Matakuliah
Tahun
Versi
: H0434/Jaringan Syaraf Tiruan
: 2005
:1
Pertemuan 8
JARINGAN COMPETITIVE
1
Learning Outcomes
Pada akhir pertemuan ini, diharapkan mahasiswa
akan mampu :
• Menjelaskan konsep Jaringan Competitive
2
Outline Materi
• Arsitektur Jaringan
• Learning Rule
3
Hamming Network
4
Layer 1 (Correlation)
We want the network to recognize the following prototype vectors:
 p1  p2   pQ
The first layer weight matrix and bias vector are given by:
2w
T
T
p
2
=
b1 =
R
R

p 1T

=
T

T
p QT
R
Sw
The response of the first layer is:
p 1T p + R
1
a = W1p + b1 =
p 2T p
+R

W1
1w
p QT p + R
The prototype
closest to the
input vector produces
the largest response.
5
Layer 2 (Competition)
2
The second layer is
initialized with the output
of the first layer.
1
a 0  = a
2
2
a  t + 1 = posli nW 2 a  t  

2
w ij =  1  if i = j
 –  otherwise
2
ai  t
2
2
+ 1  = poslin  a i t  –   a j  t 


j i
1
0    -----------S– 1
The neuron with the
largest initial condition
will win the competiton.
6
Competitive Layer
p =
Tp
= L cos q 2
2w
Sw
T
2
Sw
Tp

T
L cos q 1

n = Wp =
2w
2
T
1w p

T
1w
2
L cos q S
a = compet  n
 1 i = i 
ai = 
 0 i  i
n i  n i  i
i   i   n i = n i
7
Competitive Learning
Instar Rule
iw q
= iw  q – 1 + ai q p q – iw q – 1 
For the competitive network, the winning neuron has an
ouput of 1, and the other neurons have an output of 0.
Kohonen Rule
w  q
i
=
w q 
i
w q –
i
1 +  pq  – i w q – 1 
= 1 –  iw q – 1 + p q
iw q 
= iw  q – 1 
i  i
8
Graphical Representation
w  q
i
=
w q 
i
w q –
i
1 +  pq  – i w q – 1 
= 1 –  iw q – 1 + p q
9
Example
10
Four Iterations
11
Typical Convergence
(Clustering)
Weights
Input Vectors
Before Training
After Training
12
Dead Units
One problem with competitive learning is that neurons
with initial weights far from any input vector may never win.
Dead Unit
Solution: Add a negative bias to each neuron, and increase the
magnitude of the bias as the neuron wins. This will make it harder
13
to win if a neuron has won often. This is called a “conscience.”