* README

** What is this program?

This is the source code of my reservoir computing model presented in
the following paper:

    Tadashi Yamazaki and Shigeru Tanaka,
    Robust Reservoir Generation by Correlation-Based Learning,
    Advances in Artificial Neural Systems,
    vol. 2009, Article ID 467128, 7 pages, 2009. doi:10.1155/2009/467128

    http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2009/467128

    This is an open access article so that anyone can download the PDF
    from the above link.

The model can be run online at the sim.neuinf.jp simulation platform: 


** Files

This folder contains the following files:

README :: This file
Makefile :: Makefile
main.c :: The simulation program
xcorr.c :: The program to calculate a similarity index
mt19937ar-cok.c :: The Mersenne Twister pseudo random number generator (*)
w.0.bz2 :: Initial connection weights (expand first by % bunzip2 w.0.bz2)

(*) http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html

** Usage

1. % make
2. % ./main 3 o w.0 w.1 33
3. % xcorr o.a o.a c

#1 generates main and xcorr binaries.

#2 generates o.a, o.r, and w.1.  File o.a is used to compute a similarity
index.  File o.r is used to obtain a raster plot.  For example, using
GNUPLOT, we do:

% gnuplot
gnuplot> plot [0:1000][0:100] 'o.r' w d

to plot the activity of the first 100 neurons for 1000 steps.  File w.1
is the updated connection weights from the initial weights specified by
w.0.  The 1st arg (3) is the random number seed for random connections
from excitatory to inhibitory neurons, so that this arg is fixed during
repeated trials.  The last arg (33) is the seed for temporal afferent
noise, so that this arg should change across trials.  See usage by just
% ./main.

#3 generates c.png, c.si, c.d, the similarity index, from file o.a.  
File c.png is the PNG file of the whole index matrix (Eq. 6).
File c.si contains the average and the standard deviation of the index
with the following format:

    

c.d contains the reproducibility index (Eq. 9).  Reproducibility index
is calculated by two different output data, say o1.a and o2.a as:

% xcorr o1.a o2.a xc

xc.d represents the reproducibility index.

** Authors

Tadashi Yamazaki and Shigeru Tanaka

TY: Strategic Planning Unit, RIKEN BSI-TOYOTA Collaboration Center,
RIKEN Brain Science Institute.  ST: Lab. for Visual Neurocomputing,
RIKEN Brain Science Institute.

** Copyright

Copyright (c) 2008 RIKEN (The Institute of Physical and Chemical
Research) Some rights reserved.

** License

CC-BY

This work is licensed under the Creative Commons Attribution 3.0
License. To view a copy of this license, visit
http://creativecommons.org/licenses/by/3.0/ or send a letter to
Creative Commons, 171 Second Street, Suite 300, San Francisco,
California, 94105, USA.