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────────────────────────────────────────────────────────────
USER'S GUIDE
NeoC Explorer Version 1.0
Copyright 1994 (C), Szabolcs Szakacsits
Jozsef Attila University, Szeged, Hungary
July 22, 1994
────────────────────────────────────────────────────────────
1. Introduction to NeoC Explorer
─────────────────────────────────
The NeoC program is an implementation of Fukushima's
Neocognitron neural network. It's purpose is to test the model, to
facilitate interactivity for the experiments, and to make the
Neocognitron neural net operation more understandable.
Some substantial features:
■ friendly graphic user interface
■ explorer and tester operation modes
■ easy neural net construction
■ graphic or numerical displaying of cells and weights
■ training by patterns or modules step by step, or
complete neural net training
■ displaying of the patterns and recognition results
■ recognition statistics
■ even more statistics of the tests in a .LOG file
during tester mode
The minimal system requirements to run NeoC are a 286 AT
compatible computer, a VGA video card, and a mouse. A fast
computer with a mathematical coprocessor is recommended because of
the many computations.
There are two utility programs for NeoC. One of them is the MAP
(Make Pattern). Using it one can design new patterns easily and
quickly in the graphic mode with mouse support. The other program
- 1 -
is the DIP (Display Pattern). It converts the binary pattern files
to the standard output as text so that the text file can be
interfaced with the user's own software. One can use this text
file for one's own program (probably, the text file will have to
be modified somewhat to conform to the user's own file type), and
in this way the experiments can be done with the same patterns
comparing NeoC and other neural nets. For this purpose, another
solution can be found in the MAP.DOC file.
NeoC uses three main type file formats. They specify the
■ neural net structure and parameters (files with
extension .ndf)
■ complete neural net (files with extension .net)
■ train and input patterns (files with extension .ptt)
The first two are text files, so one can create them using a
word processor. However I suggest doing this with NeoC because
it's much easier. The structure of a .ndf file is, for instance,
the following:
2
1 8 1
6 6 3
6 4 3
3 2 3
3 1 2
0.100000
10
1.000000 1.000000
99.000000 99.000000
The first line is the number of net modules, the next lines are
the U0 (input layer), US1 (S-layer of module 1), UC1 (C-layer of
module 1), US2 (S-layer of module 2) and UC2 (C-layer of module
2). These lines consist of three columns, i. e. the number of
planes in that layer, the size of planes in the current layer (eg.
the above second line means that the input layer has one plane
with 8 x 8 cells), and the mask size (reception field). Note the
size (N) means actually a real size N x N field. The following
lines are the alpha parameter, the decision parameter (see later),
the r parameters in each and every module, and the last line that
contains the q parameters.
The .ptt binary files are created by the MAP program.
The NeoC command line structure is shown below.
NeoC [-m] [file1 [file2 [file3]]]
The file1 is a neural net definition file (.ndf), file2 is a train
file (.ptt), and file3 is an input file (also a .ptt file). If the
command line does not contain any parameters (except for the -m
option), the program will suggest a net structure, and it may be
modified and saved later. If one tests a particular net structure
- 2 -
with the same train and input file regularly, then it is useful to
make a batch file which consists of the above described lines, and
to run it. If only a monochrome monitor is available, then one
should run NeoC with the -m option.
Information can be obtained on command line structure, if the
?, -?, h, or -h options are used.
Usage of NeoC consists of six components: Main Menu, 'Explorer
Panel', 'Net Input' and 'Identify as', NeoCognitron Neural Net,
Structure, and 'Tester Panel' windows.
2. Main Menu
─────────────
Main Menu structure of NeoC:
■ Structure
■ Load
■ Save
■ Change
■ Net
■ Load
■ Save
■ Reset
■ Operation
■ Explorer
■ Tester
■ DOS
■ DOS shell
■ Exit
■ Help
■ NeoC Explorer
■ About
The neural net structure cannot be changed in the NeoCognitron
Neural Net window because of dynamic memory allocation of the net
structure. If one desires to change it, then one has to use the
Structure/Change menu.
The Net/Reset menu can be used if one is in the Explorer mode
(it is automatic in the Tester mode). By selecting it, one may
reset the weights of the current module or every module. The value
of the weights will be set between 0 and 1 randomly.
The 'Explorer Panel' window will appear if one uses the
Operation/Explorer menu (this is the default mode). Here are the
most possibilities to manipulate and examine the net.
The 'Tester Panel' window will appear instead of the 'Explorer
Panel' if the Operation/Tester menu is used. Here, the net
performance can be measured and analyzed.
Some of the menus will not always make sense, should this be
the case an information message will be displayed on the screen.
- 3 -
3. Explorer Panel
──────────────────
The white texts are static and the red ones are dynamic in the
windows and window fields. The red texts can be given a new value
by pointing and clicking on them with the left, or right, or both
buttons. The left button on the mouse will increase the value by
one, the right button will decrease the value by one, and pushing
both at the same time will cause a small window to appear on the
screen. The new value may be written into it. This method works in
the case of text variables also. The boxes in view may be left by
pressing the ESC key or by pushing both of the mouse buttons at
the same time if the new value given is not desired. If the new
value isn't correct, a message will indicate the error.
The 'Train file' and 'Input file' fields determine which
pattern files will be trained and recognized. These fields must be
filled in, and the file types must be in the .ptt file format. The
pattern size, in both files, and the input layer size of the net
must be equal. If these conditions aren't granted, the program
will display an error message. The numbers after the file names,
are the number of patterns in the current (train or input) file.
The net weights and planes (ie.