% sep96.m implements the learning rule described in Bell \& Sejnowski, Vision% Research, in press for 1997, that contained the natural gradient (w'w).%% Bell & Sejnowski hold the patent for this learning rule. %% SEP goes once through the mixed signals, x % (which is of length M), in batch blocks of size B, adjusting weights,% w, at the end of each block.% sepout is called every F counts.%% I suggest a learning rate (lrate) of 0.006, and a blocksize (B) of % 300, at least for 2->2 separation.% When annealing to the right solution for 10->10, however, lrate of% less than 0.0001 and B of 10 were most successful.%% Copyright 1996 Tony Bell% This may be copied for personal or academic use.% For commercial use, please contact Tony Bell % (tony@salk.edu) for a commercial license.x=x(:,perm);sweep=sweep+1; t=1;noblocks=fix(P/B);BI=B*Id;for t=t:B:t-1+noblocks*B,  count=count+B;  u=w*x(:,t:t+B-1);   w=w+L*(BI+(1-2*(1./(1+exp(-u))))*u')*w;  if count>F, sepout; count=count-F; end;end;