unorm.m

This Two-Category Classifier Using Discriminant Functions to separeate two classes. The Classifier

function [univar,xaxis] = unorm(mu, var, range, n)
%function [univar,xaxis] = unorm(mu, var, range, n)
% Generate Univariate Gaussian (Normal) data and plot from given mean and variance
%
% mu is scaler mean
% covar scaler variance
% range is 1x2 matrix to define plot range
% n is scaler number of data to be generated.
%
% Developed by: Kirit Patel
% EE 574: Pattern Recognition
% Date: 11/30/2002

if (nargin < 4), n = 50; end 
if (nargin < 3), range = [-10 10]; end
if (nargin < 2), errordlg('Not enough input arguments','Input Error','on'); end
xaxis = linspace(range(1), range(2), n);
if var <= 0 
    errordlg('Variance can not be Zero or Negative','Input Error','on')
    return
end
univar = exp(-0.5.*(xaxis-mu).^2./var)./sqrt(2.*pi.*var);        
if (nargout == 0) 
    plot(xaxis, univar)
    xlabel('x-axis'); ylabel('Density, p(X)');
    title('Normal Univariate Density')
end