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o
f
th
e
in
d
u
ctio
n
m
o
to
r
.
A
s
tu
d
y
h
as
b
ee
n
co
n
d
u
cted
t
o
co
m
p
ar
e
th
e
MCS
A
m
eth
o
d
an
d
v
ib
r
atio
n
m
et
h
o
d
[
1
2
]
.
T
h
is
s
tu
d
y
s
h
o
ws
th
at
th
e
MCS
A
'
s
ab
ilit
y
an
d
v
ib
r
ati
o
n
m
et
h
o
d
to
d
etec
t
m
is
alig
n
m
en
t
p
r
o
d
u
ce
s
im
ilar
cu
r
v
e
p
atter
n
s
.
Ho
wev
er
,
th
is
s
tu
d
y
h
as n
o
t a
p
p
lied
a
d
etec
tio
n
alg
o
r
ith
m
.
T
h
is
r
esear
ch
c
lass
if
y
p
r
o
ce
s
s
o
f
m
is
alig
n
m
en
t
an
d
lev
el
o
f
m
is
alig
n
m
en
t
in
in
d
u
ctio
n
u
s
i
n
g
m
o
th
er
wav
elet,
in
clu
d
in
g
Dau
b
ec
h
i
s
,
C
o
if
let
an
d
Sy
m
let
d
is
cr
e
te
wav
elet
tr
an
s
f
o
r
m
(
DW
T
)
an
d
Dis
cr
im
in
an
t
An
aly
s
is
.
I
n
d
u
ctio
n
m
o
to
r
s
t
h
at
ar
e
o
p
er
ate
d
a
n
d
e
n
g
in
ee
r
e
d
s
o
th
at
u
n
d
er
th
r
ee
co
n
d
itio
n
o
f
o
p
er
atio
n
.
An
d
th
en
,
Dau
b
ec
h
is
,
C
o
if
let
an
d
Sy
m
let
DW
T
f
r
o
m
lev
el
o
f
1
st
to
3
rd
is
ap
p
lied
to
g
e
n
er
ate
v
ib
r
atio
n
s
ig
n
al
o
f
m
o
to
r
in
d
etil
s
ig
n
al
o
r
h
ig
h
f
r
eq
u
e
n
cy
s
ig
n
al.
T
h
e
n
,
Featu
r
e
ex
tr
ac
tio
n
,
in
clu
d
in
g
r
an
g
e
,
s
u
m
,
an
d
en
e
r
g
y
,
g
en
er
ated
f
r
o
m
d
etil
s
ig
n
als
is
co
llected
.
Qu
ad
r
atic
an
d
lin
ea
r
d
is
cr
im
in
an
t
a
n
aly
s
is
(
QDA
an
d
L
DA)
v
er
if
ies
an
d
class
if
ies m
o
to
r
d
ata
in
to
t
h
r
ee
co
n
d
itio
n
s
o
f
m
o
to
r
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
Gen
er
al
d
escr
ip
tio
n
o
f
th
e
m
eth
o
d
t
o
b
e
wo
r
k
ed
is
s
h
o
wn
in
Fig
u
r
e
1
.
T
h
e
v
i
b
r
atio
n
s
ig
n
al
f
r
o
m
th
e
in
d
u
ctio
n
m
o
to
r
will
b
e
tak
en
b
y
p
iezo
elec
tr
ic
s
en
s
o
r
.
An
d
th
en
,
it
will
b
e
s
to
r
ed
o
n
th
e
SD
C
ar
d
b
y
th
e
m
icr
o
c
o
n
tr
o
ller
.
Fu
r
t
h
er
m
o
r
e,
v
ib
r
atio
n
d
ata
co
n
s
is
ti
n
g
o
f
m
o
to
r
v
ib
r
atio
n
d
ata
i
n
n
o
r
m
al
o
p
er
atio
n
,
m
is
alig
n
m
en
t
o
f
1
m
m
an
d
m
is
alig
n
m
en
t
o
f
1
.
5
m
m
will
b
e
p
r
o
ce
s
s
ed
u
s
in
g
Dau
b
ec
h
is
,
Sy
m
let
an
d
C
o
if
let
DW
T
in
lev
el
o
f
1
st
to
3
rd
.
D
W
T
r
esu
lts
tak
en
f
o
r
f
u
r
th
er
p
r
o
ce
s
s
in
g
ar
e
h
ig
h
f
r
e
q
u
en
c
y
s
ig
n
als.
T
h
e
h
ig
h
f
r
eq
u
e
n
cy
s
ig
n
al
is
p
r
o
ce
s
s
ed
to
tak
e
th
e
r
an
g
e,
s
u
m
a
n
d
en
e
r
g
y
v
ar
ia
b
les
to
b
e
ap
p
lied
as
in
p
u
t
f
o
r
QDA
an
d
LD
A.
T
h
e
o
u
tp
u
t
o
f
QDA
an
d
L
DA
is
m
o
to
r
co
n
d
itio
n
u
n
d
er
n
o
r
m
al
o
p
e
r
atio
n
,
m
is
alig
n
m
en
t
o
f
1
m
m
a
n
d
m
is
alig
n
m
en
t o
f
1
.
5
m
m
.
Fig
u
r
e
1
.
Misalig
n
m
en
t c
lass
if
icatio
n
p
r
o
ce
s
s
in
in
d
u
ctio
n
m
o
to
r
Evaluation Warning : The document was created with Spire.PDF for Python.
T
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L
KOM
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elec
o
m
m
u
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ifica
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(
P.
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.
S
a
p
u
tr
a
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963
2
.
1
.
E
x
perim
ent
a
l set
up
a
nd
s
t
ud
y
ca
s
e
L
ab
o
r
ato
r
y
ex
p
er
im
en
tal
s
etu
p
is
d
o
n
e
t
o
s
im
u
late
m
o
t
o
r
co
n
d
itio
n
in
n
o
r
m
al
o
p
e
r
atio
n
,
m
is
alig
n
m
en
t
o
f
1
m
m
an
d
m
is
alig
n
m
en
t
o
f
1
.
5
m
m
.
E
x
p
e
r
im
en
tal
s
ch
em
e
is
s
h
o
wn
in
Fig
u
r
es
2
(
a)
an
d
(
b
)
.
I
n
d
u
ctio
n
m
o
to
r
th
at
h
as
0
.
5
H
P
p
o
wer
,
with
a
s
p
ee
d
o
f
1
4
0
0
R
PM,
2
2
0
V
o
lt
v
o
ltag
e
an
d
5
0
Hz
wo
r
k
in
g
f
r
e
q
u
en
cy
p
air
e
d
with
a
g
en
er
ato
r
as a
m
ec
h
a
n
ical
lo
ad
.
I
n
th
e
in
s
tallatio
n
,
th
e
g
e
n
er
ato
r
is
in
s
talled
in
a
n
o
r
m
al
alig
n
m
en
t c
o
n
d
itio
n
o
r
in
th
e
d
ir
ec
tio
n
o
f
th
e
m
o
to
r
,
1
m
m
s
h
if
ted
an
d
1
.
5
m
m
s
h
if
ted
.
An
d
th
en
s
en
s
o
r
o
f
p
ie
zo
elec
tr
ic
is
ap
p
lied
to
m
ea
s
u
r
e
v
ib
r
atio
n
v
al
u
e,
th
en
it is
s
av
ed
to
s
to
r
ag
e
d
ev
ice
b
y
u
s
in
g
m
icr
o
c
o
n
tr
o
ller
.
(
a)
(
b
)
Fig
u
r
e
2
.
(
a
)
Gen
er
at
o
r
an
d
m
o
to
r
s
ch
em
e,
(
b
)
C
o
llect
o
f
m
o
to
r
v
ib
r
atio
n
d
ata
c
o
n
d
itio
n
2
.
2
.
Dis
cr
et
e
wa
v
ele
t
t
ra
ns
f
o
rm
Dis
cr
ete
wav
elet
tr
an
s
f
o
r
m
(
DW
T
)
is
p
r
esen
ted
in
t
h
is
r
esear
ch
b
ec
au
s
e
it
h
as si
m
p
le
ca
lcu
latio
n
an
d
r
elativ
ely
s
m
all
tim
e
in
ter
v
al
c
o
n
tin
u
o
u
s
wav
elet
tr
an
s
f
o
r
m
.
Oth
er
n
am
e
o
f
s
ca
lin
g
/d
ilatatio
n
p
a
r
am
eter
is
l
o
w
p
ass
f
ilter
(
L
PF
)
o
r
it a
ls
o
ca
n
b
e
ca
lled
as f
ath
er
wav
elet.
an
d
tr
an
s
latio
n
p
a
r
am
eter
is
also
ca
lled
as h
ig
h
p
ass
f
ilter
(
HPF)
o
r
m
o
th
er
wav
elet
[
1
3
-
1
5
]
.
W
e
will
u
s
e
b
o
th
o
f
t
h
em
to
d
o
wav
elet
tr
an
s
f
o
r
m
a
n
d
in
v
er
s
e
wav
elet
tr
an
s
f
o
r
m
.
L
PF
an
d
HPF
f
ilte
r
with
d
if
f
er
e
n
t
cu
t
o
f
f
f
r
eq
u
e
n
cy
is
u
s
ed
to
tr
an
s
f
o
r
m
s
ig
n
al.
Hig
h
f
r
eq
u
en
cy
s
ig
n
al
o
r
d
etail
s
ig
n
al
(
cD)
is
o
u
tp
u
t
f
r
o
m
HPF
an
d
l
o
w
f
r
eq
u
en
cy
s
ig
n
al
o
r
ap
p
r
o
x
im
ati
o
n
s
ig
n
al
(
cA
)
is
o
u
t
p
u
t
f
r
o
m
L
PF
[
1
6
]
.
T
h
e
r
elatio
n
s
h
ip
b
etwe
en
L
PF
/f
ath
er
wav
ele
t
an
d
HPF/
m
o
th
er
wav
elet
ca
n
b
e
d
escr
ib
ed
as
in
th
e
f
o
llo
win
g
(
1
-
3)
:
,
=
2
/
2
Φ
(
2
−
)
,
,
)
(
1
)
(
)
=
(
2
)
−
(
2
−
1
)
(
2
)
with
Ψ
(
t)
is
th
e
m
o
th
e
r
wav
e
let
an
d
Φ
(
2
t
)
is
th
e
f
ath
er
wa
v
elet.
T
h
e
f
u
n
ctio
n
o
f
t
h
e
eq
u
atio
n
o
f
th
e
m
o
th
er
wav
elet
is
(
3
)
:
,
(
)
=
2
/
2
(
2
−
)
,
,
(
3
)
b
ased
o
n
(
1
)
a
n
d
(
3
)
th
e
m
o
th
e
r
wav
elet
an
d
e
q
u
atio
n
(
1
)
.
Fu
ll e
q
u
atio
n
o
f
DW
T
is
ex
p
lain
ed
as (
4
)
.
(
)
=
0
,
0
(
)
+
∑
∑
,
Ψ
,
(
)
2
−
1
=
0
−
1
=
0
)
(
4
)
T
h
e
d
ata
p
r
o
ce
s
s
in
g
p
r
o
ce
s
s
s
tar
ts
b
y
p
ass
in
g
v
ib
r
atio
n
s
ig
n
als
in
HPF
an
d
L
PF
f
ilter
s
.
T
h
e
p
r
o
ce
s
s
will
p
r
o
d
u
ce
HF
s
ig
n
al
(
cD)
an
d
L
F
s
ig
n
al
(
cA)
.
B
o
th
o
f
t
h
em
h
a
v
e
th
e
am
o
u
n
t
o
f
d
ata
as
m
u
ch
as
h
al
f
o
f
th
e
o
r
ig
in
al
d
ata/in
itial
d
ata
.
T
h
is
p
r
o
ce
s
s
is
n
am
ed
th
e
1
s
t
le
v
el
d
ec
o
m
p
o
s
itio
n
p
r
o
ce
s
s
.
Fu
r
th
er
m
o
r
e
,
L
F
s
ig
n
al
(
cA)
will
b
e
p
ass
ed
ag
ain
i
n
HPF
an
d
L
PF
f
ilter
s
an
d
will
p
r
o
d
u
ce
HF
s
ig
n
al
(
cD)
a
n
d
L
F
s
ig
n
al
(
cA)
at
th
e
n
ex
t
lev
el.
T
h
is
lev
el
i
s
ca
ll
ed
th
e
2
n
d
lev
el
d
ec
o
m
p
o
s
itio
n
p
r
o
ce
s
s
.
T
h
is
p
r
o
ce
s
s
will
co
n
tin
u
e
to
th
e
d
esire
d
d
ec
o
m
p
o
s
itio
n
lev
el
[
1
7
,
1
8
]
.
2
.
3
.
F
e
a
t
ure
ex
t
r
a
ct
io
n
Af
ter
g
ettin
g
h
ig
h
f
r
eq
u
en
cy
s
ig
n
al
o
r
Detil
s
ig
n
al
(
cD)
f
r
o
m
DW
T
,
th
en
we
will
ca
lcu
late
t
h
e
f
ea
tu
r
e
ex
tr
ac
tio
n
f
r
o
m
th
e
HF
s
ig
n
al
(
cD)
.
T
h
e
HF
s
ig
n
al
(
cD
)
p
r
o
ce
s
s
ed
is
lev
el
o
f
1
s
t
to
3
r
d
.
T
h
en
,
f
ea
tu
r
e
ex
tr
ac
tio
n
s
u
ch
as
s
u
m
,
r
a
n
g
e,
an
d
en
er
g
y
,
is
g
e
n
er
ated
f
r
o
m
th
e
De
til/
HF
s
ig
n
als.
R
an
g
e
o
f
s
ig
n
al
is
th
e
d
if
f
er
e
n
ce
b
etwe
en
th
e
m
ax
im
u
m
an
d
m
i
n
im
u
m
v
al
u
es.
T
h
is
ca
n
b
e
d
e
s
cr
ib
ed
as (
5
)
.
R
an
g
e
=
Ma
x
o
f
s
ig
n
al
–
m
i
n
o
f
s
ig
n
al
(
5
)
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.
18
,
No
.
2
,
Ap
r
il 2
0
2
0
:
9
6
1
-
969
964
T
h
en
,
s
u
m
o
f
s
ig
n
al
is
ab
s
o
lu
t
e
v
alu
e
o
f
s
ig
n
al
an
d
th
e
n
s
u
m
m
ed
in
a
ce
r
tain
tim
e
s
p
an
.
T
h
is
ca
n
b
e
d
escr
ib
ed
as (
6
)
.
S
u
m =
1
|
(
)
|
nk
n
dn
=
=
(
6
)
W
h
er
ea
s
,
th
e
s
ig
n
al
en
er
g
y
,
e,
is
th
e
s
u
m
o
f
th
e
s
q
u
ar
es
o
f
ea
ch
s
ig
n
al
co
m
p
o
n
en
t.
T
h
is
ca
n
b
e
wr
itten
as (
7
)
[
1
9
-
2
2
]
.
e
=
2
1
(
(
)
)
nk
n
dn
=
=
(
7
)
T
h
r
ee
o
f
th
ese
th
r
ee
s
ig
n
al
ch
ar
ac
ter
s
will
b
e
p
r
o
ce
s
s
ed
as
in
p
u
t
in
QDA
an
d
L
DA
s
o
th
at
th
e
co
n
d
itio
n
o
f
th
e
m
o
to
r
ca
n
b
e
k
n
o
w
n
an
d
th
e
lev
el
o
f
d
am
ag
e
c
an
b
e
d
et
er
m
in
ed
.
2
.
4
.
Q
ua
dra
t
ic
dis
cr
ina
nt
a
na
ly
s
is
QDA
is
a
s
tati
s
tical
ap
p
r
o
ac
h
to
class
if
y
an
a
m
o
u
n
t
o
f
d
ata
in
to
s
o
m
e
clu
s
ter
s
b
ased
o
n
s
o
m
e
ch
ar
ac
ter
is
tics
.
ea
ch
o
f
d
ata
in
o
n
e
o
f
g
r
o
u
p
will
n
o
t
b
e
m
e
m
b
er
i
n
o
t
h
er
g
r
o
u
p
[
2
3
]
.
T
h
i
s
is
alik
e
to
m
u
ltip
le
lin
ea
r
r
eg
r
ess
io
n
.
T
h
e
d
i
v
er
g
en
ce
lies
in
th
e
ty
p
e
o
f
d
at
a
in
t
h
e
d
e
p
en
d
e
n
t
a
n
d
i
n
d
e
p
en
d
en
t
v
ar
ia
b
les.
T
h
e
m
u
ltip
le
r
eg
r
ess
io
n
is
u
tili
ze
d
in
ca
s
e
s
ca
le
o
f
m
etr
ic
is
u
s
ed
in
d
ep
e
n
d
en
t
v
a
r
iab
le
an
d
eith
er
n
o
n
-
m
etr
ic
o
r
m
etr
ic
s
ca
le
is
u
s
ed
in
in
d
ep
en
d
en
t
v
ar
iab
le.
W
h
ile,
d
is
cr
im
in
an
t
an
aly
s
is
is
u
tili
ze
d
in
ca
s
e
d
ep
en
d
e
n
t
v
ar
iab
le
is
ca
teg
o
r
ical
an
d
th
e
in
d
ep
en
d
en
t v
ar
ia
b
le
u
tili
ze
a
m
etr
ic
s
ca
le.
Mo
d
el
o
f
d
is
cr
im
in
an
t
an
al
y
s
is
is
an
f
o
r
m
u
la
th
at
in
d
icate
s
a
lin
ea
r
o
r
q
u
a
d
r
atic
co
m
p
o
s
ite
o
f
s
o
m
e
in
d
ep
en
d
en
t v
ar
ia
b
les,
n
am
ely
:
D
=
b
0
+
b
1
X
1
+
b
2
X
2
+
b
3
X
3
+
…
…
+
b
k
X
k
(
8
)
f
r
o
m
(
8
)
,
it
ca
n
b
e
e
x
p
lain
ed
th
at
D
is
th
e
d
is
cr
im
in
an
t
v
alu
e,
b
is
co
e
f
f
icien
t
o
f
d
is
cr
im
in
atio
n
a
n
d
X
is
v
a
r
iab
le
o
f
in
d
ep
e
n
d
en
t.
Valu
e
o
f
D
is
u
n
iu
e,
s
o
th
at
ac
co
r
d
in
g
o
n
th
e
v
alu
e
o
f
D,
p
r
ed
ictio
n
o
f
m
em
b
er
v
alu
e
ca
n
b
e
d
eter
m
i
n
e
d
.
I
n
QDA,
m
er
g
er
o
f
p
r
ed
icto
r
v
ar
iab
les
p
r
o
d
u
ce
s
zo
n
e
s
h
ap
e
d
g
r
a
p
h
o
f
q
u
ad
r
atic
f
u
n
ctio
n
s
o
th
at
it
is
ex
p
ec
ted
to
p
r
o
d
u
ce
r
esu
lt
m
o
r
e
p
r
ec
is
e
an
d
h
ig
h
e
r
ac
cu
r
ac
y
.
Nev
er
th
eles,
an
in
cr
ea
s
e
in
th
e
n
u
m
b
er
o
f
p
r
ed
icto
r
s
will m
ak
e
th
is
an
al
y
s
is
r
u
n
in
to
o
v
e
r
f
its
(
v
ar
ia
b
ilit
y
is
to
o
lar
g
e)
[
2
4
,
2
5
]
.
Fo
r
m
u
la
o
f
QDA
s
co
r
e
to
class
if
y
d
ata
in
to
m
em
b
er
o
f
o
n
e
o
f
g
r
o
u
p
s
is
in
(
9
)
as f
o
llo
ws:
(
)
(
)
i
i
i
T
i
i
Q
i
p
x
x
S
x
x
S
x
d
ln
2
1
ln
2
1
)
(
ˆ
1
+
−
−
−
−
=
−
(
9
)
with
d
is
s
co
r
e
v
al
u
e
o
f
d
is
c
r
im
in
an
t,
x
is
d
ata,
Si
is
th
e
co
v
ar
ian
ce
m
atr
ix
a
n
d
p
i
is
p
r
io
r
p
r
o
b
ab
ilit
y
o
f
th
e
ith
p
o
p
u
latio
n
.
3.
RE
SU
L
T
S
A
ND
AN
AL
Y
SI
S
T
h
e
m
o
to
r
is
tak
ed
ac
tio
n
in
s
o
m
e
p
er
io
d
o
f
tim
e
in
th
r
ee
s
tates,
in
clu
d
in
g
n
o
r
m
al
co
n
d
i
tio
n
,
1
m
m
m
is
alig
n
m
en
t
an
d
1
.
5
m
m
m
is
alig
n
m
en
t.
T
h
e
o
u
tp
u
t o
f
v
ib
r
atio
n
s
ig
n
al
is
s
en
d
ed
to
d
ata
s
to
r
ag
e
b
y
v
ib
r
atio
n
s
en
s
o
r
.
T
h
en
,
b
y
u
s
in
g
m
atlab
s
o
f
twar
e,
v
ib
r
atio
n
d
ata
o
n
d
ata
s
to
r
ag
e
is
p
r
o
ce
s
s
ed
.
T
h
e
o
u
tp
u
t
o
f
v
ib
r
atio
n
s
ig
n
al
o
f
m
o
t
o
r
is
s
h
o
wn
in
th
e
Fig
u
r
e
3.
W
e
ca
n
s
ee
th
at
m
o
to
r
s
ig
n
als
in
n
o
r
m
al
co
n
d
itio
n
s
h
av
e
ten
u
o
u
s
an
d
lo
w
v
alu
e
d
ata
v
alu
es.
W
h
en
t
h
er
e
is
a
1
m
m
o
f
m
is
alig
n
m
e
n
t,
th
e
g
r
a
p
h
g
ets
tig
h
ter
an
d
s
o
m
etim
es
th
er
e
ar
e
s
p
ik
es.
Fu
r
th
er
m
o
r
e
,
1
.
5
m
m
o
f
m
is
alig
n
m
en
t
p
r
o
d
u
ce
s
a
tig
h
t g
r
a
p
h
an
d
a
h
i
g
h
v
al
u
e.
3
.
1
.
Dis
cr
et
e
wa
v
ele
t
t
ra
ns
f
o
rm
T
h
e
n
ex
t,
v
ib
r
atio
n
s
ig
n
al
o
f
i
n
d
u
ctio
n
m
o
to
r
is
f
ilter
ed
u
s
in
g
Dau
b
ec
h
is
,
C
o
if
let
an
d
Sy
m
let
DW
T
.
T
h
e
o
u
tp
u
t
o
f
DW
T
th
at
is
u
s
e
d
in
th
e
n
ex
t
p
r
o
ce
s
s
is
H
F
s
ig
n
al
(
cD)
at
lev
el
o
f
1
st
to
3
rd
.
P
r
ed
icted
th
at
at
h
ig
h
lev
el,
id
etif
icatio
n
is
m
o
r
e
ac
c
u
r
at
e.
T
r
a
n
s
f
o
r
m
e
d
v
ib
r
atio
n
s
ig
n
al
is
s
h
o
wn
in
Fi
g
u
r
es
4
(
a
-
c)
.
T
h
e
s
am
p
le
o
f
g
r
ap
h
ic
in
Fig
u
r
e
4
is
th
e
o
u
tp
u
t
o
f
Dau
b
ec
h
is
1
DW
T
at
1
st
to
3
rd
lev
el.
T
h
e
m
o
th
er
wav
elet
ap
p
lied
is
Dau
b
ec
h
is
1
-
5
,
C
o
if
let
1
-
5
an
d
Sy
m
let
1
-
5
.
I
t
m
ea
n
s
th
at
v
ib
atio
n
s
ig
n
al
is
f
ilter
ed
b
y
Da
u
b
ec
h
is
1
-
5
,
C
o
if
let
1
-
5
an
d
Sy
m
let
1
-
5
as
m
an
y
as
3
lev
els,
n
am
ely
at
1
st
-
3
rd
lev
el.
T
h
e
am
o
u
n
t
o
f
d
ata
g
en
er
ated
an
d
u
s
ed
is
Evaluation Warning : The document was created with Spire.PDF for Python.
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o
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u
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a
p
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r
ed
u
ce
d
b
y
h
alf
o
f
th
e
in
itial
d
ata
at
ea
ch
le
v
el.
B
ec
au
s
e
th
ese
d
ata
ar
e
d
i
v
id
ed
i
n
to
HF
s
ig
n
al
an
d
L
F
s
ig
n
al.
An
d
at
th
e
n
ex
t
lev
el,
L
F
s
ig
n
al
is
u
s
ed
as
in
p
u
t
an
d
p
r
o
d
u
ce
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HF
s
ig
n
al
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d
L
F
s
ig
n
al
ag
ain
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T
h
e
r
esu
ltin
g
d
ata
s
till
lo
o
k
s
lik
e
r
an
d
o
m
.
S
o
,
th
is
d
ata
will th
en
b
e
r
etr
iev
ed
its
ch
ar
ac
ter
is
tics
f
o
r
p
r
o
ce
s
s
in
g
.
3.
2
.
F
e
a
t
ure
ex
t
r
a
ct
io
n
HF
s
ig
n
als
at
1
s
t
to
3
rd
lev
el
r
esu
lted
f
r
o
m
th
e
DW
T
p
r
o
ce
s
s
is
ex
tr
ac
ted
.
C
h
ar
ac
ter
is
tics
r
esu
lted
ar
e
s
u
m
,
r
an
g
e,
an
d
en
er
g
y
o
f
s
ig
n
al.
T
h
e
o
u
tp
u
t o
f
th
e
s
ig
n
al
f
ea
tu
r
es
is
s
h
o
wn
in
T
ab
le
s
1
-
3.
No
r
m
ally
,
a
m
o
to
r
th
at
ex
p
er
ien
ce
s
a
m
is
alig
n
m
e
n
t
will
p
r
o
d
u
ce
a
h
ig
h
er
v
ib
r
ati
o
n
f
r
e
q
u
en
c
y
.
So
th
at
if
it
is
p
r
o
ce
s
s
ed
u
s
in
g
DW
T
an
d
its
ch
a
r
ac
ter
is
tics
ar
e
tak
en
,
th
e
v
alu
e
o
f
its
ch
ar
ac
te
r
is
tics
will
b
e
d
if
f
er
en
t
f
r
o
m
t
h
e
ch
ar
ac
ter
is
tics
o
f
a
n
o
r
m
al
m
o
to
r
.
T
h
is
is
s
h
o
wn
in
T
ab
le
1
Da
u
b
ec
h
is
DW
T
at
1
s
t
lev
el.
T
h
e
v
alu
e
o
f
s
u
m
,
r
an
g
e
a
n
d
e
n
er
g
y
in
cr
ea
s
es
s
ig
n
if
ican
tly
f
r
o
m
n
o
r
m
al
m
o
t
o
r
u
n
til
1
.
5
m
m
m
is
alig
n
m
en
t
m
o
t
o
r
.
I
t’
s
s
am
e
f
o
r
th
e
o
th
er
lev
el
an
d
f
o
r
o
th
er
k
in
d
o
f
DW
T
in
T
ab
l
e
2
an
d
T
ab
le
3
.
Fig
u
r
e
3
.
Vib
r
ati
o
n
s
ig
n
al
o
f
i
n
d
u
ctio
n
m
o
to
r
T
ab
le
1
.
Featu
r
e
e
x
tr
ac
tio
n
o
f
Dau
b
ec
h
is
1
d
is
cr
ete
wav
elet
t
r
an
s
f
o
r
m
1
s
t
Le
v
e
l
2
nd
Le
v
e
l
3
rd
Le
v
e
l
S
u
m
R
a
n
g
e
En
e
r
g
y
S
u
m
R
a
n
g
e
En
e
r
g
y
S
u
m
R
a
n
g
e
En
e
r
g
y
N
o
r
mal
0
.
1
7
3
9
0
.
0
1
8
3
0
.
0
0
1
6
0
.
1
1
0
0
0
.
0
1
2
9
0
.
0
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r
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elet
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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.
18
,
No
.
2
,
Ap
r
il 2
0
2
0
:
9
6
1
-
969
966
(
a)
(
b
)
(
c)
Fig
u
r
e
4
.
Dau
b
ec
h
is
1
DW
T
(
a)
th
e
f
ir
s
t le
v
el
(
b
)
s
ec
o
n
d
lev
el
(
c)
th
ir
d
le
v
el
3
.
3
.
Dis
cr
im
ina
nt
a
na
ly
s
is
QDA
u
s
es
1
2
t
r
ain
in
g
d
ata
o
n
ea
ch
n
o
r
m
al
m
o
to
r
,
1
m
m
m
is
alig
n
m
en
t
an
d
1
.
5
m
m
m
i
s
alig
n
m
en
t.
So
all
tr
ain
in
g
d
ata
am
o
u
n
te
d
to
3
6
d
ata.
Fu
r
th
er
m
o
r
e,
f
o
r
e
ac
h
n
o
r
m
al
m
o
to
r
co
n
d
itio
n
,
1
m
m
m
is
alig
n
m
en
t
an
d
1
.
5
m
m
m
is
alig
n
m
e
n
t
will
b
e
tak
en
8
d
ata
u
s
ed
as
t
est
d
ata.
So
all
test
d
ata
am
o
u
n
ted
to
2
4
d
ata.
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
V
a
r
io
u
s
a
n
d
m
u
ltil
ev
el
o
f wa
ve
let
tr
a
s
n
fo
r
m
fo
r
cla
s
s
ifica
tio
n
mis
a
lig
n
men
t o
n
…
(
P.
P.
S
.
S
a
p
u
tr
a
l)
967
As
a
co
m
p
ar
is
o
n
i
n
m
ea
s
u
r
in
g
th
e
ac
cu
r
ac
y
o
f
QDA,
L
D
A
is
also
u
s
ed
in
p
r
o
ce
s
s
in
g
t
h
e
v
ib
r
atio
n
d
ata
o
f
th
is
m
o
to
r
.
QDA
a
n
d
L
DA
p
r
o
ce
s
s
in
g
is
d
o
n
e
u
s
in
g
m
atlab
s
o
f
twar
e.
QDA
an
d
L
DA
o
u
tp
u
t
ar
e
s
h
o
wn
in
T
ab
le
s
4
-
6.
T
ab
le
4
.
C
la
s
s
if
icatio
n
o
u
tp
u
t
s
o
f
Dau
b
ec
h
is
(
Db
)
DW
T
1
s
t
Le
v
e
l
2
nd
Le
v
e
l
3
rd
Le
v
e
l
LD
A
(
%)
Q
D
A
(
%)
LD
A
(
%)
Q
D
A
(
%)
LD
A
(
%)
Q
D
A
(
%)
Db
1
Er
r
o
r
0
.
0
0
0
4
.
1
6
7
1
2
.
5
0
0
8
.
3
3
3
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.
3
3
3
8
.
3
3
3
Db
2
Er
r
o
r
8
.
3
3
3
8
.
3
3
3
2
0
.
8
3
3
2
0
.
8
3
3
3
3
.
3
3
3
2
0
.
8
3
3
Db
3
Er
r
o
r
0
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0
0
0
0
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0
0
0
8
.
3
3
3
8
.
3
3
3
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9
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6
7
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.
3
3
3
Db
4
Er
r
o
r
4
.
1
6
7
0
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0
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4
.
1
6
7
0
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0
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0
8
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3
3
3
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3
3
3
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5
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r
o
r
1
2
.
5
0
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2
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5
0
0
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3
3
3
1
2
.
5
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0
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2
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5
0
0
T
ab
le
5
.
C
la
s
s
if
icatio
n
o
u
tp
u
t
s
o
f
C
o
if
let
DW
T
1
s
t
Le
v
e
l
2
nd
Le
v
e
l
3
rd
Le
v
e
l
LD
A
(
%)
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(
%)
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(
%)
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(
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(
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(
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o
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f
l
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t
1
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r
o
r
4
.
1
6
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.
1
6
7
8
.
3
3
3
4
.
1
6
7
2
5
.
0
0
0
1
6
.
6
6
7
C
o
i
f
l
e
t
2
Er
r
o
r
4
.
1
6
7
4
.
1
6
7
8
.
3
3
3
4
.
1
6
7
2
0
.
8
3
3
3
3
.
3
3
3
C
o
i
f
l
e
t
3
Er
r
o
r
4
.
1
6
7
4
.
1
6
7
8
.
3
3
3
0
.
0
0
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2
5
.
0
0
0
2
9
.
1
6
7
C
o
i
f
l
e
t
4
Er
r
o
r
4
.
1
6
7
4
.
1
6
7
4
.
1
6
7
8
.
3
3
3
2
5
.
0
0
0
3
3
.
3
3
3
C
o
i
f
l
e
t
5
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r
o
r
0
.
0
0
0
4
.
1
6
7
4
.
1
6
7
0
.
0
0
0
2
5
.
0
0
0
2
5
.
0
0
0
T
ab
le
6
.
C
la
s
s
if
icatio
n
o
u
tp
u
t
s
o
f
Sy
m
let
DW
T
1
s
t
Le
v
e
l
2
nd
Le
v
e
l
3
rd
Le
v
e
l
LD
A
(
%)
Q
D
A
(
%)
LD
A
(
%)
Q
D
A
(
%)
LD
A
(
%)
Q
D
A
(
%)
S
y
ml
e
t
1
Er
r
o
r
8
.
3
3
3
8
.
3
3
3
0
.
0
0
0
0
.
0
0
0
1
2
.
5
0
0
1
2
.
5
0
0
S
y
ml
e
t
2
Er
r
o
r
4
.
1
6
7
4
.
1
6
7
8
.
3
3
3
1
6
.
6
6
7
1
6
.
6
6
7
1
2
.
5
0
0
S
y
ml
e
t
3
Er
r
o
r
4
.
1
6
7
4
.
1
6
7
8
.
3
3
3
4
.
1
6
7
1
2
.
5
0
0
8
.
3
3
3
S
y
ml
e
t
4
Er
r
o
r
4
.
1
6
7
4
.
1
6
7
4
.
1
6
7
4
.
1
6
7
2
9
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1
6
7
3
7
.
5
0
0
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y
ml
e
t
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Er
r
o
r
4
.
1
6
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.
3
3
3
0
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0
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0
8
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3
3
3
2
9
.
1
6
7
2
9
.
1
6
7
T
h
e
tab
le
o
f
th
e
r
esu
lts
o
f
th
e
r
esear
ch
th
at
h
as
b
ee
n
d
o
n
e,
c
o
n
s
is
ts
o
f
1
5
c
o
n
d
itio
n
s
o
n
ea
ch
m
o
t
h
er
wav
elet.
1
5
co
n
d
itio
n
s
ar
e
d
er
iv
ed
f
r
o
m
v
ar
iatio
n
s
f
r
o
m
ea
ch
m
o
th
er
wav
elet,
n
am
ely
5
ty
p
es
o
f
m
o
t
h
er
wav
elets
m
u
ltip
lied
b
y
th
e
n
u
m
b
er
o
f
le
v
els,
n
am
ely
3
le
v
els
(
1
st
lev
el
t
o
3
rd
lev
el)
.
F
r
o
m
th
e
r
esu
lts
o
f
th
e
r
esear
ch
in
th
e
tab
le
ab
o
v
e,
we
ca
n
s
ee
th
at
th
e
er
r
o
r
s
o
b
tain
ed
f
r
o
m
QDA
an
d
L
D
A
u
s
in
g
Dau
b
ec
h
is
,
C
o
if
let
an
d
Sy
m
let
DW
T
v
ar
y
g
r
ea
tly
.
T
ex
t
with
b
lu
e
b
l
o
ck
s
s
h
o
ws th
at
L
DA
is
m
o
r
e
ac
cu
r
ate
th
an
QDA
an
d
tex
t
with
g
r
ee
n
b
l
o
ck
s
s
h
o
ws
QDA
m
o
r
e
ac
cu
r
ately
th
a
n
L
DA.
W
h
er
ea
s
co
lo
r
less
tex
t
in
d
icate
s
th
at
th
e
er
r
o
r
r
esu
lts
f
r
o
m
L
DA
an
d
QDA
ar
e
th
e
s
am
e.
W
e
ca
n
s
ee
th
at
QDA
is
m
o
r
e
ac
cu
r
ate
in
class
if
y
in
g
m
o
to
r
c
o
n
d
itio
n
s
with
ca
s
es
o
f
m
is
alig
n
m
en
t
b
y
p
r
o
ce
s
s
in
g
d
ata
u
s
in
g
Dau
b
ec
h
is
DW
T
.
B
ased
o
n
T
ab
le
4
,
QDA
is
m
o
r
e
ac
cu
r
ate
th
an
L
DA
in
7
co
n
d
itio
n
s
,
n
am
ely
o
n
Db
4
a
n
d
5
at
1
st
l
ev
el
an
d
2
n
d
lev
el
,
Db
1
at
2
nd
lev
el,
a
n
d
Db
2
an
d
3
at
3
rd
l
ev
el.
An
d
th
e
e
r
r
o
r
r
esu
lts
ar
e
th
e
s
am
e
b
etwe
en
L
DA
an
d
QDA
in
6
c
o
n
d
itio
n
s
.
W
h
er
ea
s
,
1
co
n
d
itio
n
o
f
L
D
A
is
m
o
r
e
ac
cu
r
ate.
Fro
m
T
ab
le
6
,
we
ca
n
s
ee
th
at
L
DA
is
m
o
r
e
ac
cu
r
ate
th
an
QD
A
in
4
co
n
d
itio
n
s
,
n
am
ely
o
n
Sy
m
let
2
at
2
nd
lev
el,
Sy
m
let
4
at
3
rd
le
v
el,
an
d
s
y
m
let
5
at
1
st
lev
el
an
d
2
nd
lev
el.
A
n
d
t
h
e
er
r
o
r
r
esu
lts
ar
e
th
e
s
am
e
b
etwe
en
L
DA
an
d
QDA
in
8
co
n
d
itio
n
s
.
An
d
QDA
is
m
o
r
e
ac
cu
r
ate
in
3
co
n
d
itio
n
s
.
W
h
er
ea
s
,
in
T
ab
le
5
,
th
e
p
r
o
ce
s
s
in
g
o
f
d
ata
u
s
es
C
o
if
let
DW
T
,
th
e
r
esu
lts
o
f
th
e
cl
ass
if
icatio
n
ac
cu
r
ac
y
b
etwe
en
QDA
an
d
L
DA
a
r
e
th
e
s
am
e.
B
u
t a
t th
e
1
st
lev
el,
c
lass
if
icatio
n
er
r
o
r
s
r
esu
lted
ev
en
ly
f
r
o
m
C
o
if
let
1
-
5
ar
e
v
e
r
y
m
in
im
u
m
.
W
h
er
ea
s
,
wh
en
v
iewe
d
f
r
o
m
t
h
e
ac
cu
r
ac
y
o
f
th
e
c
lass
if
icati
o
n
r
esu
lts
,
n
am
ely
th
e
r
esu
lt
o
f
an
er
r
o
r
th
at
r
ea
ch
es
0
%,
p
r
o
ce
s
s
in
g
d
ata
u
s
in
g
Dau
b
ec
h
is
DW
T
is
s
u
p
er
io
r
to
o
th
er
m
o
th
e
r
wav
e
lets
,
wh
ich
r
ea
ch
es
0
%
er
r
o
r
in
5
co
n
d
itio
n
s
.
T
h
e
0
%
er
r
o
r
ca
n
b
e
ac
h
iev
ed
u
s
in
g
th
e
Db
1
at
1
st
lev
el
with
L
D
A,
Db
3
at
1
st
lev
el
with
L
DA
an
d
QDA,
Db
4
an
d
Db
5
at
1
st
lev
el
with
QDA
an
d
Db
4
at
2
n
d
lev
el
with
QDA.
W
h
en
u
s
in
g
C
o
if
let
DW
T
,
0
% e
r
r
o
r
co
n
d
it
io
n
ca
n
b
e
ac
h
iev
ed
o
n
C
o
if
let
1
at
1
st
lev
el
with
L
DA,
an
d
C
o
if
let
3
an
d
co
if
let
5
at
2
nd
lev
el
with
QDA.
Me
an
wh
ile,
th
e
s
y
m
let
DW
T
p
r
o
d
u
ce
s
0
%
er
r
o
r
class
if
icatio
n
o
n
s
y
m
let
1
at
2
nd
lev
el
with
L
DA
an
d
QDA,
an
d
s
y
i
m
let
5
at
2
nd
lev
el
with
L
DA.
I
n
ad
d
itio
n
,
f
r
o
m
T
ab
les
4
-
6
,
we
ca
n
s
ee
th
at
th
e
class
if
icati
o
n
r
esu
lts
with
th
e
m
in
im
u
m
er
r
o
r
v
alu
e
ca
n
b
e
r
ea
ch
ed
at
th
e
1
s
t
le
v
el.
W
h
ile
o
n
th
e
3
rd
lev
el
it
p
r
o
d
u
ce
s
a
lar
g
e
e
n
o
u
g
h
er
r
o
r
.
I
t’
s
th
e
s
am
e
wh
eth
er
th
e
r
esu
lts
ar
e
ac
h
iev
ed
b
y
Da
u
b
ec
h
is
,
Sy
m
let
o
r
C
o
if
let
D
W
T
.
An
d
f
in
ally
,
f
r
o
m
th
e
r
esu
lts
o
f
th
is
r
esear
ch
,
we
f
in
d
th
at
Dau
b
ec
h
is
DW
T
at
1
s
t
lev
el
is
th
e
m
o
s
t
ac
cu
r
ate
d
ata
p
r
o
ce
s
s
in
g
in
th
e
ca
s
e
o
f
m
is
alig
n
m
en
t
o
n
in
d
u
ctio
n
m
o
to
r
c
o
m
p
ar
e
d
to
o
th
er
m
o
t
h
er
wav
elets.
As
well,
QDA
co
m
b
in
ed
with
Dau
b
e
ch
is
DW
T
p
r
o
d
u
ce
s
th
e
lo
west
class
if
icatio
n
er
r
o
r
.
Ho
wev
er
,
th
e
ab
ilit
y
to
C
o
if
l
et
1
-
5
DW
T
at
th
e
1
s
t
lev
el,
u
s
in
g
th
e
m
eth
o
d
o
f
eith
er
L
DA
o
r
QDA
also
p
r
o
d
u
ce
s
a
lo
w
class
if
icatio
n
er
r
o
r
.
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.
18
,
No
.
2
,
Ap
r
il 2
0
2
0
:
9
6
1
-
969
968
4.
CO
NCLU
SI
O
N
T
h
e
f
ailu
r
e
o
f
a
n
in
d
u
ctio
n
m
o
to
r
is
a
p
r
o
b
lem
th
at
g
iv
es
a
h
u
g
e
lo
s
s
in
th
e
i
n
d
u
s
tr
y
.
O
n
e
ty
p
e
o
f
f
ailu
r
e
is
m
is
alig
n
m
en
t
o
n
th
e
in
d
u
ctio
n
m
o
to
r
.
T
h
is
s
tu
d
y
c
lass
if
ies
m
i
s
alig
n
m
en
t
i
n
in
d
u
ctio
n
m
o
to
r
s
u
s
in
g
th
r
ee
ty
p
es o
f
wav
elet
tr
a
n
s
f
o
r
m
s
,
n
am
ely
Dau
b
ec
h
is
,
C
o
if
le
t a
n
d
Sy
m
let
DW
T
an
d
m
u
ltil
ev
el
d
ec
o
m
p
o
s
itio
n
o
f
m
o
th
er
wav
elets,
wh
ich
is
t
h
e
1
s
t
lev
el
to
th
e
3
r
d
lev
el.
T
h
e
r
esu
lt
s
h
o
ws
th
at
th
e
1
s
t
lev
e
l
o
f
DW
T
p
r
o
d
u
ce
s
th
e
h
ig
h
est
class
if
icatio
n
er
r
o
r
.
T
h
e
n
,
th
e
b
est
class
if
icati
o
n
o
r
th
e
m
o
s
t
m
in
im
u
m
cla
s
s
if
icatio
n
er
r
o
r
is
p
r
o
d
u
ce
d
b
y
Dau
b
ec
h
is
DW
T
,
esp
ec
ially
th
o
s
e
co
m
b
in
ed
with
Qu
ad
r
atic
Dis
cr
im
in
an
t
An
aly
s
is
(
QDA)
.
I
t
r
esu
lts
0
-
8
.
3
3
%
er
r
o
r
,
d
ep
en
d
o
n
k
in
d
o
f
Dau
b
ec
h
is
DW
T
u
s
ed
.
Mo
r
e
o
v
er
,
C
o
if
let
1
-
5
DW
T
at
th
e
1
s
t
lev
el
p
r
o
d
u
ce
s
a
m
in
im
u
m
clas
s
if
ic
atio
n
er
r
o
r
ev
en
l
y
.
I
t r
esu
lts
4
.
1
7
% o
f
er
r
o
r
.
Ho
wev
er
,
f
u
r
th
er
r
esear
ch
n
ee
d
s
to
b
e
d
o
n
e,
with
d
if
f
er
e
n
t in
d
u
ctio
n
m
o
to
r
p
o
wer
an
d
m
o
r
e
v
ar
ied
ca
s
es o
f
m
is
alig
n
m
en
t,
as we
ll a
s
m
o
r
e
d
ata
in
o
r
d
er
to
r
ea
ch
m
o
r
e
ac
cu
r
ate
co
n
clu
s
io
n
s
.
T
h
at
is
b
e
ca
u
s
e
t
h
e
r
esu
lts
o
f
th
e
ca
lcif
icatio
n
s
ac
h
iev
ed
in
th
is
s
tu
d
y
ar
e
s
till
v
er
y
v
a
r
ied
.
RE
F
E
R
E
NC
E
S
[1
]
Ch
o
u
ra
sia
,
A.,
S
a
lu
n
k
e
,
S
.
,
&
S
a
x
e
n
a
,
V
.
,
“
Eff
icie
n
c
y
Op
ti
m
i
z
a
ti
o
n
o
f
T
h
re
e
P
h
a
se
In
d
u
c
ti
o
n
M
o
to
r
b
y
S
li
p
Co
m
p
e
n
sa
ti
o
n
:
A
Re
v
iew
,
”
In
t
e
rn
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
E
lec
tro
n
i
c
s
a
n
d
El
e
c
trica
l
En
g
in
e
e
rin
g
,
v
o
l.
1
,
n
o
.
4
,
p
p
.
3
0
8
–
3
1
4
,
2
0
1
3
.
[2
]
Kili
ç
,
Er
d
a
l
&
D
o
g
m
u
s
,
Os
m
a
n
&
G
a
n
i,
Ah
m
e
t
&
S
it
,
S
a
m
i
&
Öz
ç
a
li
k
,
Ha
sa
n
,
“
S
imu
lati
o
n
a
n
d
E
x
p
e
rime
n
tal
S
t
u
d
y
o
f
Ve
c
to
r
Co
n
tr
o
ll
e
d
I
n
d
u
c
ti
o
n
M
o
to
r
Dri
v
e
b
a
se
d
o
n
RBF
NN
-
M
R
AC
Co
n
tro
ll
e
r,
”
In
te
rn
a
ti
o
n
a
l
Ad
v
a
n
c
e
Res
e
a
rc
h
e
s
&
En
g
i
n
e
e
rin
g
C
o
n
g
re
s,
2
0
1
7
.
[3
]
Tu
d
o
ra
c
h
e
T.
,
M
e
lsc
e
sc
u
L.
,
P
e
tr
e
V.,
“
Hig
h
e
fficie
n
c
y
sq
u
irrel
c
a
g
e
in
d
u
c
ti
o
n
m
a
c
h
in
e
s,”
Ren
e
wa
b
le
E
n
e
rg
y
a
n
d
Po
we
r Qu
a
l
it
y
J
o
u
r
n
a
l
,
v
o
l.
1
,
n
o
.
7
,
p
p
.
2
3
9
–
2
4
4
,
2
0
0
9
.
[4
]
Ha
rm
o
u
c
h
e
J.,
De
lp
h
a
C.
,
&
Dia
ll
o
D.,
“
Im
p
ro
v
e
d
fa
u
lt
d
iag
n
o
sis
o
f
b
a
ll
b
e
a
rin
g
s
b
a
se
d
o
n
t
h
e
g
l
o
b
a
l
sp
e
c
tru
m
o
f
v
ib
ra
ti
o
n
si
g
n
a
ls,”
I
EE
E
T
r
a
n
s
a
c
ti
o
n
s
o
n
En
e
rg
y
C
o
n
v
e
rs
io
n
,
v
o
l.
30
,
n
o
.
1
,
p
p
.
3
7
6
–
3
8
3
,
2
0
1
5
.
[5
]
S
.
Ba
rk
e
r,
“
Av
o
id
i
n
g
p
re
m
a
tu
re
b
e
a
rin
g
fa
il
u
re
with
in
v
e
rter
fe
d
in
d
u
c
ti
o
n
m
o
t
o
rs,”
Po
we
r
En
g
i
n
e
e
rin
g
J
o
u
r
n
a
l
,
v
o
l.
1
4
,
n
o
.
4
,
p
p
.
1
8
2
–
1
8
9
,
2
0
0
0
.
[6
]
EP
RI,
“
Im
p
ro
v
e
d
m
o
to
rs f
o
r
u
ti
li
t
y
a
p
p
li
c
a
ti
o
n
s,”
P
u
b
li
c
a
ti
o
n
EL
-
2
6
7
8
-
V1
,
fi
n
a
l
re
p
o
rt,
1
9
8
2
.
[7
]
D.
A.
As
fa
n
i,
P
.
P
.
S
u
r
y
a
S
a
p
u
tra,
I.
M
.
Yu
li
st
y
a
Ne
g
a
ra
,
I.
G
.
N.
S
a
tri
y
a
d
i
He
rn
a
n
d
a
a
n
d
R.
Wah
y
u
d
i,
"
S
imu
lati
o
n
a
n
a
ly
sis
o
n
h
i
g
h
imp
e
d
a
n
c
e
tem
p
o
ra
ry
sh
o
rt
c
ircu
i
t
i
n
in
d
u
c
ti
o
n
m
o
to
r
wi
n
d
in
g
,
"
2
0
1
3
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
QiR,
Yo
g
y
a
k
a
rta,
p
p
.
2
0
2
-
2
0
7
,
2
0
1
3
.
[8
]
Tag
lu
k
,
Æ
.
M
.
E.
,
“
Be
a
rin
g
a
n
d
m
isa
li
g
n
m
e
n
t
fa
u
l
t
d
e
tec
ti
o
n
i
n
i
n
d
u
c
t
io
n
m
o
t
o
rs
b
y
u
sin
g
t
h
e
sp
a
c
e
v
e
c
to
r
a
n
g
u
lar
flu
c
tu
a
ti
o
n
si
g
n
a
l,
”
El
e
c
trica
l
E
n
g
in
e
e
rin
g
,
v
o
l.
8
7
,
n
o
.
4
,
p
p
.
1
9
7
–
2
0
6
,
2
0
0
5
.
[9
]
A.
S
tarr
B.
K.
N.
Ra
o
,
“
C
o
n
d
it
i
o
n
M
o
n
i
to
ri
n
g
a
n
d
Dia
g
n
o
stic
E
n
g
in
e
e
rin
g
M
a
n
a
g
e
m
e
n
t,
”
Pro
c
e
e
d
e
n
g
s
o
f
th
e
1
4
th
In
trn
a
ti
o
n
a
l
Co
n
g
re
ss
,
El
se
v
ier
,
2
0
0
1
.
[1
0
]
Je
e
-
Ho
o
n
Ju
n
g
,
Lee
Jo
n
g
-
Ja
e
,
Bo
n
g
-
Hw
a
n
Kw
o
n
,
“
On
li
n
e
Dia
g
n
o
sis
o
f
In
d
u
c
ti
o
n
M
o
to
rs
Us
in
g
M
CS
A,”
IEE
E
T
ra
n
s.
In
d
.
El
e
c
tro
n
.
,
v
o
l.
53
,
n
o
.
6
,
p
p
.
1
8
4
2
–
1
8
5
2
,
2
0
0
6
.
[1
1
]
G
.
Ac
o
sta
,
C.
Ve
ru
c
c
h
i,
E.
Ce
ls
o
,
“
A
c
u
rre
n
t
m
o
n
it
o
ri
n
g
sy
ste
m
fo
r
d
iag
n
o
sin
g
e
lec
tri
c
a
l
fa
il
u
re
s
i
n
i
n
d
u
c
ti
o
n
m
o
to
rs,”
M
e
c
h
.
S
y
st.
S
i
g
n
a
l
Pr
o
c
e
ss
.
,
v
o
l.
20
,
n
o
.
4
,
p
p
.
9
5
3
–
9
6
5
,
2
0
0
6
.
[1
2
]
R.
Ob
a
id
,
T
.
Ha
b
lete
r,
“
Eff
e
c
t
o
f
Lo
a
d
o
n
De
tec
ti
n
g
M
e
c
h
a
n
ica
l
F
a
u
lt
s
in
S
m
a
ll
I
n
d
u
c
ti
o
n
M
o
to
rs
,
”
Pro
c
e
e
d
in
g
s
o
f
S
y
mp
o
si
u
m
o
n
Dia
g
n
o
stics
fo
r
El
e
c
tric
M
a
c
h
i
n
e
s,
Po
we
r
El
e
c
t
ro
n
ics
a
n
d
Dr
ive
s,
S
DE
M
PE
D
2
0
0
3
,
At
la
n
t
a
,
p
p
.
3
0
7
–
3
1
1
,
2
0
0
3
.
[1
3
]
Dja
m
a
l
E.
C.
,
G
u
stiaw
a
n
D.
P
.
,
&
Dja
jas
a
sm
it
a
D.
,
“
S
ig
n
ifi
c
a
n
t
v
a
r
iab
les
e
x
trac
ti
o
n
o
f
p
o
st
-
str
o
k
e
E
EG
sig
n
a
l
u
si
n
g
wa
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e
let
a
n
d
S
OM
k
o
h
o
n
e
n
,
”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ica
ti
o
n
C
o
mp
u
t
in
g
El
e
c
tro
n
ics
a
n
d
Co
n
tro
l,
v
o
l.
17
,
n
o
.
3
,
p
p
.
1
1
4
9
–
1
1
5
8
,
2
0
1
9
.
[1
4
]
Do
m
y
K.,
e
t.
a
l.
,
“
Wav
e
let
Ba
se
d
F
e
a
tu
re
Ex
t
ra
c
ti
o
n
fo
r
t
h
e
I
n
d
o
n
e
sia
n
CV
S
y
l
lab
les
S
o
u
n
d
,
”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ica
ti
o
n
Co
mp
u
ti
n
g
E
lec
tro
n
ics
a
n
d
C
o
n
tr
o
l
,
v
o
l
.
16
,
n
o
.
3
,
p
p
.
9
2
5
–
9
3
3
,
2
0
1
8
.
[1
5
]
Zh
a
n
g
,
S
.
,
&
Wan
g
,
A.,
“
An
I
m
a
g
e
Co
m
p
re
ss
io
n
M
e
th
o
d
Ba
s
e
d
o
n
Wav
e
let
Tran
sf
o
rm
a
n
d
Ne
u
ra
l
Ne
two
rk
,
”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ic
a
ti
o
n
C
o
mp
u
ti
n
g
El
e
c
tro
n
ics
a
n
d
Co
n
tro
l
,
v
o
l
.
13
,
n
o
.
2
,
p
p
.
5
8
7
-
5
9
6
,
2
0
1
5
.
[1
6
]
Wan
g
,
L.
,
G
u
o
,
H.,
&
Zh
a
n
g
,
S
.
,
“
M
o
t
o
r
F
a
u
lt
Dia
g
n
o
sis
Ba
se
d
o
n
Wav
e
let
Tran
sf
o
rm
,
”
T
EL
KOM
NIK
A
T
e
lec
o
mm
u
n
ica
ti
o
n
Co
mp
u
ti
n
g
E
lec
tro
n
ics
a
n
d
C
o
n
tr
o
l
,
v
o
l
.
11
,
n
o
.
9
,
p
p
.
5
3
3
6
–
5
3
4
3
,
2
0
1
3
.
[1
7
]
Ra
m
a
n
a
D.
V.,
Ba
sk
a
r
S
.
,
“
I
n
c
ip
i
e
n
t
F
a
u
l
t
De
tec
ti
o
n
o
f
t
h
e
In
v
e
rter
F
e
d
I
n
d
u
c
ti
o
n
M
o
t
o
r,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Po
we
r E
lec
tro
n
ics
a
n
d
Dr
ive
S
y
ste
ms
,
v
o
l.
8
,
n
o
.
2
,
p
p
.
7
2
2
–
72
9
.
2
0
1
7
.
[1
8
]
S
a
p
u
tra
P
.
P
.
S
.
,
M
is
b
a
h
,
e
li
y
a
n
i,
R.
F
irma
n
sy
a
h
,
D
.
Las
to
m
o
,
“
H
a
a
r
a
n
d
S
y
m
let
Disc
re
te
Wav
e
lete
Tran
sfo
rm
fo
r
Id
e
n
ti
fica
ti
o
n
M
isa
li
g
n
m
e
n
t
o
n
T
h
re
e
P
h
a
se
In
d
u
c
ti
o
n
M
o
to
r
Us
in
g
En
e
r
g
y
Le
v
e
l
a
n
d
F
e
a
tu
re
E
x
trac
ti
o
n
,
”
J
o
u
rn
a
l
o
f
Ph
y
sic
s: Co
n
fer
e
n
c
e
S
e
rie
s
,
2
0
1
9
.
[1
9
]
An
to
n
As
fa
n
i,
Dim
a
s
&
Yu
li
sty
a
Ne
g
a
ra
,
I
M
a
d
e
&
S
u
ry
a
,
P
re
ss
a
,
“
S
h
o
rt
Circu
it
De
tec
ti
o
n
in
S
tato
r
Wi
n
d
in
g
o
f
T
h
re
e
P
h
a
se
In
d
u
c
ti
o
n
M
o
t
o
r
Us
in
g
Wav
e
let
Tran
sfo
rm
a
n
d
Qu
a
d
ra
ti
c
Disc
rimin
a
n
t
An
a
ly
sis,”
T
h
e
3
rd
IIA
E
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
In
tell
ig
e
n
t
S
y
ste
ms
a
n
d
Ima
g
e
Pro
c
e
ss
in
g
2
0
1
5
,
2
0
1
5
.
[2
0
]
C.
Je
tt
a
n
a
se
n
,
A.
Ng
a
o
p
it
a
k
k
u
l,
D.
A.
As
fa
n
i
a
n
d
I.
M
.
Y.
Ne
g
a
ra
,
"
F
a
u
lt
c
las
sifica
ti
o
n
i
n
tran
sf
o
rm
e
r
u
sin
g
l
o
w
fre
q
u
e
n
c
y
c
o
m
p
o
n
e
n
t,
"
2
0
1
7
IE
EE
1
0
th
I
n
ter
n
a
t
io
n
a
l
W
o
rk
sh
o
p
o
n
Co
mp
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t
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ti
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l
I
n
telli
g
e
n
c
e
a
n
d
A
p
p
li
c
a
ti
o
n
s
(IW
CIA),
Hiro
sh
ima
,
p
p
.
1
9
9
-
2
0
2
,
2
0
1
7
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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(
P.
P.
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.
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a
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969
[2
1
]
P
.
P
.
S
.
S
a
p
u
tra,
F
.
D.
M
u
r
d
ian
to
,
R
.
F
irma
n
sy
a
h
a
n
d
K.
Wi
d
a
rso
n
o
,
“
Co
m
b
in
a
ti
o
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o
f
Qu
a
d
ra
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ic
Disc
rimin
a
n
t
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a
ly
sis
a
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d
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e
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h
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let
fo
r
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sifica
ti
o
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Lev
e
l
of
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isa
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g
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m
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on
I
n
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M
o
to
r,
”
2
0
1
9
In
ter
n
a
ti
o
n
a
l
S
y
mp
o
si
u
m o
n
El
e
c
tro
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ics
a
n
d
S
ma
rt De
v
ice
s (IS
ES
D),
B
a
d
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n
g
-
B
a
li
,
I
n
d
o
n
e
si
a
,
p
p
.
1
-
5
,
2
0
1
9
.
[2
2
]
Ca
o
X.,
Zh
o
u
S
.
,
Li
J
.
,
&
Z
h
a
n
g
S
.
,
“
F
a
u
lt
Dia
g
n
o
sis
in
M
e
d
i
u
m
Vo
lt
a
g
e
Dri
v
e
Ba
se
d
o
n
C
o
m
b
in
a
ti
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n
o
f
Wav
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let
Tran
sfo
rm
a
n
d
S
u
p
p
o
rt
Ve
c
to
r
M
a
c
h
in
e
,
”
T
EL
KOM
NIKA
T
e
lec
o
mm
u
n
ic
a
ti
o
n
Co
mp
u
ti
n
g
El
e
c
tr
o
n
ics
a
n
d
Co
n
tro
l
,
v
o
l.
14
,
n
o
.
4
,
p
p
.
1
2
8
4
–
1
2
9
1
,
2
0
1
6
.
[2
3
]
Jo
h
n
s
o
n
R
.
A
.
,
Wi
c
h
e
r
n
D
.
W.,
“
Ap
p
li
e
d
m
u
lt
iv
a
riate
s
tatisti
c
a
l
a
n
a
ly
sis,”
4
th
e
d
.
S
a
d
d
le
Riv
e
r,
NJ
:
P
re
n
ti
c
e
-
Ha
ll
,
1
9
9
8
.
[2
4
]
C.
Bo
u
v
e
y
ro
n
,
S
.
G
irard
,
a
n
d
C.
S
c
h
m
id
,
“
Hi
g
h
Dim
e
n
sio
n
a
l
Disc
rimin
a
n
t
An
a
ly
sis
,”
Co
mm
u
n
ica
ti
o
n
s
i
n
S
ta
ti
st
ics
-
T
h
e
o
ry
a
n
d
M
e
t
h
o
d
s,
”
v
o
l.
36
,
n
o
.
14
,
p
p
.
2
6
0
7
–
2
6
2
3
,
2
0
0
7
.
[2
5
]
S
a
p
u
tra
P
.
P
.
S
.
,
F
irma
n
s
y
a
h
R.
,
&
Ira
wa
n
D.
,
“
V
a
rio
u
s
a
n
d
m
u
l
ti
lev
e
l
o
f
c
o
ifl
e
t
d
isc
re
te
wa
v
e
let
tran
sfo
rm
a
n
d
q
u
a
d
ra
ti
c
d
isc
rimin
a
n
t
a
n
a
ly
sis
f
o
r
c
las
sifica
ti
o
n
m
isa
li
g
n
m
e
n
t
o
n
t
h
re
e
p
h
a
se
in
d
u
c
ti
o
n
m
o
t
o
r,
”
J
o
u
rn
a
l
o
f
P
h
y
sic
s:
Co
n
fer
e
n
c
e
S
e
rie
s
,
v
o
l.
1
3
6
7
,
n
o
.
2
0
1
9
,
p
p
.
1
-
1
1
,
2
0
1
9
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
Pre
ss
a
Per
d
a
n
a
S
u
r
y
a
S
a
p
u
tr
a
wa
s
b
o
rn
in
k
late
n
,
I
n
d
o
n
e
sia
i
n
1
9
8
8
.
He
re
c
e
iv
e
d
h
is
M
a
ste
r
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
fr
o
m
ITS
i
n
2
0
1
4
.
N
o
w
h
e
wo
rk
s
a
s
lec
tu
re
r
i
n
UMG
.
His
re
sa
rc
h
i
n
tere
sts
in
c
lu
d
e
re
n
e
wa
b
le
e
n
e
rg
y
a
n
d
e
n
e
rg
y
c
o
n
v
e
rsio
n
.
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we
v
e
r,
n
o
w
h
is
re
se
a
rc
h
fo
c
u
se
s
o
n
e
lec
tri
c
a
l
m
o
to
r
a
n
d
h
is mo
n
it
o
ri
n
g
.
Mi
sba
h
,
b
o
rn
i
n
G
re
sik
,
In
d
o
n
e
sia
in
1
9
7
6
.
Re
c
e
iv
e
d
h
is
M
a
ste
r
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
fr
o
m
ITS
in
2
0
0
9
.
Wo
r
k
e
d
a
s
lec
tu
re
r
in
UMG
.
F
o
c
u
s
re
se
a
rc
h
is
g
a
s
se
n
so
r.
T
h
e
fo
c
u
s
o
f
re
se
a
rc
h
in
th
e
field
o
f
g
a
s a
n
d
o
d
o
r
se
n
so
rs.
Cu
rre
n
tl
y
p
u
rsu
i
n
g
d
o
c
to
ra
l
stu
d
i
e
s a
t
ITS
sin
c
e
2
0
1
7
H
e
n
d
r
a
Ar
iwin
a
r
n
o
wa
s
b
o
r
n
i
n
Ba
n
y
u
wa
n
g
i
,
In
d
o
n
e
sia
in
1
9
8
0
.
His
fo
c
u
s
re
se
a
rc
h
is
EM
G
(El
e
c
tro
m
y
o
g
ra
m
)
a
n
d
it
s
c
las
sifica
ti
o
n
.
I
n
a
d
d
it
i
o
n
,
h
e
is
a
n
e
x
p
e
rt
i
n
e
lec
tro
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n
d
m
icro
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ro
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e
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r.
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r
id
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i
Mu
r
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