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`<a href "http://www.scilab.org">Scilab</a> is a open-source Matlab-like tool developed at INRIA. It can be downloaded for several platforms from the link:
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Scilab <http://www.scilab.org> is a open-source Matlab-like tool developed at INRIA. It can be downloaded for several platforms from the link:
  
 
http://www.scilab.org/download/
 
http://www.scilab.org/download/

Revision as of 17:54, 19 March 2008

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


Brief Introduction to Scilab


Scilab <http://www.scilab.org> is a open-source Matlab-like tool developed at INRIA. It can be downloaded for several platforms from the link:

http://www.scilab.org/download/

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:

!`MultivariateNormalDensity.sci`__

__ MultivariateNormalDensity.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 below:

!`MultivariateNormalDensity.sci`__ - Implementation of a function to compute the multivariate normal density

__ MultivariateNormalDensity.sci

Alumni Liaison

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

Landis Huffman