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

Basic linear algebra uncovers and clarifies very important geometry and algebra.

Dr. Paul Garrett