www.pudn.com > neuro.rar > neuro.cpp

procedure dichot_output (finished: booLean); 
var i: integer; 
begin 
 check_key; 
 gotoxy(1,4); 
 textbackground(7);textcoLor(0); 
  writeln('Training Cycle',iter,': weight Vector'); 
  writeln; {outputvecs[i][1] then {...if not correct sign} 
    begin              {...cycle ts not success} 
    finished:=false; 
    for j:=1 to leninvecs+1 do {...adjust weights +/-} 
    weightvecs[1][j]:=weightvecs[1][j]+alpha*sgn(sum)*inputvecs[i][j]; 
    end; 
  end; 
  dichot_output(finished); 
until finished or abort or quittrain; 
 if not abort then 
 while not abort and not quittest do {allow testing of new patts} 
 begin 
 writeln; 
 write('Enter a test vector of dimension',Leninvecs,':'); 
 for i:=1 to leninvecs do read(testvec[i]); 
 readln; 
 testvec[leninvecs+1]:=1.0; 
 sum:=0.0; 
 for i:=1 to leninvecs+1 do 
  sum:=sum +weightvecs[1][i]*testvec[i]; 
  if sgn(sum)<0.0 then writeln('Classified as pattern 1') 
		  else writeln('Classified as pattern 2'); 
    hitakey; 
    end; 
 until quitruns; 
 end;