo
r
c
o
m
p
lain
ts.
M
a
h
fu
z
a
h
M
u
sta
fa
o
b
tain
e
d
Di
p
lo
m
a
in
El
e
c
tro
n
ics
f
ro
m
Un
iv
e
r
siti
T
e
k
n
o
lo
g
i
M
a
lay
sia
in
1
9
9
8
.
S
h
e
re
c
e
iv
e
d
B
a
c
h
e
lo
r
o
f
En
g
i
n
e
e
rin
g
(Ho
n
s)
in
Co
m
p
u
ter
S
y
ste
m
&
Co
m
m
u
n
ica
ti
o
n
s
f
ro
m
Un
iv
e
rsiti
P
u
tra
M
a
lay
sia
in
2
0
0
2
,
th
e
n
,
s
h
e
re
c
e
iv
e
d
M
a
ste
r
o
f
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
f
ro
m
Un
iv
e
rsiti
T
u
n
Hu
ss
e
in
On
n
M
a
l
a
y
sia
in
2
0
0
4
.
He
r
P
h
il
o
so
p
h
y
Do
c
to
r
w
a
s
re
c
e
i
v
e
d
in
2
0
1
5
f
ro
m
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
M
A
R
A
M
a
l
a
y
sia
in
th
e
f
ield
o
f
Bio
-
sig
n
a
l
E
EG
A
n
a
l
y
sis.
Cu
rre
n
tl
y
sh
e
is
a
S
e
n
io
r
L
e
c
tu
re
r
a
t
F
a
c
u
lt
y
o
f
El
e
c
tri
c
a
l
a
n
d
El
e
c
tro
n
ics
En
g
in
e
e
ri
n
g
,
Un
iv
e
rsiti
M
a
la
y
sia
P
a
h
a
n
g
(UMP
)
,
M
a
lay
sia
.
He
r
c
u
rre
n
t
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
ima
g
e
/sig
n
a
l
p
ro
c
e
ss
in
g
,
b
io
-
sig
n
a
l
a
n
a
ly
sis,
c
o
m
p
u
ter v
isio
n
,
b
io
m
e
d
ica
l
e
n
g
in
e
e
rin
g
a
n
d
a
rti
f
icia
l
in
t
e
ll
ig
e
n
c
e
.
Ro
s
d
iy
a
n
a
S
a
m
a
d
wa
s b
o
rn
i
n
S
e
lan
g
o
r,
M
a
lay
sia
in
1
9
8
0
.
S
h
e
re
c
e
iv
e
d
th
e
BEn
g
.
in
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
f
ro
m
th
e
Ko
lej
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
T
u
n
Hu
ss
e
in
O
n
n
(KU
iT
T
H
O),
Jo
h
o
r,
M
a
lay
sia
in
2
0
0
2
.
I
n
2
0
0
5
sh
e
re
c
e
iv
e
d
M
S
c
.
in
El
e
c
tri
v
a
l
En
g
in
e
e
rin
g
f
ro
m
Un
iv
e
rsiti
S
a
in
s
M
a
la
y
sia
(USM
)
in
P
e
n
a
n
g
,
M
a
lay
sia
.
S
h
e
re
c
e
iv
e
d
P
h
D
d
e
g
re
e
in
E
n
g
in
e
e
rin
g
(In
telli
g
e
n
t
M
e
c
h
a
n
ica
l
S
y
st
e
m
s
En
g
in
e
e
rin
g
)
f
ro
m
K
a
g
a
w
a
Un
iv
e
rsit
y
,
Ka
g
a
w
a
,
Ja
p
a
n
in
2
0
1
2
.
C
u
rre
n
t
ly
sh
e
is
a
S
e
n
io
r
L
e
c
tu
re
r
a
t
F
a
c
u
lt
y
o
f
El
e
c
tri
c
a
l
a
n
d
El
e
c
tro
n
ics
En
g
in
e
e
rin
g
,
U
n
i
v
e
rsiti
M
a
la
y
sia
P
a
h
a
n
g
(UM
P
),
M
a
la
y
sia
.
He
r
c
u
rre
n
t
re
se
a
rc
h
in
tere
sts
in
c
l
u
d
e
c
o
m
p
u
ter
v
isio
n
,
im
a
g
e
p
ro
c
e
ss
in
g
,
p
a
tt
e
rn
re
c
o
g
n
it
io
n
,
b
io
m
e
d
ica
l
e
n
g
in
e
e
rin
g
,
a
rti
f
icia
l
in
telli
g
e
n
c
e
a
n
d
h
u
m
a
n
c
o
m
p
u
ter
in
tera
c
ti
o
n
(HCI).
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t
201
8
:
2
4
9
4
–
2
5
0
2
2502
D
w
i
Peb
r
ia
n
ti
is
a
se
n
io
r
lec
tu
re
r
in
F
a
c
u
lt
y
o
f
El
e
c
tri
c
a
l
&
El
e
c
tro
n
ics
En
g
in
e
e
rin
g
,
Un
iv
e
rsit
y
M
a
la
y
sia
P
a
h
a
n
g
,
UM
P
,
M
a
lay
si
a
sin
c
e
2
0
1
3
.
S
h
e
re
c
e
iv
e
d
Ba
c
h
e
lo
r
o
f
En
g
in
e
e
rin
g
i
n
e
lec
tro
n
ics
e
n
g
in
e
e
rin
g
f
ro
m
Un
iv
e
rsitas
In
d
o
n
e
sia
,
In
d
o
n
e
sia
,
in
2
0
0
1
a
n
d
jo
i
n
e
d
a
n
o
il
g
a
s
c
o
m
p
a
n
y
,
Ca
lt
e
x
P
a
c
if
ic
In
d
o
n
e
sia
i
n
t
h
e
sa
m
e
y
e
a
r.
S
h
e
re
c
e
iv
e
d
M
a
ste
r
o
f
En
g
i
n
e
e
rin
g
f
ro
m
th
e
De
p
a
rt
m
e
n
t
o
f
En
g
in
e
e
rin
g
S
y
n
th
e
sis,
T
h
e
Un
iv
e
rsit
y
o
f
T
o
k
y
o
,
Ja
p
a
n
in
2
0
0
6
.
He
r
P
h
il
o
so
p
h
y
Do
c
to
r
w
a
s
re
c
e
iv
e
d
in
2
0
1
1
f
ro
m
Ch
ib
a
Un
iv
e
rsit
y
in
th
e
f
ield
o
f
A
rti
f
icia
l
S
y
ste
m
S
c
ien
c
e
.
S
in
c
e
th
e
n
,
sh
e
w
a
s
se
rv
in
g
Ch
ib
a
Un
iv
e
rsity
a
s
a
P
o
st
d
o
c
to
ra
l
f
e
ll
o
w
in
th
e
s
a
m
e
f
i
e
ld
.
He
r
m
a
in
w
o
rk
s
a
re
in
c
lu
d
in
g
im
a
g
e
p
ro
c
e
ss
in
g
f
o
r
ro
b
o
t
n
a
v
ig
a
ti
o
n
,
c
o
n
tro
l
th
e
o
ry
fo
r
ro
b
o
t
n
a
v
ig
a
ti
o
n
,
a
u
t
o
m
a
ti
o
n
,
c
o
n
tro
l
sy
ste
m
,
ro
b
o
ti
c
s,
w
e
a
ra
b
l
e
c
o
m
p
u
ter,
a
rti
f
icia
l
in
telli
g
e
n
c
e
,
n
o
n
l
in
e
a
r
sy
ste
m
a
n
d
c
o
n
tr
o
l,
Un
m
a
n
n
e
d
A
e
rial
V
e
h
icle
,
M
o
ti
o
n
&
d
y
n
a
m
ics
c
o
n
tro
l,
e
m
b
e
d
d
e
d
s
y
ste
m
d
e
sig
n
,
M
o
ti
o
n
trac
k
in
g
s
y
ste
m
,
S
w
a
r
m
ro
b
o
t
a
n
d
Op
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
.
No
r
Ru
l
H
a
s
m
a
A
b
d
u
ll
a
h
o
b
tain
e
d
a
Ba
c
h
e
l
o
r
o
f
El
e
c
tri
c
a
l
En
g
i
n
e
e
rin
g
(Ho
n
s)
f
ro
m
Un
iv
e
rsiti
T
e
k
n
o
lo
g
i
M
a
lay
sia
,
M
En
g
in
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
f
ro
m
UiTT
HO
a
n
d
P
h
D
in
El
e
c
tri
c
a
l
En
g
in
e
e
rin
g
f
ro
m
Un
iv
e
r
siti
T
e
k
n
o
lo
g
i
M
A
RA
.
He
r
re
s
e
a
rc
h
i
n
tere
st
in
c
lu
d
e
s
p
o
w
e
r
s
y
ste
m
sta
b
il
it
y
,
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
s,
d
istri
b
u
te
d
g
e
n
e
ra
ti
o
n
,
sw
a
r
m
o
p
ti
m
iza
ti
o
n
a
n
d
m
e
ta
-
h
e
u
risti
c
tec
h
n
iq
u
e
s.
T
o
d
a
te,
s
h
e
is
c
u
rre
n
t
ly
a
s
e
n
io
r
lec
tu
re
r
a
t
Un
iv
e
rsiti
M
a
la
y
sia
P
a
h
a
n
g
,
M
a
lay
sia
.
Evaluation Warning : The document was created with Spire.PDF for Python.