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

Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood