drawnn.m

人工神经网络：MATLAB源程序用于训练测试

%#													
%# function drawnn(topo,w1,w2)							
%#										
%# AIM:		Draws the topology of a neural network. (Called in nnmodel.m)	
%#		 									
%# INPUT:	topo (2 x nh) : matrix containing structure of the NN (nh hidden nodes)
%#			        (H: hyperbolic tangent, L: linear, -: no function)
%#		w1 (nh x (p+1)) : matrix of weights between input-hidden layer	
%#				  (p: number of input variables)		
%#		w2 (1 x (nh+1)) : matrix of weights between hidden-output layer							
%#										
%# AUTHOR:	Programmed by : Claus Svarer, EI/CONNECT &		
%#				Magnus Norgaard, IAU/EI/IMM (1994)		
%#			        Neural Network-Based System Identification Toolbox
%#				Web site : http://www.iau.dk/Projects/proj/nnsysid.html
%#											
%#		Modified by Frederic Despagne					
%#		Copyright(c) 1998 for ChemoAC					
%#		Dienst FABI, Vrije Universiteit Brussel		
%#		Laarbeeklaan 103, 1090 Jette			
%#										
%# VERSION: 1.1 (28/02/1998)							
%#										

function drawnn(topo,w1,w2)

close
[N1,N0] = size(w1);
N0 = N0-1;
N2 = length(find(topo(2,:)~='-'));
MaxNeu = max([N0 N1 N2]);
cla
LengthTres = 0.025*MaxNeu;
axis([-0.1 2.1 0.5 MaxNeu+0.5]);
axis('off')
hold on;
for i = 1:N0,
 	plot(0,(MaxNeu/(N0+1))*i,'co');
     	text(-0.1,(MaxNeu/(N0+1))*i-0.0,sprintf('%g',i));
end;

for i = 1:N1,
   	plot(1,(MaxNeu/(N1+1))*i,'co');
  	if topo(1,i) == 'L'
		plot([1 1],[((MaxNeu/(N1+1))*i-LengthTres) ((MaxNeu/(N1+1))*i+LengthTres)],'c');
	end
end;

for i = 1:N2,
   	plot(2,(MaxNeu/(N2+1))*i,'co');
	if topo(2,i) == 'L'
		plot([2 2],[((MaxNeu/(N2+1))*i-LengthTres) ((MaxNeu/(N2+1))*i+LengthTres)],'c');
	end
end;

for i = 1:N0,
   	for j = 1:N1,
      		plot([0 1],[(MaxNeu/(N0+1))*i (MaxNeu/(N1+1))*j],'c');
   	end;
end

for i = 1:N1,
   	for j = 1:N2,
         	plot([1 2],[(MaxNeu/(N1+1))*i (MaxNeu/(N2+1))*j],'c');
   	end;
end