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Me
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C
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s
p
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A
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r
:
Ah
m
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Kh
azal
Yo
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is
Dep
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tm
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f
C
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p
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iq
1.
I
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RO
D
UCT
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N
B
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m
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im
ag
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is
n
o
t
ea
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to
d
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with
b
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f
co
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p
lex
n
atu
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f
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t
h
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im
ag
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T
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ev
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d
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if
f
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to
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d
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co
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d
itio
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s
in
th
ese
im
ag
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esp
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in
t
h
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im
ag
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T
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a
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th
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if
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On
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o
f
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way
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is
im
ag
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s
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m
en
tatio
n
.
I
m
ag
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clea
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f
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t
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is
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titi
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twar
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ap
p
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s
u
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as
Ma
tlab
[
1
]
.
On
th
e
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th
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h
an
d
,
th
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is
an
o
th
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f
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p
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r
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m
ab
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s
(
FP
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.
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GA
I
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p
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im
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ar
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th
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f
o
llo
wed
f
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s
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th
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f
im
ag
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p
r
o
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s
s
in
g
m
is
s
io
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[
2
]
.
On
t
h
e
o
th
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d
,
th
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ar
e
s
o
m
e
lim
itatio
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s
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ev
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ar
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u
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o
r
im
ag
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p
r
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ce
s
s
in
g
an
d
h
er
e
ar
e
s
o
m
e
e
x
am
p
les.
First,
wh
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FP
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s
u
s
ed
to
im
p
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t
im
ag
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f
ilter
,
th
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m
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p
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tr
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wh
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p
r
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s
s
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n
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p
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el
p
er
cl
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c
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cle
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th
at
will
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m
em
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r
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r
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b
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r
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f
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1308
p
ix
els
f
r
o
m
p
r
ev
io
u
s
im
ag
e
[
3
]
.
Seco
n
d
,
m
em
o
r
y
h
ier
a
r
ch
y
i
s
s
u
e
(
o
n
-
ch
ip
a
n
d
o
f
f
-
c
h
ip
m
e
m
o
r
y
)
w
h
er
e
th
er
e
ar
e
ad
v
an
ta
g
e
an
d
d
is
ad
v
an
ta
g
e
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o
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h
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f
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Fo
r
e
x
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m
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n
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ch
ip
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em
o
r
y
h
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tim
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at
th
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am
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tim
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h
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m
all
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ap
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p
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f
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o
r
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Dy
n
am
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m
em
o
r
y
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.
I
n
s
o
m
e
ca
s
es,
th
er
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is
n
o
o
p
tio
n
b
u
t
to
c
h
o
o
s
e
o
n
-
ch
ip
m
em
o
r
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esp
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wh
en
p
o
wer
c
o
n
s
u
m
p
tio
n
is
im
p
o
r
tan
t
[
4
]
.
Desp
ite
th
e
lim
itatio
n
s
an
d
d
if
f
icu
lties
in
FP
GA
im
p
lem
en
tatio
n
s
till
wo
r
th
b
ec
au
s
e
it
will
b
e
s
tan
d
-
alo
n
e
d
e
v
i
ce
b
y
its
elf
[
5
]
.
2.
RE
L
AT
E
D
WO
RK
T
h
e
wo
r
k
in
g
p
r
i
n
cip
le
o
f
lin
ea
r
f
ilter
s
d
e
p
en
d
s
o
n
th
e
ad
d
itio
n
an
d
m
u
ltip
licatio
n
[
6
]
.
T
h
e
r
e
ar
e
m
an
y
d
esig
n
s
f
o
r
f
ilter
s
th
at
h
a
v
e
b
e
en
p
r
o
p
o
s
ed
b
y
r
esear
ch
er
s
w
h
ich
ca
n
b
e
class
if
ied
ac
co
r
d
in
g
to
th
e
m
ec
h
a
n
is
m
o
f
its
wo
r
k
in
to
two
ca
teg
o
r
ies
[
7
]
:
f
ir
s
t
o
n
e
is
m
u
ltip
lier
b
ased
f
ilter
s
wh
ich
tak
es
a
s
e
t
o
f
m
u
ltip
lier
s
an
d
im
p
lem
en
t
m
u
ltip
licatio
n
s
th
r
o
u
g
h
th
em
s
u
ch
as
in
[8
]
-
[
1
0
]
.
W
h
ile
th
e
s
ec
o
n
d
o
n
e
is
m
u
ltip
ler
less
f
ilter
s
wh
ich
d
ep
en
d
o
n
av
o
i
d
in
g
u
s
in
g
co
s
tly
m
u
ltip
lier
s
th
r
o
u
g
h
r
ep
r
esen
tatio
n
s
an
d
v
ar
io
u
s
ar
ith
m
e
tic
tr
an
s
f
o
r
m
atio
n
s
s
u
ch
as
wo
r
k
s
in
[
1
1
]
-
[
1
4]
.
Fi
lter
s
ca
n
also
b
e
class
if
ied
ac
co
r
d
in
g
to
th
e
n
atu
r
e
o
f
th
eir
u
s
e
s
u
ch
as
m
e
d
ian
f
ilter
an
d
m
o
r
p
h
o
lo
g
ical
f
ilter
s
wh
ich
ar
e
u
s
ed
in
th
is
ar
ticle.
L
ik
e
all
o
th
er
f
ield
s
,
th
er
e
ar
e
a
lo
t
o
f
p
ap
e
r
s
p
r
o
p
o
s
ed
m
ed
ian
f
ilter
d
esig
n
s
in
d
if
f
er
en
t
m
eth
o
d
s
s
u
ch
as
in
[
1
5
]
-
[
1
8
]
.
Her
e
o
th
e
r
ex
am
p
l
e
with
s
o
m
e
d
etails,
th
e
au
th
o
r
s
in
[
1
9
]
d
esig
n
an
d
im
p
lem
en
t
m
ed
ian
f
ilter
b
y
u
s
in
g
v
er
y
h
ig
h
s
p
ee
d
in
te
g
r
ate
d
cir
cu
it
h
ar
d
war
e
d
escr
ip
tio
n
lan
g
u
ag
e
(
VHDL
)
co
d
e
in
Xilin
x
I
SE
1
2
.
2
.
T
h
e
f
ilter
h
as
ab
ilit
y
to
p
r
o
ce
s
s
8
-
b
it
g
r
ay
s
ca
le
im
ag
e
an
d
m
ask
(
3
x
3
)
is
u
s
ed
f
o
r
f
ilt
er
in
g
.
T
h
e
f
ilter
ca
n
tak
e
ca
r
e
o
f
s
alt
an
d
p
ep
p
e
r
n
o
is
e
f
o
r
g
r
ay
s
ca
le
im
ag
e.
At
th
e
s
am
e
tim
e,
it
is
f
ast
en
o
u
g
h
to
u
s
e
it
f
o
r
r
ea
l
tim
e
im
ag
e
p
r
o
ce
s
s
in
g
.
Mo
r
p
h
o
lo
g
ical
o
p
er
atio
n
s
ar
e
u
s
u
ally
in
clu
d
in
g
two
p
r
o
ce
s
s
es
d
ilati
o
n
an
d
er
o
s
io
n
.
T
h
e
r
e
ar
e
m
an
y
r
esear
ch
er
s
r
e
p
r
esen
ted
th
es
e
f
ilter
s
u
s
in
g
FP
GA
in
d
if
f
er
en
t
m
ec
h
an
is
m
s
u
ch
a
s
in
[
2
0
]
-
[
23]
.
Her
e
ar
e
two
e
x
am
p
les
with
s
o
m
e
d
etails,
f
ir
s
t
o
n
e
in
[
2
4
]
.
T
h
e
au
th
o
r
s
d
ep
en
d
in
g
o
n
d
y
n
am
ic
an
d
p
ar
tial
r
ec
o
n
f
i
g
u
r
atio
n
(
DPR
)
tech
n
iq
u
es,
th
ey
p
r
o
p
o
s
ed
a
h
ar
d
war
e
im
p
lem
en
tatio
n
o
f
m
o
r
p
h
o
lo
g
ical
o
p
er
atio
n
s
b
y
u
s
in
g
x
ilin
x
to
o
ls
an
d
Vir
tex
-
5
FP
GA
b
o
ar
d
.
T
h
ei
r
d
esig
n
g
iv
es
th
e
ab
ilit
y
to
ch
o
o
s
e
a
p
p
r
o
p
r
iate
m
o
r
p
h
o
l
o
g
ical
o
p
er
atio
n
s
(
d
ilatio
n
o
r
er
o
s
io
n
)
d
ep
en
d
i
n
g
o
n
th
e
lim
ita
tio
n
o
f
th
e
im
ag
e.
As
a
r
esu
lt,
th
ey
p
r
o
v
ed
th
at
u
s
in
g
DPR
ca
n
s
av
e
at
lea
s
t
1
1
%
o
f
ar
ea
o
n
FP
GA
an
d
im
p
r
o
v
in
g
th
e
p
er
f
o
r
m
a
n
ce
at
th
e
s
am
e
tim
e
ac
co
r
d
i
n
g
t
o
t
h
eir
r
esu
lts
.
I
n
th
e
s
ec
o
n
d
ex
am
p
le,
th
e
au
th
o
r
s
in
[
2
5
]
u
s
in
g
th
e
FP
GA
-
b
as
ed
p
ar
allel
im
p
lem
en
tatio
n
o
f
m
o
r
p
h
o
lo
g
ical
f
ilter
s
to
p
r
esen
t
th
e
h
ar
d
war
e
im
p
lem
en
tatio
n
f
o
r
g
r
ay
s
ca
le
m
o
r
p
h
o
lo
g
ical
o
p
er
atio
n
s
wh
e
r
e
r
ec
tan
g
u
lar
f
lat
to
p
s
tr
u
ct
u
r
i
n
g
elem
en
ts
is
u
s
ed
.
T
h
eir
d
esig
n
g
iv
es
m
o
r
e
th
an
o
n
e
ad
v
a
n
tag
e
s
u
ch
as,
th
r
o
u
g
h
p
u
t
an
d
p
r
o
ce
s
s
in
g
f
r
a
m
e
r
at
e
ar
e
h
ig
h
,
in
ter
n
al
m
em
o
r
y
w
h
ich
is
n
ee
d
ed
is
lo
w
an
d
lo
w
laten
cy
.
T
h
e
Xilin
x
d
esig
n
s
u
ite
1
4
.
2
I
SE
is
u
s
e
d
to
s
y
n
th
esize
th
e
p
r
o
p
o
s
ed
ar
ch
itectu
r
e
an
d
Vir
t
ex
-
5
FP
GA
b
o
ar
d
is
u
s
ed
to
p
r
o
to
ty
p
e
it.
T
h
er
e
ar
e
m
an
y
p
a
p
er
s
d
ea
l
w
ith
th
e
m
a
g
n
etic
r
eso
n
an
ce
im
ag
in
g
(
MRI)
im
ag
e
b
y
u
s
in
g
FP
GA
an
d
th
ese
ar
e
s
o
m
e
ex
a
m
p
les
b
u
t
n
o
t
lim
ited
to
.
T
h
e
a
u
th
o
r
s
in
[
2
6
]
,
[
2
7
]
u
s
e
a
g
r
ap
h
ical
u
s
er
in
t
er
f
ac
e
wh
e
r
e
th
e
Xilin
x
s
y
s
tem
g
en
er
ato
r
an
d
Ma
tlab
Simu
lin
k
ar
e
lin
k
ed
to
g
eth
er
in
o
r
d
er
to
en
h
a
n
ce
th
e
q
u
a
lity
o
f
MRI
im
ag
e.
I
n
th
ey
f
ed
th
at
I
m
p
r
o
v
ed
im
a
g
e
to
ar
tific
ial
n
eu
r
al
n
etwo
r
k
ANN
to
b
e
class
if
ied
if
it
is
n
o
r
m
al
o
r
ab
n
o
r
m
a
l
wh
ile
in
[
2
7
]
,
th
e
y
u
s
e
s
o
m
e
p
ar
am
eter
s
s
u
ch
as
m
ea
n
,
v
ar
ia
n
ce
,
an
d
s
tan
d
ar
d
d
ev
iatio
n
to
class
if
y
th
e
tu
m
o
r
.
T
h
e
au
th
o
r
s
in
[
2
8
]
u
s
e
s
tatio
n
ar
y
wav
elet
tr
an
s
f
o
r
m
a
n
d
p
r
i
n
cip
al
co
m
p
o
n
en
t
an
al
y
s
is
(
S
W
T
-
PC
A
)
tech
n
iq
u
e
f
o
r
th
e
p
r
o
ce
s
s
in
g
o
f
f
u
s
io
n
.
Ma
tlab
Simu
lin
k
an
d
b
lo
ck
s
g
en
er
ato
r
s
y
s
tem
,
Xilin
x
s
y
n
t
h
e
s
ized
with
s
y
n
th
esis
to
o
l
ar
e
u
s
ed
to
d
esig
n
an
d
s
im
u
late
o
f
th
e
p
r
o
p
o
s
ed
s
y
s
tem
.
Her
e
in
[
2
9
]
,
th
ey
en
h
an
c
e
th
e
MRI
im
ag
e
b
y
u
s
in
g
en
h
a
n
ce
d
ca
n
n
y
ed
g
e
d
e
tectio
n
th
en
,
t
h
ey
u
s
e
a
m
o
d
if
ied
wate
r
s
h
ed
s
eg
m
en
tatio
n
al
g
o
r
ith
m
t
o
s
ep
ar
ate
th
e
tu
m
o
r
f
r
o
m
th
e
o
r
ig
in
al
im
ag
e.
T
h
e
p
r
o
p
o
s
ed
s
y
s
tem
is
im
p
lem
e
n
ted
b
y
u
s
in
g
Xilin
x
Vir
tex
-
5
FP
GA.
3.
RE
S
E
ARCH
M
E
T
H
O
D
I
n
an
y
im
a
g
e
p
r
o
ce
s
s
in
g
p
r
o
ce
s
s
,
m
o
s
t
o
f
th
e
tim
e
th
e
p
r
ep
r
o
ce
s
s
in
g
is
th
e
f
ir
s
t
s
tep
wh
ich
is
u
s
u
ally
u
s
ed
to
r
em
o
v
e
s
o
m
e
u
n
wan
te
d
f
ea
tu
r
es
o
r
en
h
a
n
ce
s
o
m
e
o
th
er
o
r
it
is
u
s
ed
to
d
o
b
o
th
o
f
th
e
m
in
o
r
d
er
to
m
a
k
e
th
e
n
ex
t
s
tep
ea
s
ier
.
I
n
th
is
p
a
p
er
,
th
e
p
r
ep
r
o
ce
s
s
in
g
h
as
two
s
tep
s
,
f
ir
s
t
o
n
e
aim
s
to
en
h
a
n
ce
th
e
co
n
tr
ast
o
f
im
ag
e
an
d
ad
ju
s
t
th
e
im
ag
e
i
n
ten
s
ity
wh
er
e
it
ca
n
b
e
d
o
n
e
b
y
u
s
in
g
h
is
to
g
r
am
e
q
u
aliu
z
atio
n
an
d
th
e
r
esu
lt
m
u
ltip
ly
b
y
f
ac
to
r
(
in
o
u
r
ca
s
e
1
.
3
)
to
d
etec
t
n
o
is
e
an
d
d
eter
m
in
e
wh
ich
f
ilter
s
h
o
u
ld
b
e
ap
p
lied
in
o
r
d
er
to
r
em
o
v
e
th
at
n
o
is
e.
W
h
ile
th
e
s
ec
o
n
d
s
tep
aim
s
to
im
p
r
o
v
e
th
e
q
u
ality
o
f
t
h
e
im
ag
e
b
y
r
em
o
v
in
g
d
etec
ted
n
o
is
e.
I
n
o
u
r
wo
r
k
,
th
e
co
m
m
o
n
f
ilter
wh
ich
is
u
s
ed
to
r
em
o
v
e
th
e
p
ep
p
er
a
n
d
s
alt
n
o
is
e
is
m
ed
ia
n
f
ilter
.
T
h
is
f
ilter
is
u
s
ed
to
r
em
o
v
e
u
n
wa
n
ted
n
o
is
e
an
d
at
th
e
s
am
e
tim
e
s
av
in
g
th
e
s
h
ar
p
n
ess
o
f
th
e
im
a
g
e
f
r
o
m
ch
an
g
e
b
ec
au
s
e
th
is
k
in
d
o
f
f
ilter
is
less
s
en
s
it
i
v
e
th
an
o
th
er
lin
ea
r
f
ilter
s
.
Af
ter
f
in
is
h
in
g
th
e
p
r
e
p
r
o
ce
s
s
in
g
o
p
er
atio
n
t
h
at
is
im
p
lem
en
t
ed
b
ased
o
n
th
e
m
ed
ian
f
ilter
,
th
e
im
ag
e
is
r
ea
d
y
to
th
e
s
eg
m
en
tatio
n
p
r
o
ce
s
s
.
As
i
s
k
n
o
wn
,
th
er
e
ar
e
m
an
y
m
eth
o
d
s
f
o
r
s
eg
m
en
tatio
n
o
n
e
o
f
th
em
is
th
r
esh
o
ld
in
g
wh
ich
ca
n
b
e
s
u
m
m
ar
ized
th
u
s
ea
ch
p
ix
el
in
th
e
im
ag
e
h
as
an
i
n
ten
s
i
ty
v
alu
e
b
etwe
en
0
an
d
2
5
5
(
ass
u
m
in
g
th
e
im
a
g
e
is
g
r
a
y
s
ca
le
im
ag
e)
.
Pick
in
g
a
th
r
esh
o
l
d
f
r
o
m
th
at
r
an
g
e
will
ch
an
g
e
th
e
im
ag
e
to
b
in
ar
y
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Dete
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e
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1309
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two
co
lo
r
s
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lack
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n
d
wh
ite
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s
h
ap
e
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d
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ac
k
g
r
o
u
n
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etim
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th
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esh
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ld
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g
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e
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o
u
g
h
to
g
et
th
e
t
ar
g
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f
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o
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th
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en
tatio
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r
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m
e
f
r
am
es
th
at
a
r
e
n
o
t
is
o
lated
.
Fo
r
th
is
r
eso
n
,
th
e
m
o
r
p
h
o
lo
g
ical
o
p
er
atio
n
s
(
wh
ic
h
ar
e
u
s
u
ally
h
av
e
two
p
r
o
ce
s
s
es:
d
ilatio
n
an
d
er
o
s
io
n
)
ar
e
u
s
ed
.
I
n
d
ilatio
n
p
r
o
ce
s
s
,
we
s
tar
t
s
e
ar
ch
in
g
f
o
r
th
e
m
ax
im
u
m
v
alu
e
in
a
s
m
all
g
r
o
u
p
o
f
p
ix
els
to
s
et
it
to
th
e
ce
n
ter
.
W
h
ile
in
er
o
s
io
n
,
th
e
s
ea
r
ch
in
g
will
b
e
f
o
r
th
e
m
in
im
u
m
v
al
u
e
am
o
n
g
a
s
p
ec
if
ied
g
r
o
u
p
o
f
p
ix
els.
I
n
f
ac
t,
th
er
e
ar
e
two
u
s
es
f
o
r
d
ilatio
n
a
n
d
er
o
s
io
n
.
First
o
n
e
is
ca
lled
er
o
s
io
n
to
d
ilatio
n
(
o
p
en
in
g
u
s
e
d
)
wh
ich
is
u
s
ed
to
r
em
o
v
e
t
h
e
b
ac
k
g
r
o
u
n
d
.
W
h
ile
s
ec
o
n
d
o
n
e
is
ca
lled
d
ilatio
n
to
er
o
s
io
n
(
clo
s
in
g
u
s
ed
)
wh
ic
h
is
u
s
ed
to
s
m
o
o
th
s
th
e
im
ag
e
b
y
f
illi
n
g
all
th
e
s
m
all
h
o
les.
T
h
e
d
ec
is
io
n
o
n
t
h
e
ch
o
ice
r
ests
with
th
e
r
esear
ch
er
s
an
d
th
e
n
atu
r
e
o
f
th
e
wo
r
k
.
I
n
o
u
r
ca
s
e,
it
was
h
elp
f
u
l
to
u
s
ed
clo
s
in
g
u
s
ed
.
T
h
is
m
eth
o
d
o
lo
g
y
is
im
p
lem
e
n
ted
b
y
t
h
e
FP
GA
b
o
ar
d
a
n
d
t
h
e
im
p
lem
en
tatio
n
f
lo
wch
ar
t w
ill b
e
d
escr
ib
e
d
in
th
e
n
ex
t sectio
n
.
4.
H
ARDWA
R
E
I
M
P
L
E
M
E
N
T
AT
I
O
N
Dea
lin
g
with
th
e
h
ar
d
wa
r
e
s
y
s
tem
is
n
o
t
th
at
ea
s
y
.
Ma
n
y
p
r
o
b
lem
s
m
a
y
b
e
ap
p
ea
r
ed
d
u
r
in
g
th
e
im
p
lem
en
tatio
n
p
r
o
ce
s
s
.
S
o,
t
h
e
p
r
o
p
o
s
ed
s
y
s
tem
is
d
iv
id
ed
in
to
m
an
y
p
ar
ts
to
f
ac
ilit
ate
th
e
b
est h
an
d
lin
g
an
d
im
p
lem
en
tatio
n
o
f
it.
T
h
e
s
y
s
tem
in
clu
d
es
f
o
u
r
p
h
ases
,
a
s
s
h
o
wn
in
t
h
e
Fig
u
r
e
1
.
T
h
e
f
o
u
r
p
h
ases
ar
e
p
r
ep
r
o
ce
s
s
in
g
,
aju
s
t
im
ag
e,
i
m
p
lem
en
tatio
n
o
f
m
e
d
ian
f
ilt
er
,
an
d
i
m
p
lem
en
tatio
n
o
f
m
o
r
p
h
o
lo
g
ical
f
ilter
s
wh
ich
ar
e
d
escr
ib
e
d
with
m
o
r
e
d
etails
b
elo
w.
Fig
u
r
e
1
.
Pro
p
o
s
ed
s
y
s
tem
4
.
1
.
P
re
pro
ce
s
s
ing
s
t
a
g
e
I
n
th
is
wo
r
k
an
d
ac
co
r
d
in
g
to
th
e
F
ig
u
r
e1
,
th
e
f
ir
s
t
s
tep
in
th
e
p
r
ep
r
o
ce
s
s
in
g
is
ch
an
g
in
g
th
e
R
GB
im
ag
e
to
g
r
a
y
s
ca
le
im
ag
e.
I
n
o
r
d
er
to
s
tar
t
th
at
p
r
o
ce
s
s
,
o
r
i
g
in
al
im
ag
e
is
im
p
o
r
ted
as
A
XI
-
Stre
am
s
,
b
u
t
th
is
f
o
r
m
u
la
d
o
es
n
o
t
wo
r
k
with
th
e
h
ig
h
-
lev
el
s
y
n
t
h
esis
(
HL
S
)
en
v
ir
o
n
m
en
t.
T
h
e
r
ef
o
r
e,
it
is
n
ec
ess
ar
y
to
co
n
v
er
t
ad
v
an
ce
d
eXte
n
s
ib
le
in
ter
f
ac
e
(
AXI
)
s
tr
ea
m
s
to
th
e
HL
S
:
Ma
t
f
o
r
m
at.
T
h
is
co
n
v
er
s
io
n
will
b
e
r
e
p
ea
ted
wh
en
ev
er
is
n
ee
d
ed
b
y
u
s
in
g
t
h
e
AXI
v
id
eo
2
Ma
t
an
d
Ma
t2
A
XI
v
id
eo
f
u
n
ctio
n
s
.
T
h
e
n
ex
t
s
tep
s
h
o
u
ld
b
e
d
o
n
e
to
d
ef
in
e
t
h
e
s
ize
an
d
ty
p
e
o
f
t
h
e
HL
S
:
Ma
t
wh
ich
ar
e
d
ef
in
e
d
with
th
e
c
v
t_
co
lo
u
r
h
ea
d
er
f
i
le
an
d
ca
lcu
late
th
e
m
ax
im
u
m
wid
th
an
d
h
eig
h
t,
t
h
e
n
u
m
b
er
o
f
ch
a
n
n
els an
d
d
e
p
th
o
f
ea
c
h
o
n
e.
4
.
2
.
Adj
us
t
im
a
g
e
T
h
e
h
ar
d
war
e
im
p
lem
en
tatio
n
o
f
ad
ju
s
t
im
ag
e
co
n
tr
ast
is
d
o
n
e
b
y
a
s
ep
ar
ate
h
ar
ed
war
e
i
n
tellectu
al
p
r
o
p
er
t
y
(
IP
)
co
r
e
s
id
e
o
f
p
r
o
g
r
am
m
in
g
lo
g
ic
(
PL
)
p
a
r
t
o
f
Z
y
n
q
s
y
s
tem
o
n
a
ch
ip
(
So
C
)
in
o
r
d
er
to
r
ea
d
f
r
a
m
es
f
r
o
m
o
th
er
s
y
s
tem
h
ar
d
war
e
c
o
r
es.
Pip
elin
in
g
a
n
d
r
esh
ap
e
o
p
tim
izatio
n
d
ir
ec
tiv
es
ar
e
u
s
ed
wh
en
im
p
lem
en
tin
g
th
e
ad
ju
s
t im
ag
e
in
C
-
lan
g
u
ag
e
u
n
d
er
Viv
ad
o
HL
S to
o
l to
g
en
er
ate
o
p
tim
al
R
T
L
co
d
e
im
p
r
o
v
e
th
e
b
a
n
d
wid
th
b
y
ac
ce
s
s
in
g
th
e
d
ata
in
p
ar
allel
all
at
o
n
ce
.
Du
r
in
g
th
is
s
te
p
,
th
e
ad
ju
s
t
im
ag
e
co
r
e
r
ec
ei
v
es
th
e
g
r
ay
im
ag
e
f
r
o
m
th
e
p
r
ep
r
o
ce
s
s
in
g
o
p
er
ati
o
n
s
v
ia
AXI
s
tr
ea
m
.
As m
en
ti
o
n
ed
b
ef
o
r
e,
th
e
c
o
n
v
e
r
s
io
n
f
r
o
m
AXI
Stre
am
s
to
th
e
HL
S:
Ma
t f
o
r
m
at
o
r
v
ice
v
er
s
a
will b
e
d
o
n
e
wh
e
n
ev
er
is
n
ee
d
ed
to
f
it th
e
n
e
x
t step
.
4
.
3
.
I
m
ple
m
ent
a
t
io
n o
f
m
edi
a
n f
ilte
r
Usu
ally
,
m
ed
ian
f
ilter
is
u
s
ed
to
r
ed
u
ce
im
a
g
e
n
o
is
e
an
d
it
i
s
p
r
ef
er
r
ed
o
v
er
o
th
er
s
lin
ea
r
s
m
o
o
th
in
g
f
ilter
s
o
f
s
am
e
s
ize
b
ec
au
s
e
it
p
r
o
v
id
e
a
g
o
o
d
n
o
is
e
r
ed
u
cti
o
n
with
less
b
lu
r
r
in
g
.
T
h
e
p
r
i
n
cip
le
o
f
th
e
f
ilter
'
s
wo
r
k
is
s
im
p
ly
to
tak
e
ea
c
h
p
ix
el
an
d
co
m
p
ar
e
it
to
its
n
eig
h
b
o
r
s
,
an
d
th
en
d
ec
id
e
wh
eth
er
to
r
ep
lace
it
with
th
e
m
ed
ian
o
f
th
o
s
e
v
alu
es
o
r
n
o
t.
T
h
e
Me
d
ian
f
ilter
is
d
o
n
e
b
ased
o
n
th
e
C
o
r
tex
-
A9
p
r
o
ce
s
s
o
r
co
r
e
s
id
e
o
f
p
r
o
g
r
a
m
m
in
g
s
y
s
tem
(
PS
)
p
ar
t
o
f
Z
y
n
q
So
C
with
in
t
h
e
FP
GA
ar
ch
itectu
r
e
a
n
d
o
p
e
n
-
s
o
u
r
ce
co
m
p
u
ter
v
is
io
n
(
Op
en
C
V
)
v
id
eo
lib
r
a
r
y
.
B
y
u
s
in
g
v
id
eo
lib
r
ar
ies
(
wh
ich
a
r
e
alr
ea
d
y
ex
is
tin
g
in
Viv
ad
o
HL
S),
we
ca
n
m
ig
r
ate
th
e
Op
en
C
V
co
d
e
to
s
y
n
th
esizab
le
C
++
co
d
e.
As
a
r
es
u
lt,
f
r
am
e
r
ate
c
o
m
p
u
te
r
v
is
io
n
alg
o
r
ith
m
s
ar
e
im
p
lem
en
ted
,
a
n
d
a
h
ig
h
r
eso
l
u
tio
n
is
en
ab
led
b
y
th
e
s
y
n
th
es
ized
b
lo
ck
s
wh
en
e
v
er
in
teg
r
at
ed
in
to
a
Z
y
n
q
So
C
d
esig
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
9
,
No
.
4
,
Au
g
u
s
t
2
0
2
1
:
1
3
0
7
-
1
315
1310
4
.
4
.
I
m
ple
m
ent
a
t
io
n o
f
M
o
rpho
lo
g
ica
l f
ilte
rs
Fro
m
th
e
p
r
e
v
io
u
s
s
tag
e,
wh
ic
h
is
th
e
m
ed
ian
f
ilter
,
th
e
d
ata
wi
ll sen
d
as st
r
ea
m
t
o
th
e
Dila
te
I
P
-
C
o
r
e
an
d
th
en
t
o
th
e
er
o
d
e
IP
-
C
o
r
e.
I
n
b
o
th
ca
s
es,
th
e
k
er
n
el
th
at
is
u
s
ed
is
a
m
atr
i
x
3
x
3
(
o
n
es).
Af
ter
t
h
at,
th
e
m
u
ltip
licatio
n
p
r
o
ce
s
s
tak
es
p
lace
b
etwe
en
th
e
f
ilter
an
d
t
h
e
im
ag
e.
T
h
en
,
th
e
m
ax
im
u
m
v
alu
e
is
ex
tr
ac
te
d
in
ca
s
e
d
ilate
an
d
th
e
m
in
m
u
m
v
alu
e
is
ex
tr
ac
ted
in
ca
s
e
er
o
d
e
.
T
h
ese
two
f
ilter
s
ar
e
ap
p
lied
in
alter
n
atio
n
an
d
th
eir
r
esu
lts
ar
e
s
to
r
ed
in
a
s
p
ec
if
ic
B
R
A
M
(
B
lo
ck
R
AM
)
f
o
r
th
e
p
u
r
p
o
s
e
o
f
co
llectin
g
an
d
s
en
d
in
g
th
em
to
th
e
co
m
p
u
ter
b
y
s
er
ial
p
o
r
t.
Fin
d
i
n
g
th
e
m
ax
im
u
m
v
alu
e
a
n
d
th
e
m
in
m
u
m
v
alu
e
a
r
e
d
o
n
e
ac
c
o
r
d
in
g
t
o
th
ese
two
eq
u
atio
n
s
:
F
(
,
)
=
ma
x
−
1
≤
′
≤
+
1
−
1
≤
′
≤
+
1
(
′
,
′
)
F
(
,
)
=
min
−
1
≤
′
≤
+
1
−
1
≤
′
≤
+
1
(
′
,
′
)
T
h
e
Z
y
n
q
AXI
_
lite in
ter
f
ac
e
c
o
n
n
ec
tio
n
is
u
s
ed
to
im
p
lem
e
n
t th
e
p
r
o
p
o
s
ed
s
y
s
tem
as
illu
s
tr
ate
in
Fig
u
r
e
2
.
Fig
u
r
e
2
.
Ov
e
r
all
p
r
o
p
o
s
ed
s
y
s
tem
o
n
zy
n
q
ch
ip
5.
RE
SU
L
T
S AN
D
AN
AL
Y
SI
S
T
h
e
h
ar
d
war
e
r
eso
u
r
ce
s
f
o
r
e
n
t
ir
e
s
y
s
tem
ar
e
s
u
m
m
a
r
ized
i
n
Fig
u
r
e
3
.
T
h
e
Z
y
n
q
x
c7
z0
2
0
e
v
alu
atio
n
k
it
co
m
p
r
is
e
[
3
0
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5
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s
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Acc
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Fig
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r
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e
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lo
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m
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T
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e
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e
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r
ai
n
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o
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k
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s
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ated
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u
r
e
s
5
(
a
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,
(
b
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(
c
)
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d
(
d
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
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n
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s
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ated
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ig
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r
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m
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ltip
ly
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ich
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ilter
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ter
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en
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et
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s
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ated
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d
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s
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ill
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e
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e
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s
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s
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ated
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u
r
es 9
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b
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d
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-
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r
o
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e
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r
atio
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p
e
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:
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t
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u
s
ed
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r
em
o
v
e
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e
s
m
all
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jects
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ich
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e
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t
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elate
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o
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s
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ated
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Fig
u
r
es 1
0
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a
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,
(
b
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(
c
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n
d
(
d
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Fig
u
r
e
3
.
R
eso
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r
ce
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tili
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tio
n
o
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th
e
h
a
r
d
war
e
Fig
u
r
e
4.
Fu
n
ctio
n
s
o
f
o
u
r
p
r
o
p
o
s
e
d
wo
r
k
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
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ig
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d
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r
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tiv
ely
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ally
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e
h
is
to
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m
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etch
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Fig
u
r
e
s
1
1
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n
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at
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ep
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e
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o
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r
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u
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h
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ast
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ased
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ased
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ich
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ased
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m
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r
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e
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n
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ated
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n
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u
r
e
1
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.
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ab
le
1
R
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f
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r
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k
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d
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%
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
Dete
ctio
n
o
f
b
r
a
in
s
tr
o
ke
in
th
e
MRI
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g
e
u
s
in
g
F
P
GA
(
Dh
ey
a
a
A
lh
ela
l
)
1313
(
a)
(
b
)
Fig
u
r
e
1
1
.
T
h
ese
f
ig
u
r
es a
r
e
:
(
a)
r
esu
lt o
f
h
is
to
g
r
am
b
y
Ma
tlab
,
(
b
)
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esu
lt o
f
h
is
to
g
r
am
b
y
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GA
Fig
u
r
e
12
.
T
im
e
co
m
p
ar
is
o
n
b
etwe
en
M
atlab
an
d
FP
GA
6.
CO
NCLU
SI
O
N
T
h
e
m
ain
g
o
al
o
f
th
is
p
ap
e
r
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t
o
d
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n
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d
im
p
lem
e
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t
an
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f
i
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t
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ig
ital
s
y
s
tem
(
h
ar
d
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e
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n
ce
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ts
)
to
clar
if
y
th
e
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r
ain
s
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o
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e
in
MRI
im
ag
e
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o
r
d
e
r
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im
p
r
o
v
e
th
e
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ag
es
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d
m
ak
e
t
h
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v
is
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to
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ac
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ate
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iag
n
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is
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y
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o
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r
s
.
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h
e
s
y
s
tem
is
d
iv
id
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i
n
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o
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r
s
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s
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Pre
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s
s
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m
ed
ian
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ilter
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n
d
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o
r
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ilter
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ly
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s
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Op
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lib
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a
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h
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m
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ed
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th
e
FP
GA
-
HL
S
to
o
l
s
im
p
lify
th
e
im
p
lem
en
tatio
n
o
f
im
a
g
e
p
r
o
ce
s
s
in
g
f
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s
th
at
ar
e
u
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e
d
in
o
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r
p
r
o
p
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ed
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ar
d
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e
s
y
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tem
.
Ha
r
d
war
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d
in
p
r
o
p
o
s
ed
s
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ar
e
c
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m
p
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ted
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d
tar
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o
n
FP
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Z
y
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q
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atio
n
k
it
wh
ich
is
eq
u
al
m
ax
im
u
m
o
n
l
y
1
5
%.
Fin
ally
,
th
e
r
esu
lts
ar
e
o
b
tain
ed
b
y
FP
GA
p
r
o
v
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e
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d
s
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f
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s
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o
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Ma
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’
s
r
esu
lts
wh
er
e
th
e
ac
cu
r
ac
y
r
an
g
e
d
Evaluation Warning : The document was created with Spire.PDF for Python.
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RE
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E
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E
NC
E
S
[1
]
A.
Alh
a
wa
imil,
“
S
e
g
m
e
n
tati
o
n
o
f
Bra
in
S
tro
k
e
Im
a
g
e
,
”
In
t.
J
.
A
d
v
.
Res
.
C
o
mp
u
t.
C
o
mm
u
n
.
E
n
g
.
,
v
o
l.
4
,
n
o
.
9
,
p
p
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5
–
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7
8
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e
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.
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5
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1
0
.
1
7
1
4
8
/IJARCCE.
2
0
1
5
.
4
9
8
1
.
[2
]
D.
G
.
Ba
il
e
y
,
“
Im
a
g
e
p
ro
c
e
ss
in
g
u
sin
g
F
P
G
As
,
”
v
o
l.
5
,
n
o
.
5
,
M
a
y
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0
1
9
,
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o
i:
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0
.
3
3
9
0
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ima
g
i
n
g
5
0
5
0
0
5
3
.
[3
]
D.
G
.
Ba
il
e
y
a
n
d
A.
S
.
Am
b
ik
u
m
a
r,
“
Bo
rd
e
r
h
a
n
d
li
n
g
f
o
r
2
D
tran
s
p
o
se
fil
ter
stru
c
t
u
re
s
o
n
a
n
F
P
G
A,”
J
.
Ima
g
in
g
,
v
o
l.
4
,
n
o
.
1
2
,
p
p
.
1
-
2
1
,
No
v
.
2
0
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8
,
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o
i:
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0
.
3
3
9
0
/j
ima
g
i
n
g
4
1
2
0
1
3
8
.
[4
]
R.
S
h
i
,
J.
S
.
J.
W
o
n
g
,
a
n
d
H.
K.
H.
S
o
,
“
Hig
h
-
t
h
ro
u
g
h
p
u
t
li
n
e
b
u
f
fe
r
m
icro
a
rc
h
it
e
c
tu
re
fo
r
a
rb
i
trary
siz
e
d
stre
a
m
in
g
ima
g
e
p
ro
c
e
ss
in
g
,
”
J
.
Ima
g
in
g
,
v
o
l.
5
,
n
o
.
3
,
M
a
r.
2
0
1
9
,
d
o
i:
1
0
.
3
3
9
0
/j
ima
g
in
g
5
0
3
0
0
3
4
.
[5
]
D.
Alh
e
lal
a
n
d
M
.
F
a
e
z
ip
o
u
r
,
“
D
e
n
o
isin
g
a
n
d
b
e
a
t
d
e
tec
ti
o
n
o
f
E
CG
sig
n
a
l
b
y
Us
in
g
F
P
G
A,”
In
t.
J
.
Hi
g
h
S
p
e
e
d
El
e
c
tro
n
.
S
y
st.
,
v
o
l
.
2
6
,
n
o
.
3
,
2
0
1
7
,
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0
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4
2
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0
1
2
9
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5
6
4
1
7
4
0
0
1
6
X.
[6
]
A.
Al
-
Du
jaili
a
n
d
S
.
A.
F
a
h
m
y
,
“
Hig
h
T
h
ro
u
g
h
p
u
t
2
D S
p
a
ti
a
l
Im
a
g
e
F
il
ters
o
n
F
P
G
As
,
”
a
rXiv
,
p
p
.
1
-
8
,
Oc
t.
2
0
1
7
.
[7
]
S
.
Ba
d
a
v
e
,
“
M
u
lt
i
p
li
e
rles
s
F
IR
F
il
ter
Im
p
lem
e
n
tatio
n
o
n
F
P
G
A,”
In
t.
J
.
In
f
.
El
e
c
tro
n
.
E
n
g
.
,
v
o
l.
2
,
n
o
.
2
,
p
p
.
1
8
5
-
1
8
8
,
Ja
n
.
2
0
1
2
,
d
o
i:
1
0
.
7
7
6
3
/i
ji
e
e
.
2
0
1
2
.
v
2
.
7
8
.
[8
]
L.
S
.
De
Bru
n
n
e
r,
“
Re
d
u
c
i
n
g
c
o
m
p
lex
it
y
o
f
F
IR
fil
ter
imp
lem
e
n
tatio
n
s
f
o
r
l
o
w
p
o
we
r
a
p
p
li
c
a
ti
o
n
s,”
Co
n
f.
Rec
.
-
Asil
o
ma
r C
o
n
f
.
S
i
g
n
a
ls,
S
y
st.
C
o
mp
u
t
,
2
0
0
7
,
p
p
.
1
4
0
7
-
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4
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1
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o
i:
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0
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1
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0
9
/ACS
S
C.
2
0
0
7
.
4
4
8
7
4
6
0
.
[9
]
J.
P
a
rk
,
K.
M
u
h
a
m
m
a
d
,
a
n
d
K
.
Ro
y
,
“
Hig
h
-
p
e
rfo
rm
a
n
c
e
F
IR
fil
t
e
r
d
e
sig
n
b
a
se
d
o
n
sh
a
rin
g
m
u
lt
i
p
li
c
a
ti
o
n
,
”
IEE
E
T
ra
n
s.
Ver
y
L
a
rg
e
S
c
a
le In
teg
r.
S
y
st.
, v
o
l.
1
1
,
n
o
.
2
,
p
p
.
2
4
4
-
2
5
3
,
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u
l.
2
0
0
3
,
d
o
i:
1
0
.
1
1
0
9
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I.
2
0
0
2
.
8
0
0
5
2
9
.
[1
0
]
P
.
Bo
u
g
a
s,
P
.
Ka
li
v
a
s,
A.
Tsiri
k
o
s,
a
n
d
K.
Z.
P
e
k
m
e
stz
i,
“
P
ip
e
li
n
e
d
Arra
y
-
Ba
se
d
F
IR
F
il
ter F
o
ld
i
n
g
,
”
v
o
l
.
5
2
,
n
o
.
1
,
p
p
.
1
0
8
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8
,
Ja
n
.
2
0
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I.
2
0
0
4
.
8
3
8
5
4
2
.
[1
1
]
S
.
M
irza
e
i,
A.
Ho
sa
n
g
a
d
i,
a
n
d
R
.
Ka
stn
e
r,
“
F
P
G
A
imp
lem
e
n
tatio
n
o
f
h
i
g
h
sp
e
e
d
F
IR
fil
ters
u
sin
g
a
d
d
a
n
d
sh
if
t
m
e
th
o
d
,
”
IE
EE
I
n
t.
C
o
n
f
.
Co
m
p
u
t
.
De
s.
ICCD
,
2
0
0
6
,
p
p
.
3
0
8
-
3
1
3
,
d
o
i:
1
0
.
1
1
0
9
/ICCD.
2
0
0
6
.
4
3
8
0
8
3
3
.
[1
2
]
Z.
Tan
g
,
J.
Z
h
a
n
g
,
a
n
d
H.
M
in
,
“
A
h
ig
h
-
s
p
e
e
d
,
p
r
o
g
ra
m
m
a
b
le,
CS
D
c
o
e
fficie
n
t
F
IR
fil
ter,”
IEE
E
T
ra
n
s.
Co
n
su
m.
El
e
c
tro
n
.
,
v
o
l.
4
8
,
n
o
.
4
,
p
p
.
8
3
4
-
8
3
7
,
De
c
.
2
0
0
2
,
d
o
i
:
1
0
.
1
1
0
9
/T
C
E.
2
0
0
3
.
1
1
9
6
4
0
9
.
[1
3
]
J.
B.
Ev
a
n
s,
“
Eff
icie
n
t
F
IR
F
il
ter
Arc
h
it
e
c
tu
re
s
S
u
it
a
b
le
fo
r
F
P
G
A
Im
p
lem
e
n
tatio
n
,
”
IEE
E
T
r
a
n
s.
Circ
u
it
s
S
y
st.
II
An
a
l
o
g
Dig
it
.
S
ig
n
a
l
Pro
c
e
ss
.
,
v
o
l.
4
1
,
n
o
.
7
,
p
p
.
4
9
0
-
4
9
3
,
Ju
l.
1
9
9
4
,
d
o
i:
1
0
.
1
1
0
9
/8
2
.
2
9
8
3
8
5
.
[1
4
]
S
.
S
.
Je
n
g
,
H.
C
.
Li
n
,
a
n
d
S
.
M
.
Ch
a
n
g
,
“
F
P
G
A
imp
lem
e
n
tatio
n
o
f
F
IR
fil
ter
u
sin
g
M
-
b
it
p
a
r
a
ll
e
l
d
istri
b
u
te
d
a
rit
h
m
e
ti
c
,
”
Pro
c
.
-
IEE
E
I
n
t.
S
y
m
p
.
Circ
u
it
s
S
y
st.
,
n
o
.
5
,
p
p
.
8
7
5
-
8
7
8
,
J
u
n
.
2
0
0
6
,
d
o
i
:
1
0
.
1
1
0
9
/i
sc
a
s.
2
0
0
6
.
1
6
9
2
7
2
5
.
[1
5
]
S
.
A.
F
a
h
m
y
,
P
.
Y.
K
.
Ch
e
u
n
g
,
a
n
d
W.
Lu
k
,
“
No
v
e
l
F
P
G
A
-
b
a
se
d
imp
lem
e
n
tatio
n
o
f
m
e
d
ian
a
n
d
we
ig
h
ted
m
e
d
ia
n
fil
ters
fo
r
ima
g
e
p
ro
c
e
ss
in
g
,
”
Pro
c
.
-
2
0
0
5
In
t.
C
o
n
f
.
F.
Pro
g
r
a
m.
L
o
g
.
A
p
p
l
.
FP
L
,
S
e
p
.
2
0
0
5
,
d
o
i:
1
0
.
1
1
0
9
/F
P
L.
2
0
0
5
.
1
5
1
5
7
1
3
.
[1
6
]
A.
Eri
c
,
“
F
P
G
A
Im
p
lem
e
n
tati
o
n
o
f
M
e
d
ia
n
F
il
ter
u
sin
g
a
n
Im
p
ro
v
e
d
Alg
o
rit
h
m
fo
r
Im
a
g
e
P
ro
c
e
ss
in
g
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
f
o
r In
n
o
v
a
ti
v
e
Res
e
a
rc
h
i
n
S
c
ien
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
1
,
n
o
.
1
2
,
p
p
.
2
5
-
3
0
,
2
0
1
5
.
[1
7
]
G
.
L.
Ba
tes
a
n
d
S
.
N
o
o
sh
a
b
a
d
i
,
“
F
P
G
A
imp
lem
e
n
tatio
n
o
f
a
m
e
d
ian
fil
ter,”
IEE
E
R
e
g
.
1
0
A
n
n
u
.
I
n
t.
C
o
n
f
.
Pro
c
e
e
d
in
g
s/
T
ENCON
,
v
o
l.
2
,
p
p
.
4
3
7
-
4
4
0
,
Ja
n
.
1
9
9
7
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i:
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0
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n
c
o
n
.
1
9
9
7
.
6
4
8
2
1
0
.
[1
8
]
S
.
S
.
Tav
se
,
P
.
M
.
Ja
d
h
a
v
,
a
n
d
M
.
R.
In
g
le,
“
Op
ti
m
ize
d
M
e
d
ian
F
il
ter
Im
p
lem
e
n
tatio
n
o
n
F
P
G
A
In
c
lu
d
i
n
g
S
o
f
t
P
ro
c
e
ss
o
r,
”
In
t.
J
.
Eme
rg
.
,
v
o
l.
2
,
n
o
.
8
,
p
p
.
2
3
6
-
2
3
9
,
A
u
g
.
2
0
1
2
.
[1
9
]
K.
S
.
Ra
j
u
,
P
.
P
h
u
k
a
n
,
a
n
d
G
.
Ba
u
ra
h
,
“
An
F
P
G
A
Im
p
lem
e
n
tatio
n
o
f
a
F
a
st
2
-
Dim
e
n
sio
n
a
l
M
e
d
ian
F
il
ter
,”
Na
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Rec
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1
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D.
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3
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K.
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4
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.
[2
5
]
D.
M
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.
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.
[2
6
]
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.
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De
sh
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D.
K.
Ra
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7
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.
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A.
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.
K.
Wali,
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De
sig
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