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Tutorials describing how to use Scilab can be found here:
 
Tutorials describing how to use Scilab can be found here:
* [http://www.scilab.org/doc/intro/node1.html| The official documentation]
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* [http://www.scilab.org/doc/intro/node1.html The official documentation]
* [http://128.220.138.60:8080/download/attachments/1343559/Scilab+Tutorial+Annigeri.pdf?version=1| A hands-on tutorial]
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* [http://128.220.138.60:8080/download/attachments/1343559/Scilab+Tutorial+Annigeri.pdf?version=1 A hands-on tutorial]
* [http://comptlsci.anu.edu.au/Numerical-Methods/tutorial-all.pdf| ANU Scilab Tutorial]
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* [http://comptlsci.anu.edu.au/Numerical-Methods/tutorial-all.pdf ANU Scilab Tutorial]
* [http://www.iecn.u-nancy.fr/~pincon/scilab/docletter.pdf| Une introduction a Scilab], if you want to have some fun reading a Scilab tutorial in French.
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* [http://www.iecn.u-nancy.fr/~pincon/scilab/docletter.pdf Une introduction a Scilab], if you want to have some fun reading a Scilab tutorial in French.
  
 
==Homework #1 related functionality==
 
==Homework #1 related functionality==
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There are several ''tool boxes'' of functions written by people all over the world adding extra functionality to Scilab. Here are some useful links:
 
There are several ''tool boxes'' of functions written by people all over the world adding extra functionality to Scilab. Here are some useful links:
  
* [http://www.scilab.org/contrib/index_contrib.php?page=download&category=MANUALS| Toolboxes for Scilab and Their Manuals]
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* [http://www.scilab.org/contrib/index_contrib.php?page=download&category=MANUALS Toolboxes for Scilab and Their Manuals]
* [http://www.scilab.org/contrib/index_contrib.php?page=displayContribution&fileID=194| Scilab Toolbox especialized on Pattern Recognition -- Presto-Box]
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* [http://www.scilab.org/contrib/index_contrib.php?page=displayContribution&fileID=194 Scilab Toolbox especialized on Pattern Recognition -- Presto-Box]
* [http://lmb.informatik.uni-freiburg.de/lmbsoft/presto-box/presto-box-docu.pdf| Manual for Presto-Box -- Scilab]
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* [http://lmb.informatik.uni-freiburg.de/lmbsoft/presto-box/presto-box-docu.pdf Manual for Presto-Box -- Scilab]
* [http://dir.filewatcher.com/d/Mandrake/10.2/src/Sciences/Mathematics/scilab-toolbox-ANN-0.4.2-4mdk.src.rpm.27699.html| ANN - Neural Networks Tool Box]
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* [http://dir.filewatcher.com/d/Mandrake/10.2/src/Sciences/Mathematics/scilab-toolbox-ANN-0.4.2-4mdk.src.rpm.27699.html ANN - Neural Networks Tool Box]
* [http://www.informatik.uni-freiburg.de/~fehr/scisvm.html| SCIsvm], a plugin for the libsvm C++ library.
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* [http://www.informatik.uni-freiburg.de/~fehr/scisvm.html SCIsvm], a plugin for the libsvm C++ library.
  
  

Revision as of 10:19, 20 March 2008

Here you can find relevant information on how to implement Pattern Recognition projects using Scilab.

Brief Introduction to Scilab

Scilab is a open-source Matlab-like tool developed at INRIA. It can be downloaded for several platforms.

Tutorials describing how to use Scilab can be found here:

Homework #1 related functionality

Random Number Generator

grand is the function used to generate random numbers. In order to generate a multivariate normally distributed sequence of n vectors with mean mu and covariance cov, grand should be called as:

numbers = grand(n, 'mn',mu, cov);

Function declaration

example that computes the multivariate normal probability density:

// function to compute the multivariate normal distribution
//note that it asks for the sigma inverse, as well as the Sigma's determinant
function [g] = MultivariateNormalDensity(x,mu, sigma_inv, sigma_det)
d=length(x);
r2 = (x-mu)'*sigma_inv*(x-mu);
factor = 1/sqrt(((2*%pi)^d)*sigma_det);
g = factor * exp (-(1/2)*r2);
endfunction


The file with the code above can be downloaded from the link below: Media:MultivariateNormalDensity_OldKiwi.sci

Tool Boxes

There are several tool boxes of functions written by people all over the world adding extra functionality to Scilab. Here are some useful links:


Scilab Code

All the relevant code for the EE662 course written in Scilab is posted here.

Alumni Liaison

BSEE 2004, current Ph.D. student researching signal and image processing.

Landis Huffman