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AI::NeuralNet::Kohonen::Node - a node for AI::NeuralNet::Kohonen |
AI::NeuralNet::Kohonen::Node - a node for AI::NeuralNet::Kohonen
Implimentation of a node in a SOM - see the AI::NeuralNet::Kohonen manpage.
Returns a new Node object. If no wieghts
are supplied, the node's weights are randomized
with real nubmers.
weight.
dim, above.
x for unknown values.
x.
Find the distance of this node from the target.
Accepts: the target vector as an array reference.
Returns: the distance.
__________________
/ i=n 2
Distance = / E ( V - W )
\/ i=0 i i
Where V is the current input vector, and
W is this node's weight vector.
Calculates the effect on learning of distance from a given point (intended to be the BMU).
Accepts: the distance of this node from the given point; the radius of the neighbourhood of affect around the given point.
Returns:
( 2 )
( distance )
THETA(t) = exp ( - ----------- )
( 2 )
( 2 sigma (t) )
Where distance is the distance of the node from the BMU,
and sigma is the width of the neighbourhood as calculated
elsewhere (see FINDING THE NEIGHBOURS OF THE BMU in the AI::NeuralNet::Kohonen manpage). THETA also
decays over time.
The time t is always that of the calling object, and is not referenced here.
The the AI::NeuralNet::Kohonen manpage.
This implimentation Copyright (C) Lee Goddard, 2003. All Rights Reserved.
Available under the same terms as Perl itself.
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AI::NeuralNet::Kohonen::Node - a node for AI::NeuralNet::Kohonen |