=head1 NAME

profnet_* - neural network implementations in Fortran

=head1 SYNOPSIS

profnet_* [OPTION|filePar]

=head1 DESCRIPTION

profnet_* binaries are neural network implementations in Fortran.  Due to the original design of the code, a specific binary is compiled for each particular network architecture, changing certain constants in the source code.  Therefore, there is a binary for every network architecture used.  Note: certain array structures are intentionally indexed out of bounds in some of the binaries.

Note:

This binary should only be used to run with pre-made training data, do not try to use it to train your network as it will produce undesired results. It was made to be used I<only> as part of wrapping (dependent) packages and not as a standalone neural network program.

=head1 OPTIONS

This list is not exhaustive.

=over

=item filePar

file with input parameters (also gives fileIn, fileOut)     

=item 1

"switch"

=item 2

number of input units

=item 3

number of hidden units

=item 4

number of output units

=item 5

number of samples

=item 6 

bitacc (typically 100)

=item  7

file with input vectors

=item 8

file with junctions

=item 9

file with output of NN ("none" -> no file written)

=item 10

optional=dbg

=item  [inter] 

will bring up dialog

=back

=head1 NOTES

1st MUST be "switch"!

tested only with 2 layers!

=head1 AUTHOR

Burkhard Rost <rost@rostlab.org>

Bug fixes and enhancements by Laszlo Kajan <lkajan@rostlab.org> and Guy Yachdav <gyachdav@rostlab.org>

=head1 COPYRIGHT AND LICENSE

Copyright 1998-2011 by Burkhard Rost <rost@rostlab.org> EMBL, CUBIC (Columbia University, NY, USA) and LION Biosciences (Heidelberg, DE)

Copyright 2009-2011 by Laszlo Kajan <lkajan@rostlab.org> Technical University Munich (Munich, DE)

Copyright 2009-2011 by Guy Yachdav <gyachdav@rostlab.org> CUBIC (Columbia University, NY, USA) and Technical University Munich (Munich, DE)
