function [y] = rjGaussian(mu,x);% if nargin < 2, error('Not enough input arguments.'); end[N,d] = size(x);      % N = number of data, d = dimension of x.y=zeros(N,1);for j=1:N,  z=norm(x(j,:)-mu(1,:));             % Euclidean distance.  y(j,1)=exp(-(16*16)*z.^(2));        % Gaussian with fixed width for exp. 1.%  y(j,1)=exp(-(0.5)*inv(.00001)*z.^(2));        % Gaussian.end;