The Computational Beauty of Nature
Computer Explorations of Fractals, Chaos,
Complex Systems, and Adaptation


About the Book
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Source Code
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documentation
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Miscellany
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ASSOC Documentation


 



NAME

       assoc - retrieve associative memories


SYNOPSIS

       assoc -help
         or
       assoc  [-pfile  ...]   [-tfile  string]  [-local  integer]
              [-cut  double]  [-pprob  double]  [-noise   double]
              [-seed integer] [-steps integer] [-inv] [-mag inte-
              ger] [-term string]


DESCRIPTION

       Attempt to reconstruct a potentially corrupted image  from
       a  McCulloch-Pitts feedback neural network that acts as an
       associative memory.  The weights of the network are deter-
       mined  via Hebb's rule after reading in multiple patterns.
       Weights can be pruned either by size,  locality,  or  ran-
       domly.


OPTIONS

       -pfile ...
              File with pattern to store.

       -tfile string
              File with test pattern.

       -local integer
              locality of permitted weights

       -cut double
              Cutoff size for weights.

       -pprob double
              Probability of random pruning.

       -noise double
              Amount of noise for test case.

       -seed integer
              Random seed for initial state.

       -steps integer
              Number of time steps.

       -inv   Invert all colors?

       -mag integer
              Magnification factor.

       -term string
              How to plot points.


MISCELLANY

       All  pattern files must be in the PBM file format. You can

       request that multiple patterns be stored into the  weights
       by using the -pfile option multiple time.

       The dimensions of the stored patterns and the test pattern
       must be identical.

       For weight pruning, the program first checks to see  if  a
       weight  is  "non-local" which means that for a weight that
       connects two neurons either  the  row  indices  or  column
       indices differ by the amount greater than the value speci-
       fied by the -local option.  (If a value for  local  -local
       is  zero,  then  all weights are used.)  Next, the program
       prunes weights that are too small in size as specified  by
       the  -cut  option.   If  a weights has not been removed at
       this stage, then it will still be pruned with  probability
       as specified by the -pprob option.


BUGS

       No  sanity  checks  are performed to make sure that any of
       the options make sense.


AUTHOR

       Copyright (c) 1997, Gary William Flake.

       Permission granted for any use according to  the  standard
       GNU ``copyleft'' agreement provided that the author's com-
       ments are neither modified nor removed.   No  warranty  is
       given or implied.

Copyright © Gary William Flake, 1998-2002. All Rights Reserved. Last modified: 30 Nov 2002