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lem
s
th
at
cl
o
s
e
to
o
u
r
ap
p
r
o
ac
h
.
Sectio
n
2
s
h
o
ws
a
g
en
er
al
r
ev
iew
o
f
t
h
e
“
Par
is
ian
ev
o
lu
tio
n
"
s
tr
ateg
y
in
s
p
ec
if
ic
th
e
f
ly
alg
o
r
ith
m
.
Sectio
n
3
r
ep
r
e
s
en
ts
th
e
ad
ap
tatio
n
o
f
th
e
f
ly
alg
o
r
ith
m
in
to
ev
o
lu
tio
n
ar
y
s
o
u
n
d
s
y
n
t
h
esis
.
Ho
wev
er
,
th
e
f
ly
alg
o
r
it
h
m
p
r
e
v
io
u
s
ly
u
s
ed
f
o
r
m
ed
ical
to
m
o
g
r
ap
h
y
r
ec
o
n
s
tr
u
ctio
n
,
r
o
b
o
tic
a
n
d
d
ig
ital
ar
t
g
en
er
ato
r
ap
p
licatio
n
s
.
T
h
is
s
ec
tio
n
f
o
llo
ws
t
h
e
r
esu
lt.
Fin
ally
,
th
e
r
em
ar
k
a
b
le
co
n
cl
u
s
io
n
g
iv
es in
th
e
last
s
ec
tio
n
.
2.
E
VO
L
U
T
I
O
N
ARY
SO
UN
D
SYNT
H
E
S
I
S
So
u
n
d
s
y
n
t
h
esis
h
as
b
ee
n
ac
ti
v
e
r
esear
ch
f
o
r
m
o
r
e
t
h
an
f
o
u
r
d
ec
ad
es.
Sev
er
al
tech
n
iq
u
es
f
o
r
s
o
u
n
d
s
y
n
th
esizer
s
lik
e
ad
d
itiv
e
s
y
n
th
esis
,
s
u
b
tr
ac
tiv
e
s
y
n
th
esis
,
f
r
eq
u
en
cy
m
o
d
u
latio
n
,
wav
etab
le
s
y
n
th
esis
o
r
p
h
y
s
ical
m
o
d
elin
g
[
9
]
.
So
u
n
d
s
y
n
th
esis
f
r
o
m
th
e
im
ag
e
h
as s
ev
er
al
im
p
lem
en
tatio
n
s
; o
n
e
p
o
s
s
ib
le
ap
p
licatio
n
co
u
ld
b
e
e
x
p
r
ess
ed
u
s
in
g
a
n
a
r
tis
t
to
d
r
aw
s
o
u
n
d
[
1
0
]
.
B
r
ag
an
d
et
al
.
[
1
0
]
p
r
esen
t
a
u
s
er
in
ter
f
ac
e
to
g
e
n
er
ate
s
o
u
n
d
f
r
o
m
im
a
g
e
r
ely
in
g
o
n
a
Vo
r
o
n
o
i
alg
o
r
ith
m
.
An
o
t
h
er
ap
p
r
o
ac
h
,
Ph
o
t
o
s
o
u
n
d
er
[
1
1
]
th
e
au
th
o
r
s
ap
p
ly
an
in
v
er
s
e
Fas
t Fo
u
r
ier
tr
an
s
f
o
r
m
(
FF
T
)
o
n
t
h
e
in
p
u
t im
ag
e
t
o
g
en
er
ate
s
o
u
n
d
a
f
ter
th
ey
ex
am
in
e
th
e
im
ag
e
as
a
m
ag
n
itu
d
e
s
p
ec
tr
o
g
r
am
.
So
u
n
d
s
y
n
th
esis
im
p
lem
en
tati
o
n
s
h
av
e
m
an
ip
u
lated
u
s
in
g
an
ev
o
lu
tio
n
ar
y
alg
o
r
ith
m
(
E
A)
.
I
n
2
0
0
1
,
Gar
c
ia
an
d
h
is
co
lleag
u
e
a
p
p
lied
g
en
etic
p
r
o
g
r
am
m
in
g
(
GP)
an
d
p
er
ce
p
tu
al
d
is
tan
ce
m
etr
ics f
o
r
m
ea
s
u
r
in
g
th
e
d
is
tan
ce
b
etwe
en
th
e
tar
g
et
an
d
p
r
o
d
u
ce
d
s
o
u
n
d
s
[
1
2
]
.
T
h
e
r
esear
ch
er
s
in
[
1
3
]
en
h
a
n
ce
th
e
FM
s
y
n
th
esis
m
o
d
el
with
s
o
m
e
ch
an
g
es.
T
h
ey
r
el
y
o
n
m
o
r
e
wav
ef
o
r
m
s
th
an
a
s
in
e
wav
e,
lik
e
a
s
awto
o
th
wav
e.
Fo
r
s
y
n
th
esis
,
th
is
p
ap
er
u
s
es
GA
wit
h
a
f
itn
ess
f
u
n
ctio
n
th
at
weig
h
ted
s
u
m
o
f
two
s
p
ec
tr
u
m
-
co
m
p
ar
is
o
n
m
etr
ics.
T
h
e
cr
o
s
s
o
v
er
s
elec
tio
n
p
ar
a
m
eter
h
as
s
h
o
wn
a
s
ig
n
if
ican
t
ef
f
ec
t
o
n
th
e
p
r
o
b
l
em
d
o
m
ain
.
Yo
n
g
[
1
4
]
f
o
llo
w
s
L
ai
an
d
h
is
co
lleag
u
es
f
o
r
s
o
u
n
d
s
y
n
t
h
esis
u
s
in
g
GA.
Ho
wev
er
,
h
e
d
ep
en
d
s
o
n
th
e
DFM
s
y
n
th
esis
m
o
d
el
with
th
e
s
am
e
ty
p
e
o
f
f
itn
ess
f
u
n
ctio
n
.
T
h
e
im
p
lem
en
tatio
n
is
d
o
n
e
b
y
Ma
tLa
b
t
o
p
r
o
d
u
ce
an
o
u
tp
u
t
s
p
ec
tr
u
m
ac
co
r
d
i
n
g
to
i
n
p
u
t
(
ta
r
g
et)
s
o
u
n
d
s
p
ec
tr
u
m
f
ile.
Oth
e
r
r
esear
ch
e
r
s
[
1
5
]
h
av
e
b
ee
n
u
s
ed
m
et
h
o
d
wh
ich
is
ce
llu
lar
au
to
m
ata
(
C
A)
.
T
h
is
tech
n
iq
u
e
ca
n
b
e
class
if
ied
as
o
n
e
o
f
a
class
o
f
e
v
o
lu
tio
n
a
r
y
alg
o
r
it
h
m
s
f
o
r
m
o
d
elin
g
d
y
n
am
ic
s
y
s
tem
s
th
at
m
o
d
i
f
y
s
ev
er
al
ch
ar
ac
ter
is
tics
with
ti
m
e.
Ou
r
wo
r
k
f
o
llo
ws
th
e
ev
o
lu
t
io
n
ar
y
s
o
u
n
d
p
a
r
ad
ig
m
.
T
h
e
s
o
u
n
d
s
y
n
th
esis
s
o
lv
ed
b
y
E
A
as
an
o
p
tim
izatio
n
p
r
o
b
lem
.
I
n
s
p
e
cif
ic,
o
u
r
p
r
o
p
o
s
ed
m
eth
o
d
r
elies
o
n
th
e
f
ly
alg
o
r
ith
m
,
wh
ich
is
a
ty
p
e
o
f
co
o
p
er
ativ
e
co
-
ev
o
lu
tio
n
(
C
o
C
o
)
s
tr
ateg
y
[
1
6
]
.
I
n
th
is
r
esear
ch
,
we
tr
ea
t
s
o
u
n
d
s
y
n
th
esis
as
im
ag
e
r
ec
o
n
s
tr
u
ctio
n
.
T
h
e
p
r
in
cip
les
o
f
o
u
r
m
eth
o
d
f
o
llo
w
th
e
ca
s
e
o
f
s
tu
d
y
in
g
s
o
u
n
d
s
y
n
th
esis
as
a
s
p
ec
if
ic
ca
s
e
o
f
th
e
s
et
co
v
e
r
p
r
o
b
lem
b
y
p
lac
in
g
a
g
r
o
u
p
o
f
tiles
as
a
s
et
o
n
a
s
q
u
ar
e
s
h
ap
e
r
eg
io
n
to
co
n
v
er
g
e
n
t
a
co
lo
u
r
ed
im
ag
e
[
1
7
]
.
Her
e
s
o
u
n
d
s
y
n
th
esis
f
alls
u
n
d
er
th
e
s
u
b
ject
o
f
g
en
er
atin
g
d
ig
ital
m
o
s
aic
b
y
f
itti
n
g
m
o
s
aic
tiles
o
n
a
s
u
r
f
ac
e.
E
ac
h
tile
n
ee
d
s
s
ettin
g
u
p
9
elem
en
ts
(
3
co
lo
u
r
co
m
p
o
n
en
ts
,
h
eig
h
t,
wid
th
,
r
o
tatio
n
an
g
le,
an
d
3
-
D
p
o
s
itio
n
)
,
th
e
s
ea
r
c
h
s
p
ac
e
is
co
m
p
l
ex
wh
ich
h
as
9
_
N
d
im
en
s
io
n
s
.
Su
ch
a
p
r
o
b
lem
is
a
d
if
f
icu
lt
o
p
tim
izatio
n
p
r
o
b
lem
to
s
o
lv
e
.
I
n
th
is
r
esear
ch
,
we
p
r
o
p
o
s
e
to
s
o
lv
e
th
is
p
r
o
b
lem
u
s
in
g
a
ty
p
e
o
f
co
o
p
er
ativ
e
co
-
ev
o
lu
tio
n
al
g
o
r
ith
m
(
C
C
E
A)
ca
lled
“Par
is
ian
e
v
o
lu
tio
n
"
[
1
8
]
.
T
h
e
Par
is
ian
a
p
p
r
o
ac
h
is
d
if
f
er
in
g
f
r
o
m
class
ical
E
As.
Fo
r
th
e
s
o
lu
tio
n
o
f
th
e
o
p
tim
izatio
n
p
r
o
b
lem
,
th
e
E
As
ar
e
s
ea
r
ch
in
g
o
n
th
e
b
est
o
n
e
in
d
iv
id
u
al
as
th
e
s
o
lu
tio
n
.
W
h
ile
th
e
C
C
E
A
s
tr
ateg
y
lo
o
k
s
o
n
a
s
et
o
r
s
u
b
s
et
o
f
in
d
iv
id
u
als
o
f
th
e
p
o
p
u
latio
n
as
a
f
in
al
s
o
lu
tio
n
.
T
h
is
m
ea
n
s
t
h
at
e
v
er
y
in
d
i
v
id
u
al
is
a
p
ar
t
o
f
th
e
s
o
l
u
tio
n
,
an
d
all
i
n
d
iv
id
u
als
co
llab
o
r
atin
g
to
b
u
ild
th
e
f
in
al
s
o
lu
tio
n
[
1
9
]
.
3.
O
VE
RVI
E
W
O
F
T
H
E
F
L
Y
AL
G
O
RI
T
H
M
Fo
r
s
o
lv
in
g
th
e
s
o
u
n
d
r
ec
o
n
s
tr
u
ctio
n
p
r
o
b
lem
,
we
f
o
llo
w
th
e
m
ain
m
ec
h
an
ics
as
i
n
Par
is
ian
ev
o
lu
tio
n
.
Fig
u
r
e
1
s
h
o
ws
t
h
e
p
r
in
ci
p
les
o
f
th
e
s
tead
y
-
s
tate
o
f
th
e
Par
is
ian
ev
o
lu
tio
n
alg
o
r
ith
m
[
2
0
]
.
T
h
is
alg
o
r
ith
m
s
im
ilar
to
class
ical
E
A,
wh
ich
co
n
tain
s
th
e
u
s
u
al
g
en
etic
o
p
er
at
o
r
s
o
f
an
E
A:
s
elec
tio
n
,
m
u
tatio
n
,
an
d
r
ec
o
m
b
in
atio
n
a
s
well
as th
e
ad
d
itio
n
al
in
g
r
ed
i
en
ts
two
ty
p
es o
f
f
itn
ess
,
as th
e
f
o
llo
win
g
:
-
Glo
b
a
l f
itn
ess
ev
alu
ated
th
e
wh
o
le
p
o
p
u
latio
n
[
2
1
,
22]
.
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
u
to
ma
tic
s
o
u
n
d
s
yn
th
esis
u
s
in
g
th
e
fly
a
l
g
o
r
ith
m
(
Za
in
a
b
A
.
A
b
b
o
o
d
)
2441
-
L
o
ca
l f
itn
ess
ev
alu
ated
t
h
e
s
in
g
le
co
n
tr
i
b
u
tio
n
o
f
th
e
in
d
iv
i
d
u
al
to
th
e
g
lo
b
al
s
o
lu
tio
n
.
Fig
u
r
e
1
.
Stead
y
-
s
tate
co
o
p
er
a
tiv
e
co
-
ev
o
l
u
tio
n
s
tr
ateg
y
.
I
n
Sectio
n
2
,
we
m
e
n
tio
n
ed
th
at
o
u
r
wo
r
k
d
ep
e
n
d
ed
o
n
th
e
Par
is
ian
(
Fly
)
s
tr
ateg
y
.
T
h
e
in
d
i
v
id
u
als in
th
is
alg
o
r
ith
m
c
o
r
r
esp
o
n
d
to
two
ty
p
es
o
f
s
tr
u
ctu
r
es.
On
e
co
r
r
esp
o
n
d
s
to
ex
ce
e
d
in
g
ly
s
im
p
le
p
r
im
itiv
es:
T
h
e
f
lies
[
2
3
]
r
ep
r
esen
t a
3
-
D
p
o
s
itio
n
o
n
ly
.
T
h
e
o
th
er
s
tr
u
ct
u
r
e
co
n
tain
s
9
-
elem
en
ts
as sh
o
wn
in
Fig
u
r
e
2
:
-
T
h
e
p
o
s
itio
n
is
a
v
ec
t
o
r
o
f
3
D
co
o
r
d
in
ates
(
x
,
y
,
z)
,
wh
ich
is
r
an
d
o
m
ly
g
e
n
er
ate
d
b
etwe
en
0
an
d
wid
th
-
1
,
0
an
d
h
eig
h
t
1
,
an
d
1
an
d
-
1
r
esp
ec
tiv
ely
(
with
wid
th
an
d
h
eig
h
t
th
e
n
u
m
b
er
o
f
p
ix
els
in
th
e
im
ag
e
alo
n
g
th
e
x
-
an
d
y
-
ax
is
)
.
An
ex
a
m
p
l
e
o
f
an
im
a
g
e
g
e
n
er
ated
b
y
an
in
itial p
o
p
u
latio
n
h
as sh
o
wn
i
n
Fig
u
r
e
3
.
-
C
o
lo
u
r
r
ep
r
esen
ted
b
y
th
r
ee
c
o
m
p
o
n
en
ts
(
r
,
g
,
b
)
wh
ich
ar
e
r
ed
,
g
r
ee
n
an
d
b
lu
e
r
esp
ec
tiv
ely
.
T
h
e
co
lo
u
r
elem
en
ts
ar
e
r
an
d
o
m
ly
g
e
n
e
r
ated
b
etwe
en
0
an
d
1
f
o
r
p
r
ec
is
e
d
is
p
lay
in
g
v
a
r
io
u
s
c
o
lo
u
r
s
f
o
r
ea
ch
in
d
iv
id
u
al.
-
R
o
tatio
n
An
g
le
is
r
an
d
o
m
ly
p
r
o
d
u
ce
d
to
co
v
er
a
co
m
p
lete
an
g
le
b
etwe
en
0
a
n
d
3
6
0
.
-
T
h
e
s
ca
lin
g
f
ac
to
r
d
o
m
in
ates
th
e
s
ize
o
f
th
e
tile
o
v
er
th
e
two
-
d
im
en
s
io
n
al
co
o
r
d
in
ate
s
y
s
tem
th
r
o
u
g
h
th
e
h
o
r
izo
n
tal
an
d
v
er
tical
ax
i
s
.
-
L
o
ca
l f
itn
ess
s
ca
les
it
s
m
ar
g
in
al
co
n
tr
ib
u
tio
n
ag
ain
s
t th
e
g
lo
b
al
s
o
lu
tio
n
.
Fig
u
r
e
2
.
T
h
e
f
ly
d
ata
s
tr
u
ctu
r
e
Fig
u
r
e
3
.
R
an
d
o
m
in
itial p
o
p
u
latio
n
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
:
2
4
3
9
-
2446
2442
T
h
e
g
o
al
o
f
o
u
r
alg
o
r
ith
m
is
to
o
p
tim
ize
th
e
9
elem
e
n
ts
o
f
all
in
d
iv
i
d
u
als.
T
h
e
p
r
o
p
o
s
ed
m
eth
o
d
aim
s
to
m
in
im
ize
th
e
g
lo
b
al
f
itn
ess
f
u
n
ctio
n
.
W
e
d
ep
en
d
o
n
th
e
s
u
m
o
f
ab
s
o
lu
te
er
r
o
r
(
SAE)
wh
ich
ca
lled
Ma
n
h
attan
d
is
tan
ce
to
o
[
2
4
]
.
T
h
is
s
ca
le
ass
e
s
s
e
s
h
o
w
is
a
g
o
o
d
th
e
p
o
p
u
latio
n
to
war
d
th
e
r
ef
er
e
n
ce
s
o
u
n
d
.
(
,
)
=
∑
∑
|
(
,
)
−
(
,
)
|
(
1
)
T
h
e
SAE
is
co
m
p
ar
ed
th
e
r
ef
e
r
en
ce
im
ag
e
I
NI
with
th
e
r
ec
o
n
s
tr
u
cted
im
ag
e
p
o
p
.
W
h
ile
ass
e
s
s
in
g
th
e
p
er
f
o
r
m
a
n
ce
o
f
a
s
in
g
le
y
,
we
u
s
e
lo
c
al
f
itn
ess
.
T
h
is
f
itn
ess
k
n
o
ws
“m
ar
g
in
al
f
itn
ess
",
Fm
(
i)
(
s
ee
(
2
)
)
.
Ou
r
alg
o
r
ith
m
l
o
o
k
s
to
im
p
r
o
v
e
t
h
e
p
o
p
u
latio
n
p
er
f
o
r
m
an
ce
b
y
i
n
cr
ea
s
in
g
th
e
g
o
o
d
f
lies
ag
ain
s
t
th
e
b
ad
f
lies
.
T
h
e
SAE
m
etr
ics
p
lu
s
th
e
leav
e
-
o
n
e
-
o
u
t
c
r
o
s
s
-
v
alid
atio
n
m
et
h
o
d
ar
e
u
s
ed
to
g
a
u
g
e
th
e
d
eg
r
ee
o
f
c
o
m
p
atib
ilit
y
o
f
Fly
i
to
th
e
r
ef
er
en
ce
im
ag
e
.
W
e
s
elec
t
a
f
ly
t
h
at
h
as
a
g
o
o
d
co
n
tr
ib
u
tio
n
to
th
e
p
o
p
u
latio
n
an
d
leav
es o
u
t th
e
b
ad
o
n
e.
(
)
=
(
−
{
}
,
)
−
(
,
)
(
2
)
W
ith
R
C
I
–
{
i
}
th
e
im
a
g
e
ca
lc
u
lated
with
all
in
d
iv
id
u
als
ex
c
ep
t
Fly
i
.
T
h
e
s
ig
n
o
f
th
e
v
al
u
e
o
f
Fm
(
i)
r
ef
e
r
r
ed
to
as a
d
if
f
er
e
n
t in
ter
p
r
etatio
n
:
-
s
g
n
(
F
m
(
i)
)
b
ec
o
m
es
less
th
an
0
wh
en
th
e
d
if
f
er
e
n
ce
(
er
r
o
r
)
i
s
g
r
ea
ter
with
Fly
i
.
T
h
is
m
ea
n
s
th
at
th
e
Fly
i
is
in
co
m
p
atib
le
with
th
e
o
p
tim
al
s
o
lu
tio
n
f
o
r
all
th
e
r
est o
f
i
n
d
iv
id
u
als.
-
s
g
n
(
F
m
(
i)
)
b
ec
o
m
es
g
r
ea
ter
th
an
0
wh
en
th
e
d
if
f
er
en
ce
(
er
r
o
r
)
is
less
with
Fly
i
.
T
h
is
m
ea
n
s
th
at
th
e
Fly
i
is
co
n
v
er
g
e
d
to
th
e
o
p
tim
al
s
o
lu
tio
n
.
-
s
g
n
(
F
m
(
i)
)
b
ec
o
m
es
eq
u
al
to
0
wh
en
th
e
d
if
f
er
e
n
ce
(
er
r
o
r
)
is
th
e
s
am
e
with
Fly
i
.
T
h
is
m
ea
n
s
th
at
th
e
Fly
i
is
n
o
t v
alu
ab
le
n
o
r
d
estru
ctiv
e
.
A
s
th
e
alg
o
r
ith
m
p
r
o
ce
s
s
in
g
g
o
in
g
o
n
as
th
e
b
ad
f
lies
d
ec
r
ea
s
e.
Fo
r
th
e
s
ele
ctio
n
s
tag
e,
we
u
s
e
th
e
T
h
r
esh
o
ld
s
elec
tio
n
o
p
er
ato
r
[
2
5
]
.
I
f
F
m
(
i)
≤
0
,
th
e
n
Fly
i
ca
n
b
e
lef
t
o
u
t;
else
it
is
a
g
o
o
d
ca
n
d
i
d
ate
f
o
r
r
e
p
r
o
d
u
ctio
n
.
Fo
r
s
to
p
p
in
g
c
r
iter
ia
o
f
t
h
e
alg
o
r
ith
m
,
we
d
e
p
en
d
o
n
t
h
e
alg
o
r
ith
m
s
tr
u
g
g
le
to
f
in
d
b
ad
f
lies
to
k
ill.
4.
RE
SU
L
T
S
I
n
th
is
s
ec
tio
n
,
we
d
esig
n
a
u
to
m
ated
s
o
u
n
d
s
y
n
th
esis
th
r
o
u
g
h
th
e
f
ly
alg
o
r
ith
m
a
n
d
p
er
ce
p
tu
al
d
is
tan
ce
m
etr
ics
to
m
ea
s
u
r
e
th
e
d
is
tan
ce
b
etwe
en
r
ef
er
e
n
c
e
(
r
ef
)
an
d
g
en
e
r
ated
(
g
e
n
)
s
o
u
n
d
.
T
h
e
p
r
e
v
io
u
s
s
ec
tio
n
s
h
o
ws
th
is
wo
r
k
r
ely
in
g
o
n
SAE
m
atr
ices
to
q
u
an
tify
th
e
er
r
o
r
b
etwe
en
th
e
in
p
u
t
an
d
tar
g
et
s
o
u
n
d
.
Fo
r
f
ast
p
r
o
ce
s
s
in
g
,
we
co
m
p
u
te
th
e
SAE
with
th
e
h
elp
o
f
a
g
r
ap
h
ics
p
r
o
ce
s
s
in
g
u
n
it
(
GPU)
u
s
in
g
th
e
Op
e
n
GL
s
h
ad
in
g
lan
g
u
ag
e
(
GL
SL)
as
s
h
o
wn
in
Fig
u
r
e
4
.
Fig
u
r
e
4
.
C
o
m
p
u
tatio
n
o
f
th
e
m
ar
g
in
al
f
itn
ess
o
n
GPU
f
o
r
t
wo
im
ag
es u
s
in
g
GL
SL
an
d
Op
en
GL
(
in
y
ello
w
an
d
g
r
ee
n
b
o
x
es r
esp
ec
tiv
ely
)
T
h
e
g
en
s
o
u
n
d
is
g
e
n
er
ated
o
f
f
lin
e
u
s
in
g
a
Fra
m
e
B
u
f
f
er
Ob
ject
(
FB
O)
.
So
u
n
d
s
in
clu
d
i
n
g
r
e
f
an
d
g
en
ar
e
s
to
r
ed
u
s
in
g
2
-
D
Op
e
n
GL
tex
tu
r
es.
T
h
e
n
ex
t
s
tep
i
s
th
at
th
e
p
ix
el
-
wis
e
ab
s
o
lu
te
er
r
o
r
b
etwe
en
(
r
e
f
)
an
d
(
g
en
)
is
co
m
p
u
ted
af
ter
t
h
e
tex
tu
r
e
is
p
as
s
ed
t
o
a
GL
SL
s
h
ad
er
p
r
o
g
r
am
.
T
h
e
p
r
o
ce
s
s
o
f
s
u
m
m
atio
n
is
co
m
p
leted
o
n
th
e
GPU
with
th
e
h
elp
o
f
th
e
Op
en
GL
ap
p
lic
atio
n
o
f
th
e
r
ed
u
ctio
n
o
p
e
r
ato
r
p
r
o
v
id
e
d
b
y
B
o
o
s
t
C
o
m
p
u
te
[
2
6
]
.
I
t
e
f
f
icien
tly
s
u
p
p
lies
th
e
SAE.
Als
o
,
o
u
r
m
eth
o
d
u
s
es
o
n
ly
a
n
o
p
er
at
o
r
o
f
m
u
tatio
n
f
o
r
g
en
er
atin
g
a
g
o
o
d
f
ly
an
d
r
ep
l
ac
e
with
a
b
ad
f
ly
d
u
r
in
g
an
iter
atio
n
o
f
t
h
e
o
p
tim
izatio
n
tech
n
iq
u
e.
C
r
o
s
s
o
v
e
r
o
p
er
ato
r
e
x
clu
d
ed
to
e
n
s
u
r
e
th
at
p
r
o
d
u
ce
d
r
ec
en
t
f
l
y
p
ar
tia
lly
m
o
d
if
ied
f
r
o
m
th
e
g
o
o
d
p
r
ev
io
u
s
g
en
er
atio
n
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
u
to
ma
tic
s
o
u
n
d
s
yn
th
esis
u
s
in
g
th
e
fly
a
l
g
o
r
ith
m
(
Za
in
a
b
A
.
A
b
b
o
o
d
)
2443
f
ly
.
I
n
o
th
er
wo
r
d
s
,
wh
en
we
u
s
e
cr
o
s
s
o
v
er
m
ay
b
e
two
g
o
o
d
f
lies
p
r
o
d
u
cin
g
a
n
ew
f
ly
in
b
etwe
en
ar
e
v
er
y
lik
ely
to
b
e
b
ad
.
Ou
r
m
eth
o
d
is
test
ed
with
p
ar
am
eter
s
s
h
o
win
g
in
T
ab
le
1
a
n
d
T
ab
le
2
,
u
s
in
g
9
x
n
u
m
b
e
r
o
f
f
lies
-
D
s
ea
r
ch
s
p
ac
e.
I
n
t
h
e
f
ir
s
t
s
tep
s
o
f
th
e
al
g
o
r
ith
m
,
th
e
f
lies
r
an
d
o
m
ly
g
en
er
ate
d
u
s
in
g
th
e
s
q
u
ar
e
tiles
as
s
h
o
wn
in
Fig
u
r
e
3
.
T
h
e
m
u
tatio
n
p
r
o
b
ab
ilit
y
is
f
ix
ed
to
1
0
0
%
d
u
e
to
th
e
cr
o
s
s
o
v
er
is
n
o
t
s
u
itab
le
in
o
u
r
al
g
o
r
ith
m
.
Ou
r
p
r
ac
tical
p
ar
t
o
f
th
e
al
g
o
r
ith
m
p
r
o
ce
s
s
ed
au
t
o
m
atic
ally
.
Ho
wev
er
,
th
e
im
ag
e
(
an
d
its
s
ize)
an
d
th
e
n
u
m
b
er
o
f
in
d
iv
id
u
als
ar
e
s
elec
ted
b
y
th
e
u
s
er
.
T
o
av
o
id
s
lo
w
d
o
wn
th
e
wh
o
le
p
r
o
ce
s
s
,
th
e
u
s
er
b
alan
ce
d
th
e
n
u
m
b
er
o
f
f
lies
with
im
a
g
e
s
ize
f
o
r
a
v
o
id
in
g
p
r
em
atu
r
e
co
n
v
er
g
en
ce
.
Fo
r
r
ea
lis
tic
s
o
u
n
d
s
y
n
th
esis
,
o
u
r
alg
o
r
ith
m
r
ep
lace
s
th
e
s
q
u
a
r
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f
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ts
.
RE
F
E
R
E
NC
E
S
[1
]
R.
A.
G
a
r
c
ia,
"
Au
to
m
a
ti
n
g
t
h
e
d
e
sig
n
o
f
so
u
n
d
sy
n
th
e
sis
tec
h
n
i
q
u
e
s
u
sin
g
e
v
o
l
u
ti
o
n
a
ry
m
e
th
o
d
s,
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in
COS
T
G
-
6
Co
n
fer
e
n
c
e
o
n
Dig
i
ta
l
Au
d
io
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fe
c
ts,
L
ime
ric
k
,
Ire
la
n
d
,
2
0
0
1
.
[2
]
Rii
o
n
h
e
imo
,
J.,
Vä
li
m
ä
k
i,
V.
“
P
a
ra
m
e
ter
Esti
m
a
ti
o
n
o
f
a
P
lu
c
k
e
d
S
tri
n
g
S
y
n
th
e
sis
M
o
d
e
l
Us
in
g
a
G
e
n
e
ti
c
Alg
o
rit
h
m
with
P
e
rc
e
p
tu
a
l
F
i
tn
e
ss
Ca
lcu
latio
n
,
”
EURA
S
IP
J
.
Ad
v
.
S
ig
n
a
l
Pro
c
e
ss
,
v
o
l.
2
0
0
3
,
p
.
7
5
8
2
8
4
,
2
0
0
3
.
h
tt
p
s:/
/d
o
i.
o
rg
/
1
0
.
1
1
5
5
/S
1
1
1
0
8
6
5
7
0
3
3
0
2
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0
0
[3
]
M
.
F
.
Ca
e
tan
o
,
J.
M
a
n
z
o
ll
i,
a
n
d
F
.
J.
Vo
n
Z
u
b
e
n
,
"
I
n
tera
c
ti
v
e
Co
n
t
ro
l
o
f
Ev
o
l
u
ti
o
n
A
p
p
li
e
d
t
o
S
o
u
n
d
S
y
n
t
h
e
sis,"
i
n
FL
AIR
S
Co
n
fer
e
n
c
e
,
p
p
.
5
1
-
56
,
2
0
0
5
.
[4
]
P
.
Da
h
lsted
t
,
"
E
v
o
lu
ti
o
n
in
c
re
a
ti
v
e
so
u
n
d
d
e
sig
n
,
"
in
Evo
l
u
ti
o
n
a
ry
c
o
mp
u
ter
m
u
sic
,
e
d
:
S
p
ri
n
g
e
r,
p
p
.
7
9
-
99
,
2
0
0
7
.
[5
]
J.
M
c
De
rm
o
tt
,
N.
J.
G
riff
it
h
,
a
n
d
M
.
O’N
e
il
l,
"
Ev
o
lu
ti
o
n
a
ry
c
o
m
p
u
tatio
n
a
p
p
li
e
d
t
o
so
u
n
d
sy
n
th
e
sis,
"
in
T
h
e
Art
o
f
Arti
fi
c
ia
l
Evo
lu
ti
o
n
,
e
d
:
S
p
rin
g
e
r,
p
p
.
8
1
-
1
0
1
,
2
0
0
8
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
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,
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5
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b
e
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2
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2
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:
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2446
2446
[6
]
R.
Da
wk
in
s,
“
Th
e
b
l
in
d
wa
tch
m
a
k
e
r:
Wh
y
th
e
e
v
id
e
n
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e
o
f
e
v
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u
ti
o
n
re
v
e
a
ls
a
u
n
i
v
e
rse
wit
h
o
u
t
d
e
sig
n
.”
WW
No
rto
n
&
Co
m
p
a
n
y
,
1
9
9
6
.
[7
]
A.
Ho
rn
e
r,
J.
Be
a
u
c
h
a
m
p
,
a
n
d
L.
J.
C.
M
.
J.
Ha
k
e
n
,
"
M
a
c
h
i
n
e
to
n
g
u
e
s
XV
I:
G
e
n
e
ti
c
a
lg
o
rit
h
m
s
a
n
d
t
h
e
ir
a
p
p
li
c
a
ti
o
n
t
o
F
M
m
a
tch
in
g
sy
n
th
e
sis,"
Co
mp
u
ter
M
u
sic
J
o
u
r
n
a
l
,
v
o
l.
1
7
,
p
p
.
1
7
-
2
9
,
1
9
9
3
.
[8
]
K.
Weh
n
,
"
Us
in
g
id
e
a
s
fr
o
m
n
a
tu
ra
l
se
lec
ti
o
n
t
o
e
v
o
lv
e
sy
n
th
e
s
ize
d
so
u
n
d
s,"
i
n
Pro
c
e
e
d
i
n
g
s
o
f
Dig
it
a
l
Au
d
io
Ef
fec
ts wo
rk
sh
o
p
,
1
9
9
8
.
[9
]
E.
M
iran
d
a
,
“
Co
m
p
u
ter so
u
n
d
d
e
sig
n
:
s
y
n
t
h
e
sis tec
h
n
i
q
u
e
s a
n
d
p
r
o
g
ra
m
m
in
g
,”
Tay
lo
r
&
F
ra
n
c
is,
2
0
1
2
.
[1
0
]
V.
Bra
g
a
rd
,
T
.
P
e
ll
e
g
ri
n
i,
a
n
d
J.
P
in
q
u
ier,
"
P
y
c
2
S
o
u
n
d
:
a
P
y
th
o
n
t
o
o
l
t
o
c
o
n
v
e
rt
ima
g
e
s
i
n
to
so
u
n
d
,
"
i
n
Pro
c
e
e
d
in
g
s
o
f
t
h
e
A
u
d
i
o
M
o
stly
2
0
1
5
o
n
In
ter
a
c
ti
o
n
w
it
h
S
o
u
n
d
,
e
d
,
2
0
1
5
,
p
p
.
1
-
4
,
2
0
1
5
.
[1
1
]
L.
K.
P
h
o
t
o
so
u
n
d
e
r
,
“
p
h
o
t
o
so
u
n
d
e
r
,”
2
0
1
9
.
[On
li
n
e
].
A
v
a
il
a
b
le
:
h
t
tp
:/
/
p
h
o
to
s
o
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n
d
e
r.
c
o
m
[1
2
]
J.
M
a
n
z
o
ll
i,
A.
M
a
ia
Jr,
J.
F
o
r
n
a
ri,
a
n
d
F
.
J.
N.
R.
Da
m
ian
i,
"
A
M
e
th
o
d
fo
r
S
o
u
n
d
S
y
n
t
h
e
sis
Ba
se
d
o
n
G
e
n
e
ti
c
Alg
o
rit
h
m
s,"
S
e
ma
n
t
ic S
c
h
o
la
r
,
p
p
.
4
0
-
4
9
,
2
0
1
2
.
[1
3
]
Y.
Lai,
S
.
-
K.
Je
n
g
,
D.
-
T
.
Li
u
,
a
n
d
Y.
-
C.
Li
u
,
"
Au
t
o
m
a
ted
o
p
t
imiz
a
ti
o
n
o
f
p
a
ra
m
e
ters
fo
r
F
M
so
u
n
d
sy
n
t
h
e
sis
with
g
e
n
e
ti
c
a
lg
o
rit
h
m
s,"
in
In
ter
n
a
ti
o
n
a
l
W
o
rk
sh
o
p
o
n
Co
m
p
u
ter
M
u
si
c
a
n
d
Au
d
i
o
T
e
c
h
n
o
l
o
g
y
,
p
.
2
0
5
,
2
0
0
6
.
[1
4
]
Y.
S
.
,
"
Au
t
o
m
a
ti
c
F
M
S
y
n
th
e
sis
Ba
se
d
o
n
G
e
n
e
ti
c
Alg
o
ri
th
m
,
"
M
u
sic
T
e
c
h
n
o
lo
g
y
,
M
c
Gill
Un
ive
rs
it
y
,
2
0
0
7
.
[1
5
]
J.
S
e
rq
u
e
ra
a
n
d
E
.
R.
M
iran
d
a
,
"
Ev
o
l
u
ti
o
n
a
ry
s
o
u
n
d
s
y
n
t
h
e
sis:
re
n
d
e
rin
g
sp
e
c
tr
o
g
ra
m
s
fro
m
c
e
ll
u
lar
a
u
t
o
m
a
ta
h
isto
g
ra
m
s,"
in
Eu
r
o
p
e
a
n
C
o
n
fer
e
n
c
e
o
n
t
h
e
Ap
p
li
c
a
ti
o
n
s o
f
Evo
l
u
ti
o
n
a
ry
Co
mp
u
t
a
ti
o
n
,
p
p
.
3
8
1
-
3
9
0
,
2
0
1
0
.
[1
6
]
J.
Lo
u
c
h
e
t,
"
S
tere
o
a
n
a
ly
sis
u
sin
g
in
d
iv
i
d
u
a
l
e
v
o
lu
ti
o
n
stra
teg
y
,
"
i
n
Pro
c
e
e
d
in
g
s
1
5
t
h
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Pa
tt
e
rn
Rec
o
g
n
it
io
n
.
IC
PR
-
2
0
0
0
,
p
p
.
9
0
8
-
9
1
1
.
2
0
0
0
.
[1
7
]
R.
M
.
Ka
rp
,
"
Re
d
u
c
ib
il
it
y
a
m
o
n
g
c
o
m
b
i
n
a
to
rial
p
r
o
b
lem
s,"
i
n
C
o
mp
lex
it
y
o
f
c
o
mp
u
ter
c
o
m
p
u
t
a
ti
o
n
s
,
e
d
:
S
p
ri
n
g
e
r,
p
p
.
8
5
-
1
0
3
,
1
9
7
2
.
[1
8
]
A.
M
.
Bo
u
m
a
z
a
a
n
d
J.
Lo
u
c
h
e
t,
"
Dy
n
a
m
ic
fli
e
s:
Us
in
g
re
a
l
-
ti
m
e
P
a
risian
e
v
o
lu
t
io
n
i
n
r
o
b
o
ti
c
s,"
i
n
W
o
rk
sh
o
p
s
o
n
Ap
p
li
c
a
ti
o
n
s
o
f
Evo
lu
ti
o
n
a
ry
Co
mp
u
ta
ti
o
n
,
p
p
.
2
8
8
-
2
9
7
,
2
0
0
1
.
[1
9
]
C.
Vo
,
L.
P
a
n
a
it
,
a
n
d
S
.
Lu
k
e
,
"
Co
o
p
e
ra
ti
v
e
c
o
e
v
o
lu
ti
o
n
a
n
d
u
n
i
v
a
riate
e
stim
a
ti
o
n
o
f
d
istri
b
u
ti
o
n
a
lg
o
ri
th
m
s,"
in
Pro
c
e
e
d
in
g
s
o
f
t
h
e
ten
t
h
AC
M
S
I
GEVO
wo
rk
sh
o
p
o
n
F
o
u
n
d
a
ti
o
n
s
o
f
g
e
n
e
ti
c
a
l
g
o
rit
h
ms
,
p
p
.
1
4
1
-
1
5
0
,
2
0
0
9
.
[2
0
]
F
.
P
.
Vid
a
l
,
D.
Laz
a
ro
-
P
o
n
th
u
s,
S
.
Leg
o
u
p
i
l,
J.
L
o
u
c
h
e
t,
É.
Lu
t
to
n
,
a
n
d
J.
-
M
.
R
o
c
c
h
is
a
n
i,
"
Arti
ficia
l
e
v
o
l
u
ti
o
n
fo
r
3
D
P
ET
re
c
o
n
str
u
c
ti
o
n
,
"
i
n
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
Arti
fi
c
i
a
l
Evo
l
u
ti
o
n
(Evo
l
u
ti
o
n
Art
if
icie
ll
e
)
,
p
p
.
3
7
-
4
8
.
2
0
0
9
.
[2
1
]
L.
P
a
n
a
it
,
S
.
L
u
k
e
,
a
n
d
J.
F
.
Ha
rriso
n
,
"
Arc
h
iv
e
-
b
a
se
d
c
o
o
p
e
ra
ti
v
e
c
o
e
v
o
lu
ti
o
n
a
r
y
a
lg
o
ri
th
m
s,"
i
n
Pro
c
e
e
d
in
g
s
o
f
th
e
8
t
h
a
n
n
u
a
l
c
o
n
fer
e
n
c
e
o
n
Ge
n
e
ti
c
a
n
d
e
v
o
lu
t
io
n
a
ry
c
o
mp
u
t
a
ti
o
n
,
p
p
.
3
4
5
-
3
5
2
,
2
0
0
6
.
[2
2
]
E.
S
a
p
in
,
J.
Lo
u
c
h
e
t,
a
n
d
E.
L
u
tt
o
n
,
"
T
h
e
F
ly
Alg
o
rit
h
m
Re
v
isit
e
d
-
Ad
a
p
tatio
n
to
CM
OS
Im
a
g
e
S
e
n
s
o
rs,"
in
IJ
CCI
,
p
p
.
2
2
4
-
229
,
2
0
0
9
.
[2
3
]
Z.
A.
Ab
b
o
o
d
,
O.
Am
lal,
a
n
d
F
.
P
.
Vi
d
a
l,
"
E
v
o
l
u
ti
o
n
a
ry
a
rt
u
sin
g
th
e
fly
a
lg
o
rit
h
m
,
"
in
E
u
ro
p
e
a
n
Co
n
fer
e
n
c
e
o
n
th
e
Ap
p
li
c
a
t
io
n
s o
f
Evo
l
u
ti
o
n
a
ry
Co
mp
u
t
a
ti
o
n
,
p
p
.
4
5
5
-
4
7
0
,
2
0
1
7
.
[2
4
]
F
.
Al
F
a
rid
,
A.
G
h
o
d
s,
M
.
S
h
o
h
a
g
Ba
rm
a
n
,
A.
S
h
a
h
,
a
n
d
J.
Ud
d
in
,
"
An
Eff
icie
n
t
Alg
o
rit
h
m
f
o
r
Ac
c
e
lera
ti
n
g
Im
a
g
e
Re
sto
ra
ti
o
n
Us
i
n
g
E
u
c
li
d
e
a
n
a
n
d
M
a
n
h
a
tt
a
n
Dista
n
c
e
s."
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
M
a
ter
ia
ls,
El
e
c
tro
n
ics
&
In
fo
rm
a
t
io
n
E
n
g
i
n
e
e
rin
g
,
ICM
EI
E
-
2
0
1
5
,
At:
T
h
e
Un
i
v
e
rsi
ty
o
f
Ra
jsh
a
h
i,
Ra
jsh
a
h
i,
Ba
n
g
lad
e
sh
,
2
0
1
5
.
[2
5
]
F
.
P
.
Vi
d
a
l,
J.
Lo
u
c
h
e
t,
J.
-
M
.
Ro
c
c
h
isa
n
i,
a
n
d
É
.
L
u
tt
o
n
,
"
Ne
w
g
e
n
e
ti
c
o
p
e
ra
to
rs
i
n
t
h
e
fl
y
a
l
g
o
rit
h
m
:
a
p
p
li
c
a
ti
o
n
to
m
e
d
ica
l
P
ET
ima
g
e
re
c
o
n
stru
c
ti
o
n
,
"
in
Eu
ro
p
e
a
n
Co
n
fer
e
n
c
e
o
n
th
e
Ap
p
li
c
a
t
io
n
s
o
f
Evo
l
u
ti
o
n
a
r
y
Co
mp
u
t
a
ti
o
n
,
p
p
.
2
9
2
-
301
,
2
0
1
0
.
[2
6
]
K.
Lu
tz.
“
B
o
o
st
C
o
m
p
u
te
r
,”
2
0
1
5
.
[On
li
n
e
].
Av
a
il
a
b
le
:
h
t
tp
:/
/b
o
o
st
o
rg
.
g
it
h
u
b
.
io
/co
m
p
u
te/.
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