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lib/AI/NNFlex.pm  view on Meta::CPAN

sub load_state
{
	my $network = shift;

	my %config = @_;

	my $filename = $config{'filename'};

	open (IFILE,$filename) or return "Error: unable to open $filename because $!";

	# we have to build a map of nodeids to objects
	my %nodeMap;
	foreach my $layer (@{$network->{'layers'}})
	{
		foreach my $node (@{$layer->{'nodes'}})
		{
			$nodeMap{$node->{'nodeid'}} = $node;
		}
	}

	# Add the bias node into the map
	if ($network->{'bias'})
	{
		$nodeMap{'bias'} = $network->{'biasnode'};
	}


	my %stateFromFile;

	while (<IFILE>)
	{

lib/AI/NNFlex/Hopfield.pm  view on Meta::CPAN

 $network->learn($dataset);

 my $outputsRef = $dataset->run($network);

 my $outputsRef = $network->output();

=head1 DESCRIPTION

AI::NNFlex::Hopfield is a Hopfield network simulator derived from the AI::NNFlex class. THIS IS THE FIRST ALPHA CUT OF THIS MODULE! Any problems, let me know and I'll fix them.

Hopfield networks differ from feedforward networks in that they are effectively a single layer, with all nodes connected to all other nodes (except themselves), and are trained in a single operation. They are particularly useful for recognising corru...

Full documentation for AI::NNFlex::Dataset can be found in the modules own perldoc. It's documented here for convenience only.

=head1 CONSTRUCTOR 

=head2 AI::NNFlex::Hopfield->new();

=head2 AI::NNFlex::Dataset

 new (	[[INPUT VALUES],[INPUT VALUES],