matthiasm@8: function dist=JSDiv(P,Q)
matthiasm@8: % Jensen-Shannon divergence of two probability distributions
matthiasm@8: %  dist = JSD(P,Q) Kullback-Leibler divergence of two discrete probability
matthiasm@8: %  distributions
matthiasm@8: %  P and Q  are automatically normalised to have the sum of one on rows
matthiasm@8: % have the length of one at each 
matthiasm@8: % P =  n x nbins
matthiasm@8: % Q =  1 x nbins
matthiasm@8: % dist = n x 1
matthiasm@8: 
matthiasm@8: 
matthiasm@8: if size(P,2)~=size(Q,2)
matthiasm@8:     error('the number of columns in P and Q should be the same');
matthiasm@8: end
matthiasm@8: 
matthiasm@8: % normalizing the P and Q
matthiasm@8: Q = Q ./sum(Q);
matthiasm@8: Q = repmat(Q,[size(P,1) 1]);
matthiasm@8: P = P ./repmat(sum(P,2),[1 size(P,2)]);
matthiasm@8: 
matthiasm@8: M = 0.5.*(P + Q);
matthiasm@8: 
matthiasm@8: dist = 0.5.*KLDiv(P,M) + 0.5*KLDiv(Q,M);