som_winner.m

this file is leverage algorithm written in matlab as m-file and tested in matlab.so anyone can ue th

function [winner,d_min] = som_winner(x_in,W)

% som_winner calculates the winner neuron 
% (based on euclidean distance)
%
% winner = som_winner(x_in,W);
%
% input:
%   x_in        sample [1 x p]
%   W           unfolded kohonen weights [size*size x p]
% 
% output:
%   winner      winner neuron
%
% see the HTML HELP files (help.htm) for details 

if length(find(isnan(x_in)))== 0
    D_squares_x = (sum(x_in'.^2))'*ones(1,size(W,1));
    D_squares_w = sum(W'.^2);
    D_product   = - 2*(x_in*W');
    D = (D_squares_x + D_squares_w + D_product).^0.5;
    [d_min,winner] = min(D);
else
    d_min = NaN;
    for m = 1:size(W,1)
        d = dist_calc(x_in,W(m,:));
        if isnan(d_min)|d < d_min
            winner = m;
            d_min = d;
        end    
    end
end

%--------------------------------------------

function D = dist_calc(x_1,x_2,dist);

d = (x_1 - x_2).^2;
D = (sum(d(~isnan(d))))^0.5;