MACHINE LEARNING TECHNIQUES - LASA

153
To simplify the description of the information retrieval, one, often, uses:
1
η = (6.66)
K
6.9.3 Retrieval Phase
Each neuron updates its state as if it were a single neuron with the threshold activation function
⎛⎛ ⎞⎞ ⎧⎧1 if z ≥ 0
xj = θ⎜⎜
wijxi
⎟⎟, θ( z)
=⎨⎨
⎝⎝ i ⎠⎠ ⎩⎩-1 if z < 0
∑ (6.67)
x ∈−
n
j
{ 1,1}
The activity of the neurons can be updated either synchronously or asynchronously. The retrieval
procedure is iterative and consists of the following:
Initialization:
r
At time t=0, inject a pattern to the net x µ
random pattern), i.e. set the state of all the network’s neuron to
Update:
Synchronous Update:
(possibly a noisy version of a stored pattern or a
( 0 ) ,..., ( 0)
x = x x = x
µ µ
1 1 K K
⎛⎛
xj( t) = θ aj( t− ) ∀ aj t− = ⎜⎜ wijxi
t−
⎝⎝ i
( 1 ) j ( 1) ( 1)
⎞⎞
⎟⎟
⎠⎠
∑ (6.68)
All neurons compute their activation and update their state simultaneously following:
Asynchronous Update:
One neuron at a time computes its activations and updates its state. The sequence of
selected neuron may be fixed or random:
⎛⎛
xj( t) = θ aj( t− ) aj t− = ⎜⎜ wijxi
t−
⎝⎝ i
( 1 ) ( 1) ( 1)
( ) x ( t )
x t = −1 ∀ i≠
j
i
i
⎞⎞
⎟⎟
⎠⎠
∑ (6.69)
© A.G.Billard 2004 – Last Update March 2011