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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

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