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Science
Vo
l.
23
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.
3
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Sep
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1708
J
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Les
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In
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K
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Acc
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a
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CC BY
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C
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Sin
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1
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cc
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to
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ased
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te
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s
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p
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s
s
o
r
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E
L
M)
[
1
]
,
[
2
]
.
T
h
e
E
L
M
is
a
f
ab
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icate
d
p
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o
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ty
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e
lo
g
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r
ith
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ased
p
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r
,
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h
as
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3
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b
it
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s
f
o
r
m
atio
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-
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ased
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NS
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ith
m
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it
(
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.
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h
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p
r
o
ce
s
s
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h
ad
d
e
m
o
n
s
tr
ated
t
h
at
L
NS
co
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ld
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e
th
e
b
est
r
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t
to
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with
s
p
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p
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v
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n
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an
d
h
ad
b
ee
n
ass
u
m
ed
as
a
r
ef
e
r
r
ed
s
tan
d
ar
d
f
o
r
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elate
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ch
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esig
n
s
.
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L
M,
an
o
t
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tewo
r
th
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ased
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p
r
o
ce
s
s
o
r
is
th
e
g
r
av
ity
p
ip
elin
e
(
GR
APE)
b
y
Ma
k
in
o
an
d
T
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[
3
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,
wh
ich
is
an
awa
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d
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win
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in
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f
o
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n
d
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p
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ly
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tili
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d
th
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L
NS
ad
d
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.
T
h
e
d
r
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ac
k
s
o
f
L
NS
s
u
b
tr
ac
tio
n
p
r
ec
lu
d
e
th
e
wid
e
s
p
r
ea
d
o
f
L
NS
u
s
ag
e
in
m
o
s
t
ap
p
licatio
n
s
.
B
ac
k
to
th
e
a
r
ith
m
etic
o
p
er
atio
n
s
co
n
d
u
cted
in
DSP,
th
e
L
NS
co
u
ld
s
im
p
lify
th
e
h
ig
h
ly
-
u
s
ed
ar
ith
m
etic
f
u
n
cti
o
n
s
wh
ich
a
r
e
th
e
FLP
m
u
ltip
licatio
n
an
d
d
iv
is
io
n
,
b
y
r
ep
r
esen
tin
g
t
h
em
in
f
ix
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-
p
o
in
t
(
FXP)
ad
d
itio
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a
n
d
s
u
b
tr
ac
tio
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r
esp
ec
tiv
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.
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t
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at,
L
NS
h
ad
b
ee
n
e
x
ten
s
iv
ely
em
p
lo
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ed
i
n
ar
ith
m
etic
-
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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J
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&
C
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4
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Les
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(
S
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Md
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)
1709
r
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c
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4
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7
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s
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8
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.
B
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h
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in
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f
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m
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R
NS)
to
g
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with
L
NS
[1
7
]
,
[
1
8
]
.
As
t
h
e
g
r
o
win
g
d
em
an
d
f
o
r
L
NS
in
ap
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k
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tr
en
g
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h
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co
m
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u
tatio
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f
o
r
m
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ltip
licatio
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d
d
iv
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io
n
o
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n
.
Ho
wev
er
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th
e
in
tr
icate
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ep
r
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n
tatio
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f
o
r
ad
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an
d
s
u
b
tr
ac
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n
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p
er
atio
n
in
L
NS
s
u
f
f
er
a
lo
t
o
f
d
if
f
icu
lty
as it r
ep
r
esen
ted
b
y
a
co
m
p
lex
f
u
n
ctio
n
in
wh
ic
h
k
n
o
wn
as n
o
n
-
lin
ea
r
f
u
n
ctio
n
.
No
n
eth
eles
s
,
th
ese
d
r
awb
ac
k
s
ar
e
allev
iated
an
d
n
e
g
o
tiab
le
f
o
r
lo
w
-
p
r
ec
is
io
n
ap
p
licatio
n
s
as
d
etailed
in
[
19
]
.
I
n
d
escr
i
b
in
g
th
e
n
o
n
-
lin
ea
r
f
u
n
ctio
n
,
ass
u
m
e
=
±
.
T
h
er
ef
o
r
e,
th
e
lo
g
ar
ith
m
ic
r
ep
r
esen
tatio
n
will
b
e
l
og
2
=
l
og
2
(
±
)
.
Af
ter
d
er
iv
atio
n
,
th
e
f
in
al
eq
u
atio
n
is
l
og
2
=
l
og
2
+
l
og
2
(
1
±
2
(
l
o
g
2
−
l
o
g
2
)
)
,
with
l
og
2
(
1
±
2
(
l
o
g
2
−
l
o
g
2
)
)
d
ep
icted
t
h
e
n
o
n
-
lin
ea
r
f
u
n
cti
o
n
.
T
h
is
f
u
n
ctio
n
co
n
s
u
m
es
e
n
o
r
m
o
u
s
am
o
u
n
t
o
f
R
OM
s
f
o
r
lo
g
v
alu
e
s
to
r
ag
e,
th
u
s
in
cr
ea
s
e
th
e
h
ar
d
war
e
an
d
ar
ea
r
eq
u
ir
e
m
en
ts
o
n
th
e
s
ilico
n
.
Hen
ce
,
th
e
ch
allen
g
e
is
to
r
ed
u
ce
th
e
h
ar
d
war
e
co
s
t w
h
ile
im
p
r
o
v
i
n
g
th
e
s
p
ee
d
o
f
th
ese
o
p
er
atio
n
s
in
L
NS a
t o
n
ce
.
T
o
s
u
p
p
o
r
t
th
e
ad
v
a
n
ce
m
en
t
o
f
L
NS
ar
ith
m
etic,
v
ar
io
u
s
m
eth
o
d
s
wer
e
d
is
co
v
er
e
d
to
en
h
an
ce
th
e
q
u
ality
o
f
ad
d
itio
n
an
d
s
u
b
t
r
ac
tio
n
o
p
er
atio
n
o
f
L
NS
as
lis
ted
in
[2
0
]
wh
ich
in
clu
d
e
L
UT
an
d
tab
le
p
ar
titi
o
n
in
g
m
eth
o
d
,
a
n
d
th
e
m
o
s
t
cu
r
r
e
n
t
m
eth
o
d
:
th
e
c
o
m
b
in
atio
n
o
f
co
-
tr
a
n
s
f
o
r
m
atio
n
with
in
te
r
p
o
latio
n
.
Yet,
in
ter
p
o
latio
n
is
f
o
u
n
d
t
o
b
e
t
h
e
f
in
est
s
ch
em
e
to
b
e
co
m
b
in
e
d
with
o
th
e
r
a
p
p
r
o
a
ch
f
o
r
lo
g
a
r
ith
m
ic
ap
p
r
o
x
im
atio
n
.
T
h
is
f
in
d
in
g
e
v
o
k
es th
e
id
ea
f
o
r
t
h
e
n
ew
L
N
S a
r
ch
itectu
r
e
in
th
is
wo
r
k
.
I
n
th
is
p
ap
e
r
,
th
e
k
ey
-
m
o
s
t
p
r
o
ce
d
u
r
e
in
L
NS
wh
ic
h
is
th
e
in
ter
p
o
latio
n
p
r
o
ce
d
u
r
e
is
e
x
ten
s
iv
ely
elab
o
r
ated
in
Sectio
n
2
with
t
h
e
b
est
s
elec
t
io
n
o
f
in
ter
p
o
lat
o
r
f
o
r
t
h
e
n
ew
L
NS.
Sectio
n
3
ex
p
o
s
es
th
e
p
r
o
ce
s
s
o
f
ev
alu
atin
g
an
d
m
ea
s
u
r
in
g
th
e
p
er
f
o
r
m
a
n
ce
o
f
th
e
d
esig
n
ed
L
NS
s
y
s
tem
.
T
h
e
ev
alu
atio
n
s
tep
s
f
o
r
ea
ch
p
er
f
o
r
m
an
ce
p
ar
am
eter
s
in
th
ese
p
r
o
ce
s
s
es
wh
ich
in
clu
d
e
m
em
o
r
y
u
tili
za
tio
n
an
d
ac
cu
r
ac
y
ar
e
m
e
n
tio
n
e
d
in
d
etail.
T
h
e
r
esu
lts
o
f
th
e
n
ew
L
NS
ar
ch
itectu
r
e
ar
e
p
r
esen
t
ed
an
d
d
is
cu
s
s
ed
in
Sectio
n
4
.
T
h
e
f
in
al
s
ec
tio
n
co
n
clu
d
es th
e
m
ai
n
o
u
tc
o
m
es
o
f
th
e
d
esig
n
.
2.
T
H
E
A
L
G
O
RIT
H
M
2
.
1
.
I
nte
rpo
la
t
i
o
n
p
ro
ce
du
re
in L
NS
I
n
ter
p
o
latio
n
is
d
ef
in
ed
as
a
p
r
o
ce
s
s
o
f
esti
m
atin
g
v
alu
es
o
r
o
th
er
p
o
i
n
ts
u
s
in
g
o
th
er
d
ata
v
alu
es
at
ce
r
tain
p
o
i
n
ts
[2
1
]
.
T
h
is
m
et
h
o
d
im
p
lem
en
ts
clo
s
ed
-
f
o
r
m
r
ep
r
esen
tatio
n
o
f
f
u
n
ctio
n
as
th
e
b
asis
f
o
r
o
th
er
n
u
m
er
ical
tech
n
i
q
u
es,
eith
er
n
u
m
er
ical
d
if
f
er
en
t
iatio
n
o
r
i
n
teg
r
atio
n
.
E
s
s
en
tially
,
th
e
in
ter
p
o
lated
L
UT
is
a
m
eth
o
d
th
at
wo
r
k
s
b
y
ass
o
ciatin
g
th
e
ap
p
r
o
x
im
atio
n
f
u
n
cti
o
n
v
alu
e
f
r
o
m
a
s
in
g
le
-
h
a
r
d
w
ar
e
u
n
it
s
o
-
ca
lled
as
in
ter
p
o
latin
g
m
e
m
o
r
y
[2
2
]
to
g
eth
er
with
th
e
in
ter
p
o
latio
n
s
c
h
em
e
f
o
r
h
ig
h
er
p
r
ec
is
io
n
.
T
h
e
u
s
ag
e
o
f
in
ter
p
o
lato
r
s
with
h
ig
h
er
d
eg
r
ee
ca
n
im
p
r
o
v
e
th
e
ac
cu
r
ac
y
o
f
th
e
i
n
ter
p
o
la
ted
r
esu
lts
d
esp
ite
its
d
is
ad
v
an
tag
es
o
f
u
tili
zin
g
a
n
u
m
b
e
r
o
f
m
em
o
r
y
lo
o
k
u
p
tab
les
an
d
m
u
ltip
lier
s
,
esp
ec
ially
in
h
ar
d
war
e
im
p
lem
en
tatio
n
.
H
o
wev
er
,
ea
c
h
i
n
ter
p
o
lato
r
w
ill
d
if
f
er
in
ter
m
s
o
f
h
ig
h
e
r
d
eg
r
ee
s
eg
m
e
n
t
r
ep
r
esen
tatio
n
alb
eit
th
ei
r
lin
e
ar
r
ep
r
esen
tatio
n
s
ar
e
s
im
ilar
.
T
h
er
ef
o
r
e,
p
r
o
p
er
s
elec
tio
n
o
f
in
ter
p
o
lato
r
co
u
ld
m
in
im
ize
th
e
r
is
k
in
p
r
o
d
u
cin
g
r
esu
lts
with
h
ig
h
er
p
r
ec
is
io
n
.
Me
an
wh
ile,
L
ag
r
a
n
g
e
in
te
r
p
o
lato
r
th
at
was
u
s
ed
in
r
ec
en
t
L
NS
im
p
lem
en
tatio
n
as
i
n
[1
0
]
is
n
o
t
s
u
itab
le
to
b
e
im
p
lem
en
ted
in
h
ig
h
er
d
eg
r
ee
f
o
r
m
in
h
ar
d
war
e
p
latf
o
r
m
,
as
it
h
as
to
r
ec
alcu
late
t
h
e
in
ter
p
o
latio
n
co
e
f
f
icien
ts
[2
3
]
with
q
u
ite
a
n
u
m
b
er
o
f
m
u
ltip
lier
s
.
T
h
e
lab
o
u
r
o
f
r
e
-
co
m
p
u
t
in
g
an
d
h
ig
h
u
s
ag
e
o
f
m
u
ltip
lier
s
m
ay
in
cr
ea
s
e
th
e
ar
ea
co
n
s
u
m
p
tio
n
an
d
th
e
s
p
ee
d
o
f
th
e
o
v
er
all
d
esig
n
.
B
ased
o
n
th
is
r
ea
s
o
n
,
th
e
L
ag
r
an
g
e
in
ter
p
o
lato
r
was
o
m
itted
f
r
o
m
th
is
wo
r
k
,
an
d
t
h
e
f
o
cu
s
will
b
e
o
n
o
th
er
p
o
te
n
tial
in
ter
p
o
lato
r
s
:
T
ay
lo
r
an
d
New
to
n
D
iv
id
ed
D
if
f
er
en
ce
in
ter
p
o
lato
r
s
.
T
h
ese
in
ter
p
o
lato
r
s
ar
e
s
elec
t
ed
as
th
ey
p
r
o
v
id
e
ac
ce
p
tab
le
am
o
u
n
t
o
f
m
u
ltip
licatio
n
u
n
it
th
at
is
n
ee
d
e
d
to
im
p
lem
en
t
a
h
ig
h
er
d
eg
r
ee
p
o
r
tio
n
o
f
t
h
e
in
ter
p
o
lato
r
,
wh
ile
ab
le
to
u
tili
ze
ex
is
tin
g
m
em
o
r
y
r
eso
u
r
ce
s
.
2
.
2
.
New
t
o
n div
ided diff
er
ence
inte
rpo
la
t
o
r
New
to
n
d
iv
id
ed
d
if
f
er
e
n
ce
in
ter
p
o
lato
r
is
an
in
ter
p
o
lati
o
n
tech
n
i
q
u
e
u
s
ed
wh
en
th
e
in
ter
v
al
d
if
f
er
en
ce
is
ir
r
e
g
u
lar
f
o
r
all
s
eq
u
en
ce
o
f
v
alu
es.
T
h
is
p
o
l
y
n
o
m
ial
in
ter
p
o
lato
r
is
m
u
ch
p
r
ef
er
ab
le
co
m
p
a
r
ed
to
lag
r
an
g
e
as
l
ag
r
an
g
e
is
n
o
t
v
er
y
co
m
p
ete
n
t
an
d
n
u
m
e
r
ically
u
n
s
tab
le
wh
en
th
er
e
is
ad
d
itio
n
o
f
n
ew
p
o
in
ts
(
L
ag
r
an
g
e
r
eq
u
ir
es
co
m
p
u
ti
n
g
th
e
p
o
ly
n
o
m
ial
ag
ain
,
f
r
o
m
s
cr
atch
)
with
th
e
r
eq
u
ir
em
en
t
o
f
h
ig
h
e
r
in
ter
p
o
latio
n
d
e
g
r
ee
.
T
h
e
r
ef
o
r
e,
New
to
n
is
th
e
ch
o
ice
o
f
h
an
d
lin
g
th
is
ty
p
e
o
f
d
ata
in
in
te
r
p
o
latin
g
th
ese
d
ata
in
cr
em
en
tally
.
T
ak
i
n
g
th
e
lin
ea
r
eq
u
atio
n
o
f
n
ewto
n
d
iv
id
ed
d
if
f
er
e
n
ce
(
NDD)
in
ter
p
o
l
ato
r
,
th
e
q
u
a
d
r
atic
in
ter
p
o
latan
t o
f
th
e
s
am
e
p
o
ly
n
o
m
ial
in
ter
p
o
lato
r
ca
n
b
e
s
ig
n
if
ied
a
s
f
o
llo
w
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
3
,
Sep
tem
b
er
2
0
2
1
:
1
7
0
8
-
1
7
1
7
1710
2
(
)
=
1
(
)
+
2
(
−
0
)
(
−
1
)
=
0
+
1
(
−
0
)
+
2
(
−
0
)
(
−
1
)
(
1
)
T
h
er
ef
o
r
e,
th
e
s
ec
o
n
d
d
e
g
r
ee
s
eg
m
en
t,
2
(
2
)
o
r
2
will b
e
d
en
o
ted
as
:
2
(
2
)
=
1
(
)
+
2
(
2
−
0
)
(
2
−
1
)
=
0
+
1
(
2
−
0
)
+
2
(
2
−
0
)
(
2
−
1
)
=
2
(
2
)
Sin
ce
th
en
,
th
e
s
ec
o
n
d
d
e
g
r
ee
co
ef
f
icien
t,
2
ca
n
b
e
e
v
alu
ated
as:
2
=
2
−
1
2
−
1
−
1
−
0
1
−
0
×
1
2
−
1
=
1
−
0
2
−
1
≡
2
0
(
3
)
Usi
n
g
(
3
)
,
a
n
y
h
i
g
h
er
d
eg
r
ee
c
o
ef
f
icien
t c
an
b
e
d
ef
i
n
ed
as:
=
−
1
1
−
−
1
0
−
1
≡
0
(
4
)
Hen
ce
,
(
1
)
ca
n
b
e
r
ewr
itten
as:
2
(
)
=
0
+
0
(
−
0
)
+
2
0
(
−
0
)
(
−
1
)
(
5
)
W
ith
,
0
=
1
−
0
1
−
0
(
6
)
a
nd
2
0
=
2
−
1
2
−
1
−
1
−
0
1
−
0
×
1
2
−
1
or
1
−
0
2
−
1
(
7
)
E
ac
h
o
f
th
e
d
e
r
iv
ativ
e
tab
le,
0
an
d
2
0
ar
e
im
p
lem
en
ted
as
lo
o
k
u
p
tab
les.
I
n
an
o
th
er
o
p
tio
n
,
t
h
e
s
ec
o
n
d
d
eg
r
ee
in
ter
p
o
lato
r
p
o
r
tio
n
,
2
0
m
ay
n
o
t
r
eq
u
ir
e
d
ed
ica
ted
lo
o
k
u
p
tab
le
as
it
m
ay
b
e
g
en
er
ated
o
n
-
th
e
-
f
ly
u
s
in
g
th
e
f
ir
s
tly
cr
ea
te
d
lin
ea
r
tab
le,
0
.
Ho
wev
er
,
th
is
o
p
tio
n
will
n
ee
d
ex
tr
a
ad
d
iti
o
n
a
n
d
d
iv
is
io
n
o
p
er
atio
n
f
o
r
ea
ch
g
en
er
atio
n
o
f
2
0
v
alu
e.
T
h
is
ac
tio
n
m
ig
h
t
s
ac
r
if
ice
th
e
ar
ea
an
d
th
e
s
p
ee
d
o
f
th
e
d
esig
n
o
n
s
ilico
n
u
p
o
n
th
e
a
d
d
itio
n
al
o
p
er
atio
n
al
u
n
its
u
s
ed
f
o
r
th
e
p
u
r
p
o
s
e.
T
h
er
ef
o
r
e,
th
e
f
o
r
m
e
r
o
p
tio
n
is
s
elec
ted
f
o
r
th
is
wo
r
k
.
Fo
r
a
f
air
co
m
p
ar
is
o
n
,
th
e
q
u
a
d
r
atic
in
ter
p
o
latan
t
f
o
r
T
ay
lo
r
in
ter
p
o
lato
r
as
b
ee
n
u
s
ed
i
n
E
u
r
o
p
ea
n
lo
g
ar
ith
m
ic
m
icr
o
p
r
o
ce
s
s
o
r
(
E
L
M)
[
2
]
was
also
ev
alu
ated
in
th
is
wo
r
k
.
T
h
e
e
q
u
atio
n
f
o
r
T
ay
lo
r
in
ter
p
o
lato
r
u
p
to
a
s
ec
o
n
d
d
e
g
r
ee
ca
n
b
e
r
ep
r
esen
ted
a
s:
(
)
=
(
0
)
+
′
(
0
)
(
−
0
)
+
"
(
0
)
2
(
−
0
)
2
(
8
)
o
r
s
u
m
m
ar
ized
as:
(
)
=
∑
(
0
)
!
(
−
0
)
=
0
(
9
)
with
n
as
th
e
d
eg
r
ee
o
f
th
e
p
o
ly
n
o
m
ial.
I
n
th
e
m
ea
n
tim
e,
f
o
r
=
l
og
2
(
2
+
1
)
,
th
e
f
ir
s
t
d
er
iv
ativ
e
is
g
iv
en
as:
′
(
)
=
2
2
+
1
(
1
0
)
an
d
th
e
s
ec
o
n
d
d
e
r
iv
ativ
e
as:
"
(
)
=
2
(
2
+
1
)
2
(
1
1
)
T
h
er
ef
o
r
e,
(
8
)
ca
n
b
e
r
ewr
itte
n
as:
2
(
)
=
(
0
)
+
2
2
+
1
(
−
0
)
+
2
2
(
2
+
1
)
2
(
−
0
)
2
(
1
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Les
s
mem
o
r
y
a
n
d
h
ig
h
a
cc
u
r
a
cy
lo
g
a
r
ith
mic
n
u
mb
er sys
tem
a
r
ch
itectu
r
e
fo
r
…
(
S
iti Za
r
in
a
Md
N
a
z
ir
i
)
1711
B
ased
o
n
th
is
eq
u
atio
n
,
ea
ch
o
f
th
e
d
i
f
f
er
en
tial
tab
les
ar
e
g
en
er
ated
an
d
s
to
r
ed
i
n
to
lo
o
k
u
p
tab
les.
Fo
r
T
ay
lo
r
in
ter
p
o
lato
r
,
L
UT
i
s
th
e
o
n
ly
m
eth
o
d
th
at
ca
n
b
e
u
s
ed
in
a
p
p
r
o
x
im
atin
g
th
e
f
i
n
a
l
v
alu
e
o
f
th
e
L
NS
ad
d
itio
n
an
d
s
u
b
tr
ac
tio
n
.
3.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
is
wo
r
k
f
o
cu
s
s
ed
o
n
th
e
i
m
p
r
o
v
e
m
en
ts
o
f
th
e
lo
g
a
r
ith
m
ic
ar
ith
m
etic
u
n
it
d
esig
n
in
[
1
1
]
b
y
en
h
an
cin
g
th
e
two
im
p
o
r
tan
t
p
r
o
ce
d
u
r
es
f
o
r
th
e
L
NS
ad
d
itio
n
an
d
s
u
b
tr
ac
tio
n
:
in
te
r
p
o
latio
n
a
n
d
c
o
-
tr
an
s
f
o
r
m
atio
n
.
T
h
e
n
ew
ar
r
a
n
g
em
en
t
o
f
th
e
two
p
r
o
ce
d
u
r
es
w
o
u
ld
b
e
ab
le
to
im
p
r
o
v
e
th
e
ad
d
itio
n
an
d
s
u
b
tr
ac
tio
n
o
p
er
atio
n
in
L
NS,
wh
ich
co
u
ld
r
ep
r
esen
t
a
wh
o
le
n
ew
lo
g
ar
ith
m
ic
ar
ith
m
etic
u
n
it
ar
ch
itectu
r
e.
T
h
e
ar
r
an
g
em
en
ts
o
f
t
h
ese
p
r
o
ce
d
u
r
es
ca
n
b
e
r
ep
r
esen
ted
b
y
th
e
f
u
n
ctio
n
(
)
in
Fig
u
r
e
1
,
wh
ich
illu
s
tr
ates
th
e
r
r
eg
io
n
with
d
ed
icate
d
p
r
o
ce
d
u
r
es in
v
o
lv
ed
in
p
o
s
itiv
e
r
eg
io
n
o
f
r
.
Fig
u
r
e
1
.
I
n
ter
p
o
latio
n
an
d
co
-
tr
an
s
f
o
r
m
atio
n
p
r
o
ce
d
u
r
e
ac
co
r
d
in
g
to
r
eg
io
n
f
o
r
th
e
n
ew
L
NS a
d
d
itio
n
an
d
s
u
b
tr
ac
tio
n
ar
ch
itectu
r
e
d
esig
n
T
h
e
p
r
o
ce
s
s
o
f
d
esig
n
v
alid
ati
o
n
r
eq
u
i
r
es
s
p
ec
if
ic
s
im
u
latio
n
to
o
ls
f
o
r
ea
ch
p
u
r
p
o
s
e.
T
h
e
r
ef
o
r
e,
th
e
th
e
ad
d
itio
n
an
d
s
u
b
t
r
ac
tio
n
o
p
er
atio
n
s
L
NS
d
esig
n
i
n
th
i
s
wo
r
k
h
ad
g
o
n
e
th
r
o
u
g
h
th
e
s
im
u
latio
n
p
r
o
ce
s
s
u
s
in
g
s
p
ec
ially
m
o
d
elled
s
im
u
lato
r
p
r
o
g
r
am
s
with
th
e
co
n
tr
o
l
o
f
ap
p
r
o
p
r
iate
d
ata
an
d
r
esu
lts
f
r
o
m
th
e
p
r
ev
io
u
s
L
NS
d
esig
n
.
T
h
e
s
im
u
lato
r
s
wer
e
d
esig
n
ed
to
p
e
r
ce
iv
e
th
e
b
est
lo
o
k
u
p
tab
le
a
r
r
an
g
em
e
n
ts
f
o
r
th
e
in
ter
p
o
lato
r
an
d
c
o
-
tr
an
s
f
o
r
m
a
tio
n
p
r
o
ce
d
u
r
e
i
n
ac
h
iev
in
g
th
e
B
T
FP
r
ate.
T
h
e
s
ize
a
n
d
t
h
e
n
u
m
b
er
o
f
lo
o
k
u
p
tab
les ca
n
b
e
m
o
d
if
ied
r
e
p
ea
te
d
ly
an
d
ac
co
r
d
i
n
g
ly
u
n
til it m
ee
ts
th
e
d
esig
n
’
s
ex
p
ec
tatio
n
.
T
h
e
L
NS
d
esig
n
s
im
u
lato
r
p
r
o
g
r
am
s
f
o
r
b
o
th
ar
ith
m
etic
o
p
er
atio
n
s
wer
e
co
n
s
tr
u
cte
d
in
C
lan
g
u
ag
e
an
d
th
e
ex
ec
u
tio
n
o
f
th
e
co
m
p
ilatio
n
p
r
o
ce
s
s
wer
e
d
o
n
e
u
s
in
g
Dev
-
C
C
o
m
p
iler
in
I
n
tel
C
o
r
e
i7
p
r
o
ce
s
s
o
r
.
T
h
e
ex
ec
u
tio
n
o
f
th
ese
p
r
o
g
r
am
s
will
allo
w
th
e
m
ea
s
u
r
em
en
t
o
f
t
h
e
wo
r
s
t
-
ca
s
e
er
r
o
r
f
o
r
ea
ch
lo
o
k
u
p
tab
le
co
m
b
in
atio
n
.
T
h
e
b
est
tab
le
s
ize
co
m
b
in
atio
n
s
f
o
r
th
e
in
ter
p
o
latio
n
p
r
o
ce
d
u
r
e
ar
e
r
etr
iev
e
d
f
r
o
m
a
n
u
m
b
e
r
o
f
co
m
p
ilatio
n
s
b
y
t
h
e
v
ar
io
u
s
tab
le
ar
r
an
g
e
m
en
ts
with
th
e
lim
it
o
f
ac
cu
r
ac
y
with
in
th
e
FLP
b
o
u
n
d
ar
ies.
T
h
ese
s
im
u
lato
r
s
also
allo
wed
th
e
m
o
d
if
icatio
n
o
f
v
ar
ia
b
les
as
s
tat
ed
in
T
ab
le
1
.
T
h
ese
tab
les
wh
ich
ar
e
lab
elled
as
F,
D
,
an
d
S a
r
e
u
s
ed
in
at
m
o
s
t
s
ix
s
eg
m
en
ted
r
an
g
es wh
ich
i
m
p
lied
th
e
co
n
ce
p
t o
f
p
o
we
r
-
of
-
two
p
ar
titi
o
n
s
.
Fig
u
r
e
2
d
escr
ib
es
th
e
d
ev
elo
p
m
en
t
o
f
t
h
e
s
im
u
lato
r
p
r
o
g
r
a
m
s
wh
ich
in
clu
d
es
th
e
m
ain
e
lem
en
ts
o
f
th
e
s
im
u
lato
r
.
T
h
e
p
r
o
ce
s
s
b
eg
an
with
th
e
d
esig
n
o
f
th
e
ex
p
o
n
e
n
t
an
d
lo
g
ar
ith
m
f
u
n
ctio
n
s
th
at
wer
e
em
b
ed
d
e
d
an
d
u
s
ed
th
r
o
u
g
h
o
u
t
th
e
s
im
u
latio
n
s
.
Nex
t
was
th
e
p
r
o
ce
s
s
o
f
d
escr
ib
in
g
th
e
i
n
ter
p
o
lato
r
an
d
c
o
-
tr
an
s
f
o
r
m
atio
n
m
o
d
el.
No
te
t
h
at
th
e
in
ter
p
o
lato
r
m
o
d
el
co
v
er
s
th
e
wh
o
le
r
an
g
e
o
f
r
f
o
r
L
NS
ad
d
itio
n
an
d
s
u
b
tr
ac
tio
n
f
u
n
ctio
n
,
e
x
ce
p
t
f
o
r
th
e
s
u
b
tr
ac
tio
n
f
u
n
ctio
n
t
h
at
allo
ca
tes
ce
r
tain
r
an
g
e
f
o
r
co
-
tr
an
s
f
o
r
m
atio
n
r
eg
io
n
o
n
ly
.
T
h
er
e
f
o
r
e,
th
e
co
-
tr
an
s
f
o
r
m
atio
n
m
o
d
el
was
s
p
ec
ially
d
esig
n
ed
to
co
m
p
u
te
t
h
e
d
if
f
e
r
en
ce
,
r
th
a
t
f
alls
in
to
th
e
r
eg
i
o
n
(
t
h
e
r
eg
i
o
n
m
ay
r
an
g
e
f
r
o
m
r
=
0
u
p
t
o
r
=
2
)
.
Fo
r
tab
le
co
m
p
u
tatio
n
p
u
r
p
o
s
es,
a
s
p
ec
ial
m
o
d
u
le
was
also
d
esig
n
ed
t
o
g
en
er
ate
th
e
v
alu
es
f
o
r
t
h
e
lo
o
k
u
p
tab
les
u
s
ed
in
th
e
in
t
er
p
o
latio
n
a
n
d
co
-
tr
an
s
f
o
r
m
atio
n
f
u
n
ctio
n
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
3
,
Sep
tem
b
er
2
0
2
1
:
1
7
0
8
-
1
7
1
7
1712
T
ab
le
1
.
Simu
latio
n
v
ar
iab
les
f
o
r
th
e
i
n
ter
p
o
lato
r
P
a
r
a
me
t
e
r
D
e
scri
p
t
i
o
n
F
S
t
o
r
e
d
f
u
n
c
t
i
o
n
v
a
l
u
e
a
t
r
n
D
S
t
o
r
e
d
f
u
n
c
t
i
o
n
o
f
l
i
n
e
a
r
d
e
r
i
v
a
t
i
v
e
a
t
r
n
S
S
t
o
r
e
d
f
u
n
c
t
i
o
n
o
f
s
e
c
o
n
d
d
e
g
r
e
e
d
e
r
i
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Fig
u
r
e
2
.
Simu
lato
r
d
esig
n
f
lo
w
f
o
r
L
NS a
d
d
itio
n
an
d
s
u
b
tr
a
ctio
n
B
ased
o
n
th
e
r
eg
i
o
n
in
d
icate
d
b
y
r
,
t
h
e
n
ex
t
p
r
o
ce
s
s
will
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e
th
e
g
en
er
atio
n
o
f
th
e
ap
p
r
o
x
im
atio
n
r
esu
lts
f
o
r
th
e
L
NS
ad
d
itio
n
a
n
d
s
u
b
tr
ac
tio
n
f
u
n
ctio
n
s
.
At
t
h
e
s
am
e
tim
e,
th
e
e
x
ac
t
r
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lt
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f
r
was
co
m
p
u
ted
th
r
o
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g
h
th
e
FLP r
esu
lt m
o
d
u
le.
T
h
is
v
alu
e
will b
e
co
m
p
ar
ed
with
th
e
ap
p
r
o
x
im
ated
r
es
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lt
in
th
e
n
ex
t m
o
d
u
le.
T
h
e
co
m
p
ar
is
o
n
will
ex
p
o
s
e
th
e
ac
cu
r
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y
o
f
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h
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ap
p
r
o
x
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ated
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wh
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icate
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th
e
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r
ec
is
io
n
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th
e
d
ev
elo
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e
d
L
NS sy
s
tem
.
4.
RE
SU
L
T
S
AND
D
I
SCU
SS
I
O
N
T
h
e
an
aly
s
is
co
n
ce
n
tr
ates
o
n
t
h
e
im
p
lem
en
tatio
n
o
f
a
s
ec
o
n
d
d
eg
r
ee
f
o
r
v
ar
i
o
u
s
i
n
ter
p
o
lat
o
r
s
.
T
h
r
ee
in
ter
p
o
lato
r
tab
les
ar
e
in
v
o
lv
ed
,
wh
ich
ar
e
F,
D
an
d
S
tab
le
with
n
u
ll
in
v
o
lv
em
e
n
t
o
f
t
h
e
er
r
o
r
co
r
r
ec
tio
n
s
ch
em
e
f
o
r
th
e
s
ec
o
n
d
d
eg
r
ee
in
ter
p
o
lato
r
-
b
ased
d
esig
n
.
A
s
th
e
r
ea
s
o
n
p
o
i
n
ted
o
u
t
in
i
n
tr
o
d
u
ctio
n
s
ec
tio
n
,
o
n
ly
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ter
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o
lato
r
s
wer
e
s
e
lecte
d
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o
r
f
u
r
th
er
i
m
p
lem
en
tat
io
n
test
in
g
wh
ich
ar
e
T
a
y
lo
r
a
n
d
New
to
n
d
i
v
id
ed
d
if
f
er
en
ce
in
ter
p
o
lato
r
.
As
th
e
m
ea
n
s
t
o
m
ea
s
u
r
e
th
e
ac
cu
r
a
cy
o
f
th
e
L
NS
s
y
s
tem
a
n
d
to
co
m
p
ar
e
it
with
th
e
FLP
s
y
s
tem
,
th
e
m
ath
em
atica
l
ex
p
r
ess
io
n
s
as
d
ef
in
ed
in
[
2
]
ar
e
ad
o
p
ted
.
T
h
e
a
n
aly
s
is
d
ea
ls
with
v
ar
io
u
s
len
g
th
s
o
f
g
u
ar
d
b
its
.
T
ab
le
2
co
n
v
ey
s
th
e
ac
c
u
r
ac
y
o
f
ea
c
h
d
esig
n
ac
co
r
d
in
g
to
th
e
in
ter
p
o
lato
r
s
an
d
v
ar
io
u
s
n
u
m
b
er
o
f
g
u
ar
d
b
its
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Les
s
mem
o
r
y
a
n
d
h
ig
h
a
cc
u
r
a
cy
lo
g
a
r
ith
mic
n
u
mb
er sys
tem
a
r
ch
itectu
r
e
fo
r
…
(
S
iti Za
r
in
a
Md
N
a
z
ir
i
)
1713
T
ab
le
2
.
Ma
x
im
u
m
r
elativ
e
e
r
r
o
r
f
o
r
L
NS a
d
d
itio
n
an
d
s
u
b
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tio
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ter
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d
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r
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e
l
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(
h
i
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h
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5
6
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4
2
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1
I
n
th
is
an
aly
s
is
,
th
e
s
ize
o
f
F,
D
an
d
S
tab
le
u
s
ed
f
o
r
ea
c
h
in
ter
p
o
lato
r
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e
f
ix
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to
2
5
6
wo
r
d
s
.
T
h
u
s
,
th
e
f
o
ca
l
f
ac
to
r
o
f
th
is
an
aly
s
is
is
th
e
s
ize
o
f
g
u
ar
d
b
its
.
B
y
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ar
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g
th
e
g
u
ar
d
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its
,
i
t
is
f
o
u
n
d
th
at
th
e
s
u
b
tr
ac
tio
n
o
p
e
r
atio
n
o
f
L
NS
u
s
in
g
T
ay
lo
r
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n
ter
p
o
lato
r
c
o
u
l
d
n
o
t
ac
h
iev
e
th
e
FLP
s
tan
d
ar
d
o
f
0
.
5
u
.
l.p
.
ev
en
with
th
e
u
s
ag
e
o
f
s
ix
g
u
a
r
d
b
i
ts
.
T
h
is
is
d
u
e
to
th
e
f
ac
t
th
at
th
e
ap
p
r
o
x
im
atio
n
b
y
T
ay
lo
r
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s
co
n
ce
n
tr
ated
at
a
s
p
ec
if
ic
p
o
in
t
wh
ich
u
s
u
ally
p
r
o
v
id
e
in
ac
c
u
r
ate
ap
p
r
o
x
i
m
atio
n
s
as
th
e
n
ew
p
o
in
t
m
o
v
es
awa
y
f
r
o
m
th
e
p
ar
ticu
lar
p
o
in
t
[2
4
]
.
T
h
is
co
n
d
itio
n
ev
e
n
ap
p
lies
f
o
r
h
ig
h
er
d
eg
r
ee
p
o
ly
n
o
m
ial.
T
h
u
s
,
th
e
s
itu
atio
n
lim
its
th
e
T
ay
lo
r
p
o
ly
n
o
m
ial
to
o
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ly
ap
p
r
o
x
im
ate
n
u
m
b
er
s
th
at
is
clo
s
e
to
its
in
itial p
o
in
t.
Ho
wev
er
,
th
e
s
am
e
d
esig
n
was
ab
le
to
ac
h
iev
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th
e
s
ta
n
d
ar
d
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s
in
g
New
to
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d
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ed
d
if
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ce
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ter
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o
lato
r
with
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aller
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te
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t
o
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g
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ar
d
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its
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wh
ich
in
th
i
s
ca
s
e
is
o
f
o
n
ly
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r
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u
a
r
d
b
its
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T
h
e
p
r
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p
o
s
ed
d
esig
n
p
r
o
d
u
ce
d
+0
.
4
5
1
4
o
f
m
ax
im
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m
r
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er
r
o
r
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wh
ic
h
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th
e
r
a
n
g
e
o
f
th
e
b
etter
-
th
an
-
f
lo
ati
ng
-
p
o
in
t
(
B
T
FP
)
r
ate.
I
t
s
h
o
u
ld
b
e
n
o
ted
th
at
th
e
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elativ
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er
r
o
r
o
f
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n
o
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s
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t
er
p
o
lato
r
s
is
n
o
t
t
h
e
m
ain
is
s
u
e
in
th
is
wo
r
k
s
in
ce
th
e
s
u
b
tr
ac
tio
n
f
u
n
ctio
n
co
n
tr
o
ls
th
e
m
ax
im
u
m
er
r
o
r
r
ate
o
f
th
ese
two
co
m
p
le
x
L
NS
f
u
n
ctio
n
s
ca
u
s
ed
b
y
co
-
t
r
an
s
f
o
r
m
atio
n
.
T
h
e
m
em
o
r
y
c
o
n
s
u
m
p
tio
n
an
aly
s
is
p
u
t
m
o
r
e
f
o
cu
s
o
n
th
e
L
NS
s
u
b
tr
ac
tio
n
d
esig
n
with
New
to
n
d
iv
id
ed
d
if
f
er
e
n
ce
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ter
p
o
lato
r
s
in
ce
it
h
as
p
r
o
v
id
ed
th
e
m
o
s
t
o
p
tim
u
m
ac
cu
r
ac
y
a
m
o
n
g
o
th
e
r
in
ter
p
o
lato
r
s
b
ased
o
n
th
e
im
p
lem
en
t
atio
n
o
f
s
ec
o
n
d
d
eg
r
ee
in
ter
p
o
lato
r
en
v
ir
o
n
m
en
t.
T
ab
le
3
s
u
m
m
ar
izes
th
e
s
to
r
ag
e
r
eq
u
ir
ed
f
o
r
m
em
o
r
y
tab
le
s
f
o
r
L
NS
ad
d
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n
an
d
s
u
b
tr
ac
tio
n
d
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n
s
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s
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g
f
ir
s
t a
n
d
s
ec
o
n
d
d
eg
r
ee
o
f
t
h
e
in
ter
p
o
lato
r
.
T
ab
le
3.
C
o
m
p
a
r
is
o
n
o
f
s
to
r
ag
e
r
eq
u
ir
em
e
n
ts
f
o
r
L
NS a
d
d
itio
n
an
d
s
u
b
tr
ac
ti
o
n
o
p
er
atio
n
o
f
v
ar
io
u
s
d
eg
r
ee
New
to
n
d
iv
id
ed
d
if
f
er
e
n
ce
in
t
er
p
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lato
r
with
m
u
ltip
le
r
an
g
e
o
f
co
-
tr
a
n
s
f
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r
m
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n
D
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g
n
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a
n
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n
To
t
a
l
Ta
b
l
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r
g
a
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a
t
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#
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t
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b
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m
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<
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at
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tly
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r
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it
s
to
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if
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ten
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f
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ly
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r
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f
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ter
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m
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I
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J
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3
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ir
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eg
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u
r
e
3
d
e
m
o
n
s
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ates th
at
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em
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e
n
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u
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3
.
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µ
m
tech
n
o
lo
g
y
.
T
ab
le
4
s
h
o
ws
th
e
an
aly
s
is
o
f
r
elativ
e
er
r
o
r
b
y
co
m
p
ar
in
g
th
e
p
r
o
p
o
s
ed
d
esig
n
with
th
e
ab
o
v
e
-
m
en
tio
n
ed
L
N
S
d
esig
n
s
.
T
o
n
o
te,
th
ese
d
esig
n
s
s
et
th
e
s
am
e
r
es
tr
ictio
n
o
f
eq
u
iv
ale
n
t
FLP
ac
c
u
r
ac
y
o
f
0
.
5
u
.
l.p
.
B
ased
o
n
th
e
tab
le,
th
e
n
ewly
d
esig
n
ed
L
NS
a
d
d
itio
n
an
d
s
u
b
tr
ac
tio
n
o
p
er
atio
n
s
o
f
f
er
s
t
h
e
m
o
s
t
ac
cu
r
ate
r
esu
lts
as
c
o
m
p
ar
ed
to
th
e
two
o
th
er
d
esig
n
s
with
s
im
ilar
co
n
f
ig
u
r
atio
n
,
wh
ile
g
ain
in
g
th
e
l
o
west r
elativ
e
er
r
o
r
f
o
r
th
e
ad
d
itio
n
f
u
n
ctio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
Les
s
mem
o
r
y
a
n
d
h
ig
h
a
cc
u
r
a
cy
lo
g
a
r
ith
mic
n
u
mb
er sys
tem
a
r
ch
itectu
r
e
fo
r
…
(
S
iti Za
r
in
a
Md
N
a
z
ir
i
)
1715
T
ab
le
4
.
E
r
r
o
r
a
n
aly
s
is
o
f
p
r
o
p
o
s
ed
an
d
o
th
er
L
NS a
d
d
itio
n
a
n
d
s
u
b
tr
ac
tio
n
d
esig
n
s
with
s
im
ilar
co
n
f
ig
u
r
atio
n
a
n
d
d
esig
n
tech
n
o
lo
g
y
Er
r
o
r
F
u
n
c
t
i
o
n
ELM
[
2
]
C
o
l
e
m
a
n
& I
smai
l
[
10
]
P
r
o
p
o
se
d
D
e
s
i
g
n
R
e
l
e
r
r
o
r
(
n
s)
A
d
d
+
0
.
4
5
4
4
+
0
.
4
5
2
7
+
0
.
4
1
1
0
S
u
b
-
0
.
4
4
1
4
-
0
.
4
9
8
7
-
0
.
4
5
1
4
M
a
x
e
r
r
o
r
-
+
0
.
4
5
4
4
+
0
.
4
9
8
7
+
0
.
4
5
1
4
T
h
e
u
s
ag
e
o
f
New
to
n
d
iv
id
e
d
d
if
f
e
r
en
ce
in
ter
p
o
latio
n
u
p
to
a
s
ec
o
n
d
d
e
g
r
ee
h
ad
d
eliv
er
ed
m
o
r
e
ac
cu
r
ate
r
esu
lts
o
f
ad
d
itio
n
an
d
s
u
b
tr
ac
tio
n
o
f
L
NS
with
th
e
r
elativ
e
er
r
o
r
o
f
+
0
.
4
5
1
4
as
r
e
f
lecte
d
in
Fig
u
r
e
5
.
T
h
e
r
esu
lt
o
f
f
er
s
9
%
m
o
r
e
a
cc
u
r
ate
as
co
m
p
ar
ed
to
[
10
]
.
T
h
is
wo
r
k
also
b
ea
ts
th
e
ac
cu
r
ac
y
o
f
s
p
ec
ial
f
u
n
ctio
n
(
SF
)
-
b
ased
L
NS
d
esig
n
[2
6
]
an
d
ev
en
two
FLP
u
n
i
t
(
FP
U)
d
esig
n
s
[1
1
]
.
T
h
is
p
r
o
v
es
th
at
th
e
h
ig
h
e
r
th
e
d
eg
r
ee
o
f
in
ter
p
o
lato
r
u
s
ed
,
th
e
b
etter
th
e
ac
cu
r
ac
y
ac
h
iev
ed
,
as
ev
id
en
ce
d
b
y
p
r
ev
i
o
u
s
eq
u
ati
o
n
s
.
T
h
e
s
tatis
t
ics
al
s
o
d
em
o
n
s
tr
ates
th
at
L
NS
co
u
ld
o
f
f
er
b
etter
ac
c
u
r
ac
y
with
ac
h
iev
i
n
g
B
T
FP
r
ate.
Oth
er
th
an
th
at,
th
e
u
s
ag
e
o
f
h
i
g
h
er
in
ter
p
o
la
to
r
ca
n
b
e
a
s
u
b
s
titu
tio
n
o
f
th
e
er
r
o
r
co
r
r
ec
tin
g
s
ch
em
e,
wh
ich
is
p
u
r
p
o
s
ely
d
esig
n
ed
to
im
p
r
o
v
e
ac
c
u
r
ac
y
,
as
b
ee
n
in
teg
r
ate
d
with
th
e
f
ir
s
t
d
eg
r
ee
in
ter
p
o
lato
r
a
s
in
[
2
]
an
d
[
1
0
]
.
Ho
wev
er
,
th
e
r
esu
lts
m
ay
d
if
f
er
an
d
m
a
y
n
o
t a
p
p
licab
le
f
o
r
ea
ch
in
ter
p
o
lato
r
u
s
ed
.
Fig
u
r
e
5
.
Acc
u
r
ac
y
c
o
m
p
ar
is
o
n
o
f
p
r
o
p
o
s
ed
L
NS d
esig
n
wit
h
o
th
er
L
NS d
esig
n
s
an
d
FLU
s
On
an
o
th
e
r
asp
ec
t,
th
e
a
d
o
p
ti
o
n
o
f
New
to
n
d
i
v
id
ed
d
if
f
er
e
n
ce
in
ter
p
o
lato
r
u
p
to
t
h
e
s
ec
o
n
d
d
eg
r
e
e
in
th
e
n
ew
L
NS
d
esig
n
im
p
r
o
v
es
th
e
m
e
m
o
r
y
co
n
s
u
m
p
tio
n
o
f
th
e
in
te
r
p
o
latio
n
p
r
o
ce
s
s
o
f
t
h
is
wo
r
k
as
it
m
an
ag
ed
to
ac
h
iev
e
1
4
9
,
7
6
0
b
its
f
o
r
its
F,
D,
an
d
S
tab
l
e
s
to
r
ag
e.
T
h
o
s
e
tab
les
co
n
s
titu
te
with
th
e
d
er
iv
ativ
e
(
s
u
p
p
o
r
tin
g
in
ter
p
o
latio
n
d
e
g
r
ee
)
tab
les.
T
h
is
m
ar
k
s
an
o
v
e
r
all
s
to
r
ag
e
r
ed
u
ctio
n
o
f
5
1
%
o
f
[
2
]
a
n
d
6
%
o
f
[
10
]
as
illu
s
tr
ated
in
Fig
u
r
e
6
.
T
h
e
e
x
p
an
s
io
n
o
f
co
-
tr
an
s
f
o
r
m
atio
n
r
e
g
io
n
u
p
to
r
=
2
,
h
o
wev
er
,
h
a
d
ca
u
s
ed
a
s
lig
h
t
in
cr
em
en
t
o
f
co
-
t
r
an
s
f
o
r
m
atio
n
f
u
n
ctio
n
s
to
r
ag
e
o
f
9
.
6
%
(
2
,
0
4
8
b
its
)
as
co
m
p
a
r
ed
to
th
e
p
r
e
v
io
u
s
s
ec
o
n
d
o
r
d
er
co
-
tr
an
s
f
o
r
m
atio
n
as
a
r
esu
lt
o
f
a
b
ig
g
er
s
ize
o
f
co
-
tr
a
n
s
f
o
r
m
atio
n
tab
le
th
at
m
a
n
ag
ed
th
e
ex
ten
s
io
n
r
an
g
e.
I
n
r
etu
r
n
,
th
e
t
ab
le
s
ize
ass
o
ciate
s
with
th
e
in
ter
p
o
latio
n
p
r
o
ce
s
s
alo
n
e
o
n
ly
co
n
tr
ib
u
tes
8
6
%
o
f
to
tal
m
e
m
o
r
y
b
its
,
wh
ich
i
s
2
%
less
er
co
m
p
ar
ed
to
[
10
].
T
h
er
ef
o
r
e,
t
h
ese
o
u
tco
m
es
p
r
o
v
e
th
at
a
s
to
r
ag
e
-
ef
f
icien
t
L
NS
d
esig
n
co
u
ld
b
e
r
ea
lized
with
in
ter
p
o
lato
r
s
o
f
a
h
ig
h
er
d
eg
r
ee
with
s
o
m
e
m
o
d
if
icatio
n
s
o
n
th
e
alg
o
r
ith
m
s
tr
u
ctu
r
e
(
in
t
h
is
wo
r
k
,
th
e
s
ec
o
n
d
o
r
d
e
r
co
-
tr
a
n
s
f
o
r
m
atio
n
with
r
an
g
e
ex
p
a
n
s
io
n
)
in
o
r
d
e
r
to
g
ai
n
th
e
ac
cu
r
ac
y
o
f
f
er
e
d
b
y
th
e
h
ig
h
er
d
eg
r
ee
i
n
ter
p
o
latio
n
.
T
h
is
co
u
ld
r
e
d
u
ce
o
r
ev
en
d
is
m
is
s
th
e
in
itial
ass
u
m
p
tio
n
th
at
a
h
ig
h
er
d
eg
r
ee
in
ter
p
o
latio
n
c
o
u
ld
in
cr
ea
s
e
th
e
s
to
r
ag
e
u
s
ag
e
in
to
tal
d
u
e
to
th
e
f
ac
t
th
at
th
ese
d
eg
r
ee
s
will c
o
n
s
u
m
e
ex
tr
a
lo
o
k
u
p
tab
les.
Fig
u
r
e
6
.
Sto
r
a
g
e
co
n
s
u
m
p
tio
n
co
m
p
a
r
is
o
n
o
f
p
r
o
p
o
s
ed
a
n
d
o
th
er
L
NS a
d
d
itio
n
an
d
s
u
b
tr
ac
tio
n
d
esig
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
23
,
No
.
3
,
Sep
tem
b
er
2
0
2
1
:
1
7
0
8
-
1
7
1
7
1716
5.
CO
NCLU
SI
O
N
T
h
e
n
ew
im
p
lem
en
ted
L
NS
d
esig
n
h
as
s
h
o
wn
th
e
im
p
r
o
v
e
m
en
t
o
f
th
e
ex
ten
d
ed
r
a
n
g
e,
s
ec
o
n
d
o
r
d
er
co
-
tr
an
s
f
o
r
m
atio
n
an
d
in
ter
p
o
latio
n
f
u
n
ctio
n
in
th
e
p
o
s
itiv
e
r
eg
io
n
o
f
r
.
T
h
e
n
ew
L
N
S
d
esig
n
h
ad
b
ee
n
u
tili
zin
g
th
e
s
ec
o
n
d
d
eg
r
ee
in
ter
p
o
latio
n
,
w
h
ich
r
esu
lts
in
a
g
r
ea
t
im
p
r
o
v
e
m
en
t
in
ac
c
u
r
ac
y
.
T
h
e
d
esig
n
in
cr
ea
s
es
th
e
ac
cu
r
ac
y
b
y
th
e
r
an
g
e
o
f
2
%
to
9
%
as
co
m
p
ar
ed
to
th
e
m
o
s
t
r
ec
en
t
an
d
s
im
ilar
co
n
f
ig
u
r
atio
n
an
d
tech
n
o
lo
g
y
o
f
L
NS
d
esig
n
s
.
B
esid
es,
th
e
m
em
o
r
y
b
it
u
s
ag
e
d
u
r
in
g
in
ter
p
o
latio
n
p
r
o
c
ess
a
ls
o
ab
le
to
b
e
r
ed
u
ce
d
ev
e
n
th
o
u
g
h
th
e
n
u
m
b
er
is
n
o
t
t
o
o
s
ig
n
if
ican
t.
I
n
c
o
n
clu
s
io
n
,
th
e
en
h
a
n
ce
m
en
t
o
f
in
ter
p
o
latio
n
p
r
o
ce
s
s
o
f
f
er
s
L
NS
d
esig
n
wi
th
b
etter
ac
cu
r
ac
y
an
d
m
an
a
g
ab
le
m
em
o
r
y
co
n
s
u
m
p
tio
n
t
h
at
ca
n
b
e
b
e
n
ef
ited
b
y
th
e
im
a
g
e
p
r
o
ce
s
s
in
g
ap
p
li
ca
tio
n
s
,
with
L
I
P a
r
ea
s
in
p
ar
ti
cu
lar
.
RE
F
E
R
E
NC
E
S
[1
]
J.
N.
Co
lem
a
n
,
E.
I.
Ch
e
ste
r
,
C.
I.
S
o
f
tl
e
y
,
a
n
d
J.
Ka
d
le
c
,
"
Arith
m
e
ti
c
o
n
t
h
e
E
u
ro
p
e
a
n
lo
g
a
rit
h
m
ic
m
icro
p
ro
c
e
ss
o
r,
"
in
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Co
mp
u
ter
s
,
v
o
l.
4
9
,
n
o
.
7
,
p
p
.
7
0
2
-
7
1
5
,
J
u
ly
2
0
0
0
,
d
o
i
:
1
0
.
1
1
0
9
/
1
2
.
8
6
3
0
4
0
.
[2
]
J.
N.
Co
lem
a
n
,
e
t
a
l.
,
“
Th
e
Eu
ro
p
e
a
n
Lo
g
a
rit
h
m
ic
M
icro
p
r
o
c
e
so
r,
”
in
IEE
E
T
ra
n
s
a
c
ti
o
n
s
o
n
Co
m
p
u
ters
,
v
o
l.
5
7
,
n
o
.
4
,
p
p
.
5
3
2
-
5
4
6
,
A
p
ril
2
0
0
8
,
d
o
i:
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.
[3
]
J.
M
a
k
i
n
o
,
M
.
Taiji
,
T.
E
b
isu
z
a
k
i
,
a
n
d
D.
S
u
g
imo
to
,
“
G
RAPE
‐4
:
A
M
a
ss
iv
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ly
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ra
ll
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l
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ial‐P
u
r
p
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se
C
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p
u
ter
fo
r
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l
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d
y
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imu
lati
o
n
s,”
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J
.
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[4
]
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.
Z.
M
d
Na
z
iri
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R.
C.
Ism
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il
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a
n
d
A.
Y.
M
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h
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k
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ff,
"
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it
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re
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d
In
ter
n
a
ti
o
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C
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fer
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4
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[5
]
H.
G
o
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in
a
u
d
,
Y.
G
a
v
e
t,
J.
De
b
a
y
le,
a
n
d
J.
P
i
n
o
li
,
"
Co
lo
r
c
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rre
c
ti
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n
i
n
th
e
fra
m
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wo
rk
o
f
C
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h
m
ic
Im
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g
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P
ro
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e
ss
in
g
,
"
2
0
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1
7
th
I
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ter
n
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ti
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a
l
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mp
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g
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(I
S
PA
)
,
2
0
1
1
,
p
p
.
129
-
1
3
3
.
[6
]
M
.
Jo
u
rl
in
,
J.
Bre
u
g
n
o
t,
F
.
Itt
h
ir
a
d
,
M
.
Bo
u
a
b
d
e
l
lah
,
a
n
d
B.
Clo
s
s,
“
Ch
a
p
ter
2
-
Lo
g
a
rit
h
m
ic
Im
a
g
e
P
ro
c
e
ss
in
g
fo
r
Co
lo
r
Im
a
g
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s,”
in
A
d
v
a
n
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e
s
in
Im
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g
i
n
g
a
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d
El
e
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tro
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P
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s
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l
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p
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0
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8
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8
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-
8.
[7
]
K.
M
o
h
a
m
m
a
d
,
S
.
Ag
a
ian
,
a
n
d
F
.
Hu
d
so
n
,
“
Im
p
lem
e
n
tatio
n
o
f
Dig
it
a
l
El
e
c
tro
n
ic
Arith
m
e
ti
c
s
a
n
d
it
s
a
p
p
li
c
a
ti
o
n
i
n
ima
g
e
p
ro
c
e
ss
in
g
,
”
C
o
mp
u
ter
s
&
El
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c
trica
l
En
g
in
e
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rin
g
,
v
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l.
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o
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.
[8
]
M
.
G
.
Arn
o
ld
a
n
d
S
.
C
o
ll
a
n
g
e
,
"
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Re
a
l/
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m
p
lex
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ic
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m
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ste
m
ALU,"
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[9
]
R.
C.
Ism
a
il
a
n
d
J.
N.
C
o
lem
a
n
,
"
ROM
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s
LNS
,
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2
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0
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N.
C
o
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a
n
a
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d
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Ch
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Is
m
a
il
,
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LNS
with
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1
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o
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,
J.
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n
,
a
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d
J.
Dra
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De
sig
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Trad
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lo
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m
s,”
in
2
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ter
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[1
2
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T.
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t
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is,
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h
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p
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r,
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In
ter
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Aco
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st
ics
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[1
3
]
P
.
Lee
,
“
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lu
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f
a
Hy
b
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d
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m
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DCT/IDCT
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m
,
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in
2
0
0
5
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EE
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ter
n
a
t
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S
CAS.
2
0
0
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1
4
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7
2
2
.
[1
4
]
H.
Zh
a
n
g
,
H.
J.
Lee
,
a
n
d
S
.
-
B.
K
o
,
"
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icie
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t
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ix
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d
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late
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ro
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ss
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rs,"
2
0
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8
IEE
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In
ter
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a
ti
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CAS
.
2
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5
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3
5
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.
[1
5
]
F
.
Lai,
"
A
1
0
n
s
h
y
b
ri
d
n
u
m
b
e
r
s
y
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m
d
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ta
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ti
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n
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fo
r
d
ig
it
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l
sig
n
a
l
p
ro
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ss
in
g
sy
ste
m
s,"
i
n
IEE
E
J
o
u
r
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a
l
o
f
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o
li
d
-
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te Ci
rc
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[1
6
]
C.
Y.
S
h
e
n
g
,
R.
C.
Ism
a
il
,
S
.
Z.
M
.
Na
z
iri
,
M
.
N.
M
.
Isa
,
S
.
A.
Z.
M
u
ra
d
,
a
n
d
A
.
Ha
ru
n
,
“
Hy
b
ri
d
F
lo
a
ti
n
g
P
o
in
t/
Lo
g
a
rit
h
m
ic
Nu
m
b
e
r
S
y
ste
m
P
ro
c
e
ss
o
r,
”
in
IOP
Co
n
fer
e
n
c
e
S
e
rie
s:
M
a
ter
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ls
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c
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[1
7
]
M
.
G
.
Arn
o
ld
,
I.
Ko
u
re
tas
,
V.
P
a
li
o
u
ra
s,
a
n
d
A.
M
o
r
g
a
n
,
“
On
e
-
H
o
t
Re
sid
u
e
Lo
g
a
rit
h
m
ic
Nu
m
b
e
r
S
y
ste
m
s,”
2
0
1
9
IEE
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2
9
th
In
t.
S
y
mp
.
Po
we
r
T
imin
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M
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.
[1
8
]
M
.
G
.
Arn
o
ld
,
V
.
P
a
li
o
u
ra
s,
a
n
d
I.
Ko
u
re
tas
,
"
Im
p
lem
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ti
n
g
th
e
Re
sid
u
e
Lo
g
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ri
th
m
ic
N
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m
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S
y
ste
m
Us
i
n
g
In
terp
o
latio
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n
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Co
tran
sfo
rm
a
ti
o
n
,
"
i
n
IEE
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T
ra
n
sa
c
ti
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[1
9
]
B.
P
a
rh
a
m
i,
“
Co
m
p
u
ti
n
g
with
lo
g
a
rit
h
m
ic
n
u
m
b
e
r
sy
ste
m
a
rit
h
m
e
ti
c
:
Im
p
lem
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n
tatio
n
m
e
th
o
d
s
a
n
d
p
e
rfo
rm
a
n
c
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b
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fit
s,”
Co
m
p
u
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El
e
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n
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.
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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d
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J
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&
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2502
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S
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1717
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0
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S
.
Z.
M
.
Na
z
iri
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R.
C.
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a
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d
A.
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M
.
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h
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k
a
ff,
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2
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[2
1
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L.
V.
F
a
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se
tt
,
‘‘
Ap
p
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.,
2
0
0
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.
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2
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A.
S
.
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e
tze
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.
[2
3
]
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ira,
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n
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R
.
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í
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4
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2
0
1
1
.
[2
5
]
S
.
Z.
M
.
Na
z
iri
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R.
C.
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n
d
A.
Y.
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.
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h
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k
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ff,
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2
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5
IEE
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C
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6
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d
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e
m
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th
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h
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d
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g
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fro
m
Ne
wc
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stl
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Un
iv
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rsity
,
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ted
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g
d
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m
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in
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icro
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y
ste
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De
sig
n
.
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is
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o
w
a
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ro
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ss
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th
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a
c
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lt
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o
f
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tro
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En
g
i
n
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rin
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h
n
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lo
g
y
,
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rs
it
i
M
a
lay
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n
d
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g
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g
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d
in
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l
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it
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l
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s.
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is
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se
n
io
r
m
e
m
b
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f
th
e
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f
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c
tri
c
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l
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n
d
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e
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tr
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n
g
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rs
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E),
a
m
e
m
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sh
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m
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ter
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n
d
c
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ro
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g
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r
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g
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rs M
a
lay
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).
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h
d
N
a
z
r
in
Md
Is
a
is
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se
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tu
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r
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th
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g
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,
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a
lay
sia
P
e
rli
s
(Un
i
M
AP).
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h
a
s
j
o
in
e
d
th
e
u
n
iv
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rs
it
i
a
s
a
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tu
re
r
sin
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e
2
0
0
5
.
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re
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iv
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d
h
is
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S
c
.
d
e
g
re
e
in
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e
c
tri
c
a
l
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n
d
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lec
tro
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ic
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g
in
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e
r
in
g
with
h
o
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o
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rs
fro
m
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lej
Un
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rsiti
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n
o
lo
g
i
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n
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ss
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(KU
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THO) i
n
2
0
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3
,
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.
S
c
.
d
e
g
re
e
fro
m
Un
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e
rsiti
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a
in
s
M
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lay
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in
2
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5
a
n
d
t
h
e
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h
.
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d
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g
re
e
in
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ield
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ro
g
ra
m
m
a
b
le
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te
Arra
y
(F
P
G
A)
d
e
sig
n
fro
m
th
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v
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o
f
E
d
in
b
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g
h
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S
c
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tl
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n
d
in
2
0
1
3
.
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h
a
s
a
u
t
h
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re
d
m
o
re
t
h
a
n
4
0
p
u
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li
sh
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d
tec
h
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p
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p
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in
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ics
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n
d
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d
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n
.
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c
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rre
n
t
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se
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h
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ti
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in
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lu
d
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I
n
tern
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t
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f
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h
in
g
s
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o
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a
n
d
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d
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wit
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z
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h
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tri
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m
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f
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las
g
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w,
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i
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with
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n
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.
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P
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s.
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