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ab
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m
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f
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test
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ap
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s
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m
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f
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[
1
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a
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o
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v
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Pictu
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[
2
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.
MA
C
d
esig
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s
am
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th
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m
o
s
t
im
p
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r
tan
t
o
p
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n
s
(
lik
e
E
d
g
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Dete
ctio
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)
[
3
]
,
[
4
]
in
im
ag
e
p
r
o
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s
s
in
g
ap
p
licatio
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s
an
d
alg
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r
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m
s
.
I
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213
r
eq
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,
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e
d
ical
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v
ices
[
5
]
.
As
a
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o
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f
f
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s
p
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d
s
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en
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th
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d
esire
d
.
On
th
e
Xilin
x
Ver
tex
FP
GA
[
6
]
p
latf
o
r
m
,
a
2
D
co
n
v
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l
u
tio
n
f
r
am
ewo
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k
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r
o
p
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s
ed
to
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im
p
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W
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d
ev
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p
in
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ag
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tech
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iq
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with
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p
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[
7
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,
it
is
cr
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cial
f
o
r
em
b
ed
d
ed
s
y
s
tem
s
to
ev
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av
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lo
w
p
o
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co
n
s
u
m
p
tio
n
an
d
h
ig
h
th
r
o
u
g
h
p
u
t
[
8
]
.
T
h
er
e
ar
e
v
ar
i
o
u
s
s
tep
s
to
th
e
im
p
lem
en
tati
o
n
p
r
o
ce
s
s
[
9
]
.
T
h
e
tar
g
et
p
la
tf
o
r
m
is
t
h
e
Ver
te
x
FP
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an
d
h
ig
h
er
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io
n
s
.
E
v
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p
ix
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alu
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ch
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b
r
ig
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t
n
ess
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an
d
s
o
o
n
,
h
as
its
o
wn
m
ea
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in
g
[
1
0
]
.
Data
is
k
ep
t
in
a
m
atr
ix
f
o
r
m
a
t.
T
h
e
f
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s
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ir
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MA
C
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eg
r
ess
io
n
)
[
1
1
]
o
n
th
o
s
e
m
atr
ices a
r
e
th
en
e
x
ec
u
t
ed
u
s
in
g
a
k
er
n
el
s
elec
ted
b
y
t
h
e
u
s
er
.
T
h
e
r
em
ain
d
er
o
f
t
h
is
wo
r
k
is
ar
r
an
g
ed
in
th
e
f
o
llo
win
g
m
an
n
er
.
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h
e
d
esig
n
m
eth
o
d
o
lo
g
y
f
o
r
co
n
v
o
l
u
tio
n
o
p
e
r
at
o
r
is
in
t
r
o
d
u
ce
d
in
Sectio
n
2
.
T
h
e
p
r
o
p
o
s
ed
ar
ch
itectu
r
e
a
n
d
h
ar
d
war
e
i
m
p
lem
en
tatio
n
f
o
r
MA
C
d
esig
n
as
co
n
v
o
lu
tio
n
o
p
er
at
o
r
a
r
e
d
is
cu
s
s
ed
in
Sectio
n
3
.
Sectio
n
4
o
f
th
is
p
ap
er
e
x
p
lain
s
th
e
co
m
p
u
tatio
n
al
r
esu
lts
,
th
e
s
im
u
latio
n
d
ata
is
d
is
cu
s
s
ed
i
n
Secti
o
n
5
,
tr
ac
k
in
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s
y
s
tem
s
an
d
p
er
f
o
r
m
a
n
ce
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alu
atio
n
p
a
r
am
eter
s
ar
e
d
is
c
u
s
s
ed
in
Sectio
n
6
,
an
d
th
e
a
r
ticle’
s
co
n
clu
s
io
n
is
d
is
cu
s
s
ed
in
Sectio
n
7
.
2.
DE
S
I
G
N
M
E
T
H
O
DO
L
O
G
Y
I
m
ag
e
p
r
o
ce
s
s
in
g
is
u
s
ef
u
l
i
n
a
wid
e
r
an
g
e
o
f
s
itu
atio
n
s
[
1
2
]
,
[
1
3
]
.
Fo
r
p
ar
ticu
lar
,
wh
en
ev
er
a
n
im
ag
e
is
s
en
t
o
r
ac
q
u
ir
ed
,
o
r
wh
en
an
im
ag
e
is
co
m
p
r
ess
ed
,
n
o
is
e
s
ig
n
als
ar
e
ea
s
ily
in
jecte
d
in
to
th
e
o
r
i
g
in
al
im
ag
e.
As
a
r
esu
lt,
r
ed
u
cin
g
t
h
e
d
is
tu
r
b
an
ce
s
in
th
e
o
r
ig
i
n
a
l
im
ag
e
n
ec
ess
itates
an
ad
d
iti
o
n
al
s
tep
[
1
4
]
.
T
h
e
tech
n
iq
u
e
[
1
5
]
,
[
1
6
]
o
f
im
ag
e
f
ilter
s
is
cr
itical
in
d
ig
ital
im
ag
e
p
r
o
ce
s
s
in
g
.
A
k
e
r
n
el,
wh
ich
is
a
tin
y
ar
r
ay
ap
p
lied
to
ea
ch
n
eig
h
b
o
r
in
g
p
i
x
els
in
th
e
im
ag
e,
ca
n
b
e
u
s
ed
to
d
ef
in
e
a
f
ilter
.
T
h
e
k
er
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els
ce
n
tr
ic
ar
e
u
s
u
ally
alig
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ed
with
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cu
r
r
en
t
p
ix
el
th
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o
u
g
h
o
u
t
m
an
y
ap
p
licatio
n
s
.
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h
e
f
in
al
im
ag
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is
o
b
tain
ed
b
y
co
n
v
o
l
v
in
g
an
im
ag
e
with
th
e
k
er
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el.
Ker
n
el
m
atr
ices
p
lay
a
s
ig
n
if
ican
t
p
ar
t
in
th
e
co
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o
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tio
n
id
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a,
d
if
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er
en
t
k
er
n
el
m
atr
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p
r
o
d
u
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e
d
is
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ct
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a
g
e
r
esu
ltan
ts
.
B
lu
r
r
in
g
,
s
m
o
o
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h
in
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c
o
n
tr
ast
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ce
m
en
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o
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ased
o
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tio
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n
all
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e
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p
lis
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en
d
i
n
g
u
p
o
n
o
n
k
er
n
el
m
atr
ices selec
ted
[
1
7
]
,
[
1
8
]
.
T
h
e
I
m
a
g
e
p
i
x
el
p
r
i
n
cip
le
s
tatin
g
I
(
x
,
y
)
,
t
h
e
k
e
r
n
el
co
n
v
o
lu
ti
o
n
m
ea
s
u
r
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s
h
o
ws
K(
x
,
y
)
,
an
d
th
e
co
n
v
o
l
u
tio
n
r
esu
ltin
g
f
o
r
th
e
f
r
am
e
O(
x
,
y
)
.
T
h
e
c
o
n
v
o
lu
tio
n
tech
n
iq
u
e
is
d
e
p
icted
in
im
a
g
e
k
er
n
el
m
atr
ices
ar
e
r
eg
ar
d
e
d
3
*
3
in
Fig
u
r
e
1
,
as
well
a
s
im
ag
e
co
n
v
o
lu
tio
n
th
e
r
esu
ltan
t
m
atr
ices
co
n
v
o
lu
tio
n
is
p
r
o
v
id
ed
b
y
4
*
4
m
atr
ices.
T
h
e
r
esu
ltan
t
o
f
th
e
c
o
n
v
o
lu
tio
n
o
u
tp
u
t
v
alu
e
s
[
1
9
]
,
[
2
0
]
is
s
u
b
s
titu
ted
f
o
r
th
e
p
ix
els’
o
r
ig
i
n
al
v
alu
es,
an
d
th
e
r
esu
ltan
t
ar
r
a
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’
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p
o
r
tio
n
s
,
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a
r
e
th
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am
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s
ize
as
th
e
k
er
n
el,
wer
e
u
ltima
tely
av
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ag
ed
.
T
h
e
p
r
o
ce
s
s
will
b
e
r
ep
ea
ted
,
with
th
e
c
o
n
v
o
lu
tio
n
[
2
1
]
,
[
2
2
]
o
f
th
e
g
e
n
er
ated
v
al
u
es
r
ep
lacin
g
th
e
en
tire
p
ictu
r
e
in
th
e
m
atr
ices,
p
ix
el
v
alu
es.
T
h
e
co
n
v
o
lu
tio
n
p
ix
el
v
alu
e
r
esu
ltan
t
s
h
o
u
ld
b
e
0
wh
en
ev
er
th
e
k
er
n
el
p
ix
el
v
alu
e
is
o
u
ts
id
e
th
e
m
at
r
ix
.
T
h
e
b
lo
ck
is
f
ed
with
th
e
co
r
e
p
ix
el
v
alu
es
t
o
b
e
an
al
y
ze
d
,
as
well
as
its
n
eig
h
b
o
r
in
g
p
ix
els.
T
h
e
c
o
n
v
o
lu
tio
n
o
p
er
ato
r
is
u
s
ed
in
r
ea
l
-
tim
e
ap
p
licatio
n
s
f
o
r
v
ar
i
o
u
s
ed
g
e
d
etec
tio
n
alg
o
r
ith
m
s
[
2
3
]
,
[
2
4
]
an
d
also
ed
g
e
f
ilter
f
o
r
v
i
d
eo
p
r
o
ce
s
s
in
g
s
y
s
tem
o
n
r
ec
o
n
f
ig
u
r
ab
le
p
latf
o
r
m
[
2
5
]
,
[
2
6
]
.
F
i
g
u
r
e
1
.
M
a
t
r
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c
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s
o
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t
h
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c
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ar
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ated
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.
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ter
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ith
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ter
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u
r
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1
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.
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ice
Fig
u
r
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1
6
.
R
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R
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m
p
lem
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n
tatio
n
5.
CO
NCLU
SI
O
N
T
h
is
p
ap
er
d
is
cu
s
s
es
th
e
h
ar
d
war
e
im
p
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en
tatio
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f
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AC
d
esig
n
with
co
n
v
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l
u
tio
n
o
p
er
ato
r
in
Ver
ilo
g
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r
m
.
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h
e
s
u
g
g
es
ted
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ar
d
wa
r
e
d
esig
n
is
m
o
d
el
led
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Ver
ilo
g
an
d
s
y
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esize
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u
s
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an
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d
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g
et
d
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ice
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er
tex
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h
ig
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er
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s
SOC
.
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h
en
co
m
p
ar
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to
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n
v
e
n
tio
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al
ar
ch
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r
e,
cr
itical
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ath
tim
e
is
lo
wer
ed
m
o
r
e
in
th
is
d
e
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d
it
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s
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e
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r
o
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elay
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eter
m
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ed
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e
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s
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r
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o
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s
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e
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8
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r
6
0
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6
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,
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e
d
ela
y
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b
e
lo
n
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er
.
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h
e
r
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ltin
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e
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e
n
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tio
n
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ce
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u
r
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is
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m
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leted
.
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h
is
p
ap
er
p
r
e
d
o
m
i
n
an
tly
d
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ib
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n
ew
ar
c
h
ite
ctu
r
e
f
o
r
th
e
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C
im
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en
tatio
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n
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o
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o
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.
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ith
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y
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x
,
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U
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ck
s
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m
u
ltip
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itio
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iv
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io
n
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d
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o
n
tr
o
l
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g
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b
lo
ck
s
f
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o
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tr
o
l
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ig
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ls
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ch
s
tag
e
o
f
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ip
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s
tag
e,
it
is
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asic
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d
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f
icien
t
h
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d
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e
im
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ip
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ig
u
r
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m
a
n
d
h
el
p
s
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ed
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th
e
cr
itical
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ath
d
ela
y
.
ACK
NO
WL
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DG
M
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hi
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t
a
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e
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et
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s
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m
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ar
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e
ch
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o
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al
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n
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er
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i
ty
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T
U
)
in
B
e
la
g
a
vi
,
K
ar
n
at
a
ka
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I
n
di
a.
RE
F
E
R
E
NC
E
S
[1
]
T.
F
.
S
m
it
h
a
n
d
M
.
S
.
Wate
rm
a
n
,
“
Id
e
n
ti
fica
ti
o
n
o
f
c
o
m
m
o
n
m
o
lec
u
lar
su
b
se
q
u
e
n
c
e
s,”
J
o
u
rn
a
l
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219
[2
]
R.
Nik
h
il
,
“
Bl
u
e
sp
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c
S
y
ste
m
Ve
r
il
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g
:
e
fficie
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t,
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RTL
fr
o
m
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ig
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l
e
v
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sp
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c
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c
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[3
]
R
.
S
h
o
u
p
, “
P
a
ra
m
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teriz
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d
c
o
n
v
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l
u
ti
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n
fil
terin
g
in
a
field
p
ro
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ra
m
m
a
b
le g
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te arra
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in
ter
v
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l
,
”
Tec
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ica
l
Re
p
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rt
1
9
9
3
.
[4
]
H.
S
.
Ne
o
h
a
n
d
A
.
Ha
z
a
n
c
h
u
k
,
“
Ad
a
p
ti
v
e
e
d
g
e
d
e
tec
ti
o
n
fo
r
re
a
l
-
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m
e
v
id
e
o
p
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o
c
e
ss
in
g
u
si
n
g
F
P
G
A
s
,
”
Glo
b
a
l
S
ig
n
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l
Pro
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ss
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g
,
2
0
0
4
,
v
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l
.
7
,
n
o
.
3
,
p
p
.
2
-
3.
[5
]
J.
Wan
g
,
S
.
Z
h
o
n
g
,
L.
Ya
n
,
a
n
d
Z.
Ca
o
,
“
An
e
m
b
e
d
d
e
d
s
y
ste
m
-
on
-
c
h
ip
a
rc
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it
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c
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re
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l
-
ti
m
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v
isu
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l
d
e
tec
ti
o
n
a
n
d
m
a
tch
i
n
g
,
”
i
n
IE
EE
T
ra
n
sa
c
ti
o
n
s
o
n
C
irc
u
it
s
a
n
d
S
y
ste
ms
fo
r
Vi
d
e
o
T
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3
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2
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.
[6
]
P
.
M
o
n
d
a
l
,
P
.
B
iswa
l,
a
n
d
S
.
Ba
n
e
rjee
,
“
F
P
G
A
b
a
se
d
a
c
c
e
ler
a
ted
3
D
a
ffin
e
tran
sf
o
rm
f
o
r
r
e
a
l
-
ti
m
e
ima
g
e
p
ro
c
e
ss
in
g
a
p
p
li
c
a
ti
o
n
s,”
C
o
mp
u
t
.
El
e
c
tr.
En
g
.
,
v
o
l.
4
9
,
p
p
.
6
9
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8
3
,
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0
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6
,
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o
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0
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1
0
1
6
/
j.
c
o
m
p
e
lec
e
n
g
.
2
0
1
5
.
0
4
.
0
1
7
.
[7
]
E.
Ka
d
ric,
D.
La
k
a
ta,
a
n
d
A.
D
e
h
o
n
,
“
Im
p
a
c
t
o
f
p
a
ra
ll
e
li
sm
a
n
d
m
e
m
o
ry
a
rc
h
it
e
c
tu
re
o
n
f
p
g
a
c
o
m
m
u
n
ica
ti
o
n
e
n
e
rg
y
,
”
AC
M
T
r
a
n
s.
Rec
o
n
fi
g
u
r
a
b
le T
e
c
h
n
o
l
.
S
y
st
,
v
o
l.
9
,
n
o
.
4
,
2
0
1
6
,
d
o
i:
1
0
.
1
1
4
5
/2
8
5
7
0
5
7
.
[8
]
I.
Ka
u
r,
L.
R
o
h
il
la,
A.
Na
g
p
a
l
,
B
.
P
a
n
d
e
y
,
a
n
d
S
.
S
h
a
rm
a
,
“
Diffe
r
e
n
t
c
o
n
fig
u
ra
ti
o
n
o
f
lo
w
-
p
o
we
r
m
e
m
o
ry
d
e
sig
n
u
sin
g
c
a
p
a
c
it
a
n
c
e
sc
a
li
n
g
o
n
2
8
-
n
m
field
-
p
ro
g
ra
m
m
a
b
le
g
a
te
a
rra
y
,
”
In
:
M
u
tt
o
o
S
.
(e
d
s)
S
y
ste
m
a
n
d
Arc
h
it
e
c
tu
re
.
Ad
v
a
n
c
e
s i
n
In
tell
ig
e
n
t
S
y
ste
ms
a
n
d
C
o
mp
u
ti
n
g
,
v
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l
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2
.
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in
g
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p
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re
:
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:
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7
8
-
9
8
1
-
10
-
8
5
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3
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8
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1
5
.
[9
]
L.
P
e
z
z
a
ro
ss
a
,
A.
T.
Kriste
n
se
n
,
M
.
S
c
h
o
e
b
e
rl,
a
n
d
J.
S
p
a
rsø
,
“
Us
in
g
d
y
n
a
m
ic
p
a
rti
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l
re
c
o
n
fi
g
u
ra
ti
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n
o
f
F
P
G
As
in
Re
a
l
-
Ti
m
e
S
y
ste
m
s,”
M
icr
o
p
ro
c
e
ss
a
n
d
M
icr
o
sy
s
tem
s
,
v
o
l
.
6
1
,
p
p
.
1
9
8
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0
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8
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o
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0
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.
m
icp
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o
.
2
0
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8
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0
5
.
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1
7
.
[1
0
]
S
.
D.
Bro
wn
,
R
.
J.
F
ra
n
c
is,
J.
R
o
se
,
a
n
d
Z.
G
.
Vra
n
e
sic
,
Fi
e
ld
Pro
g
ra
mm
a
b
le Ga
te A
rr
a
y
s
,
Be
rli
n
:
S
p
rin
g
e
r
S
c
ien
c
e
&
Bu
sin
e
ss
M
e
d
ia,
1
9
9
2
.
[1
1
]
C.
T.
H
u
it
z
il
a
n
d
M
.
A.
N.
M
a
g
a
n
d
a
,
“
Are
a
ti
m
e
e
fficie
n
t
imp
le
m
e
n
tatio
n
o
f
lo
c
a
l
a
d
a
p
ti
v
e
ima
g
e
th
re
sh
o
l
d
i
n
g
i
n
re
c
o
n
fig
u
ra
b
le
h
a
rd
wa
re
,
”
AC
M
S
IGAR
CH
C
o
mp
u
t.
Arc
h
.
Ne
ws
,
v
o
l.
4
2
,
n
o
.
4
,
p
p
.
3
3
–
3
8
,
2
0
1
4
,
d
o
i:
1
0
.
1
1
4
5
/
2
6
9
3
7
1
4
.
2
6
9
3
7
2
1
.
[1
2
]
A.
S
u
n
g
h
e
e
th
a
a
n
d
R.
S
.
Ra
jen
d
ra
n
,
“
A
n
o
v
e
l
Ca
p
sN
e
t
b
a
se
d
ima
g
e
re
c
o
n
stru
c
ti
o
n
a
n
d
re
g
re
s
sio
n
a
n
a
ly
sis
,
”
J
o
u
rn
a
l
o
f
In
n
o
v
a
ti
v
e
Ima
g
e
Pro
c
e
ss
in
g
,
v
o
l.
2
,
n
o
.
0
3
,
p
p
.
1
5
6
-
1
6
4
,
Ju
l.
2
0
2
0
,
d
o
i:
1
0
.
3
6
5
4
8
/
ji
ip
.
2
0
2
0
.
3
.
0
0
6
.
[1
3
]
S
.
Du
tt
a
a
n
d
A.
Ba
n
e
rjee
,
“
Hig
h
ly
p
re
c
ise
m
o
d
ifi
e
d
b
l
u
e
wh
a
le
m
e
th
o
d
fra
m
e
d
b
y
b
len
d
i
n
g
b
a
t
a
n
d
lo
c
a
l
se
a
rc
h
a
lg
o
rit
h
m
fo
r
t
h
e
o
p
ti
m
a
li
t
y
o
f
i
m
a
g
e
fu
sio
n
a
l
g
o
rit
h
m
,
”
J
o
u
rn
a
l
o
f
S
o
ft
Co
mp
u
ti
n
g
Pa
r
a
d
i
g
m
,
v
o
l
.
2
,
n
o
.
0
4
,
p
p
.
195
-
2
0
8
,
2
0
2
0
,
d
o
i:
1
0
.
3
6
5
4
8
/
jsc
p
.
2
0
2
0
.
4
.
0
0
1
.
[1
4
]
P
.
Ly
sa
g
h
t,
B
.
Blo
d
g
e
t,
J
.
M
a
so
n
,
J.
Yo
u
n
g
,
a
n
d
B.
Bri
d
g
f
o
rd
,
“
In
v
it
e
d
p
a
p
e
r:
E
n
h
a
n
c
e
d
a
rc
h
it
e
c
tu
re
s,
d
e
sig
n
m
e
th
o
d
o
lo
g
ies
a
n
d
CAD
to
o
ls
f
o
r
d
y
n
a
m
ic
re
c
o
n
fi
g
u
ra
ti
o
n
o
f
Xi
li
n
x
F
P
G
As
,
”
2
0
0
6
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Fi
e
ld
Pro
g
ra
mm
a
b
le L
o
g
ic
a
n
d
A
p
p
li
c
a
ti
o
n
s
,
2
0
0
6
,
p
p
.
1
-
6
,
d
o
i:
1
0
.
1
1
0
9
/
F
P
L.
2
0
0
6
.
3
1
1
1
8
8
.
[1
5
]
G
.
Do
u
g
h
e
rty
,
“
Im
a
g
e
a
n
a
ly
sis
in
m
e
d
ica
l
ima
g
in
g
:
Re
c
e
n
t
a
d
v
a
n
c
e
s
in
se
lec
ted
e
x
a
m
p
les
,
”
Bi
o
me
d
Ima
g
in
g
In
ter
v
.
J
.
,
v
o
l.
6
,
n
o
.
3
,
p
p
.
E3
2
,
2
0
1
0
,
d
o
i:
1
0
.
2
3
4
9
/b
ii
j.
6
.
3
.
e
3
2
.
[1
6
]
J.
C.
Ru
ss
,
T
h
e
Ima
g
e
Pro
c
e
ss
in
g
Ha
n
d
b
o
o
k
,
6
th
Ed
.
,
F
lo
ri
d
a
:
CR
C
P
re
ss
,
2
0
1
1
.
[1
7
]
Z.
Na
v
a
b
i,
Dig
i
ta
l
De
sig
n
a
n
d
Imp
lem
e
n
ta
ti
o
n
wit
h
Fi
e
ld
Pro
g
ra
mm
a
b
le
De
v
ice
s
,
Bo
sto
n
:
Kl
u
we
r
Ac
a
d
e
m
ic
P
u
b
l
ish
e
rs,
2
0
0
5
.
[1
8
]
G
.
N.
Ch
iran
jee
v
i
a
n
d
S
.
Ku
l
k
a
rn
i,
“
P
ip
e
li
n
e
a
rc
h
it
e
c
tu
re
fo
r
N=
=
K*
2
L
Bit
m
o
d
u
lar
ALU:
Ca
se
stu
d
y
b
e
twe
e
n
c
u
rre
n
t
g
e
n
e
ra
ti
o
n
c
o
m
p
u
ti
n
g
a
n
d
v
e
d
ic
c
o
m
p
u
ti
n
g
,
”
2
0
2
1
6
t
h
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
f
o
r
Co
n
v
e
rg
e
n
c
e
in
T
e
c
h
n
o
l
o
g
y
(I
2
CT
)
,
2
0
2
1
,
p
p
.
1
-
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,
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1
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6
8
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2
0
2
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.
9
4
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7
9
1
7
.
[1
9
]
B.
S
.
Du
r
g
a
k
e
ri
a
n
d
G
.
N.
Ch
ira
n
jee
v
i,
“
Im
p
lem
e
n
ti
n
g
ima
g
e
p
ro
c
e
ss
in
g
a
lg
o
ri
th
m
s
u
si
n
g
x
il
i
n
x
s
y
ste
m
g
e
n
e
ra
to
r
with
re
a
l
ti
m
e
c
o
n
stra
in
ts,
”
2
0
1
9
4
t
h
In
ter
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2
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.
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3
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4
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5
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.
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6
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8
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