<s>
Extension	B-Algorithm
neural	I-Algorithm
network	I-Algorithm
is	O
a	O
pattern	O
recognition	O
method	O
found	O
by	O
M	O
.	O
H	O
.	O
Wang	O
and	O
C	O
.	O
P	O
.	O
Hung	O
in	O
2003	O
to	O
classify	O
instances	O
of	O
data	O
sets	O
.	O
</s>
<s>
Extension	B-Algorithm
neural	I-Algorithm
network	I-Algorithm
is	O
composed	O
of	O
artificial	B-Architecture
neural	I-Architecture
network	I-Architecture
and	O
extension	O
theory	O
concepts	O
.	O
</s>
<s>
It	O
uses	O
the	O
fast	O
and	O
adaptive	O
learning	O
capability	O
of	O
neural	B-Architecture
network	I-Architecture
and	O
correlation	O
estimation	O
property	O
of	O
extension	O
theory	O
by	O
calculating	O
extension	O
distance	O
.	O
</s>
<s>
Extension	B-Algorithm
neural	I-Algorithm
network	I-Algorithm
has	O
a	O
neural	B-Architecture
network	I-Architecture
like	O
appearance	O
.	O
</s>
<s>
Rather	O
than	O
using	O
one	O
weight	O
value	O
between	O
two	O
layer	O
nodes	O
as	O
in	O
neural	B-Architecture
network	I-Architecture
,	O
extension	B-Algorithm
neural	I-Algorithm
network	I-Algorithm
architecture	O
has	O
two	O
weight	O
values	O
.	O
</s>
<s>
In	O
extension	B-Algorithm
neural	I-Algorithm
network	I-Algorithm
architecture	O
,	O
for	O
instance	O
,	O
is	O
the	O
input	O
which	O
belongs	O
to	O
class	O
and	O
is	O
the	O
corresponding	O
output	O
for	O
class	O
.	O
</s>
<s>
Weight	O
values	O
in	O
extension	B-Algorithm
neural	I-Algorithm
network	I-Algorithm
represent	O
these	O
ranges	O
.	O
</s>
