findclassifier2

 FINDCLASSIFIER2
       is very similar to FINDCLASSIFIER1 but uses a different 
       criterion for selecting the time segment.
 [CC,Q,TSD,MD]=findclassifier2(D,TRIG,Class,class_times,t_ref);

 D     data, each row is one time point
 TRIG    trigger time points
 Class class information
 class_times    classification times, combinations of times must be in one row 
 t_ref    reference time for Class 0 (optional)

 CC     contains LDA and MD classifiers
 Q      is a list of classification quality for each time of 'class_times'
 TSD     returns the LDA classification 
 MD    returns the MD  classification 

 [CC,Q,TSD,MD]=findclassifier2(AR,find(trig>0.5)-257,~mod(1:80,2),reshape(1:14*128,16,14*8)');


 Reference(s): 
 [1] Schl�l A., Neuper C. Pfurtscheller G.
     Estimating the mutual information of an EEG-based Brain-Computer-Interface
      Biomedizinische Technik 47(1-2): 3-8, 2002.
 [2] A. Schl�l, C. Keinrath, R. Scherer, G. Pfurtscheller,
    Information transfer of an EEG-based Bran-computer interface.
    Proceedings of the 1st International IEEE EMBS Conference on Neural Engineering, Capri, Italy, Mar 20-22, 2003