function p=gaussian(mu,Sigma,x)
%% x=gaussian(mu,Sigma,N)
%% mu, sigma: parameters of the Gaussian
%% x: calculate the probability of x

if sum(~isnan(x))==0, %% The prob. of the zero-dimension vector is one.
   p=1;
else, %% Non-zero dimension vector
  good_ind = find(~isnan(x)); 


  %% Compute marginalized Gaussian on features that were detected
  x = x(good_ind);
  mu = mu(good_ind);
  Sigma = Sigma(good_ind,good_ind);
  
  ll = length(mu);
  y = x-mu; 
  d2 = diag(y' * inv(Sigma) * y);
  p = exp(-d2/2) / sqrt((2*pi)^ll * det(Sigma));
end;