sgnt_insert.m

ISGNN是对SGNN(self-generated neural network)的一种改进,是一种在线学习的算法.

function [node] = sgnt_insert(node,e,alfa)
% Insert the data s into the SNGT node.
% Input:
%       node: is a SGNT
%       e: is a sample data
%       alfa: is a threshold value of minimum distance bwteen e and winner
[noder,nodec]= size(node);
m = nodec -4;

% choose(i,node)
winner = 1;
dmin = inf;
dead = 0;
t = 1;
for h=1:1:noder
    if h == 1 | node(h, m+2) > 0
        w = node(h,1:m);
        % d = sqrt((y1(i,:)-w)*(y1(i,:)-w)');
        d = sum((e - w).^2);
        if d < dmin
            dmin = d;
            winner = h;
        end
    else
        dead(t) = h;
        t = t+1;
    end
end

if dmin > alfa      
    %*************************************************
    if node(winner,m+3)== 0  % winner is a leaf
        % copy(n_j,n_win); and  % connect(n_j,n_win);
        j = noder +1;
        if dead(1) > 0 j= dead(1);  end
        
        node(j,:)= node(winner,:);
        node(j,m+1)= 1;
        node(j,m+2)= winner;
        node(j,m+3)= 0;
        node(j,m+4)= 0;
        node(winner,m+3)= j;
    end
    
    [noder,nodec]= size(node);
    j =  noder +1;
    if length(dead) > 1   j = dead(2);   end
    
    % copy(n_j,e_i);
    node(j,1:m) = e;
    node(j,m+1)= 1;
    node(j,m+2)= winner;
    node(j,m+3)= 0;
    node(j,m+4)= 0;
     
    % connect(n_j,n_win);
    j_sibling = node(winner,m+3);
     while(node(j_sibling, m+4) >0)
         j_sibling= node(j_sibling,m+4);
     end
     node(j_sibling, m+4) = j;
     
     % update(e_i,n_win)
      node(winner,m+1)= node(winner,m+1)+1;
     node(winner,1:m)= node(winner,1:m)+(e(1:m)-node(winner,1:m))./node(winner,m+1);
           
     while(winner > 1)
         winner= node(winner,m+2);
         node(winner,m+1)= node(winner,m+1)+1;
         node(winner,1:m)= node(winner,1:m)+(e(1:m)-node(winner,1:m))./node(winner,m+1);
     end
end