give me a detailed code for LBG algorithm or give me the function d=disteu(v,c) in the below function

function b=vqlbg(v,k) % VQLBG Vector quantization using the Linde-Buzo-Gray algorithm % % Inputs: % v contains training data vectors (one per column) % k is number of centroids required % % Outputs: % c contains the result VQ codebook (k columns, one for each centroids) c=mean(v,2); figure(8); plot(c(:,:),'.'); title('initial codebook'); %pause e=0.01; c(:,1)=c(:,1)+c(:,1)*e; figure(9); plot(c(:,:),'.'); title('codebook1'); %pause c(:,2)=c(:,1)-c(:,1)*e figure(10); plot(c(:,:),'.'); title('codebook2'); %pause % Nearest Neighbour Searching. % Given a current codebook 'c', assign each training vector in 'v' with the % closest codeword. Using the function disteu2, the distances between these % vectors (v and c) are computed. d=disteu(v,c); [m,id]=min(d,[],2); [rows,cols]=size(c); % The centroids of the vectors are found using the mean function. for j=1:cols c(:,j)=mean(v(:,find(id==j)),2); end figure(11); plot(c(:,:),'.'); title('new cluster'); %pause % for each training vector, find the closest codeword using the min % function. n=1;n=n*2; while cols<16 for i=1:cols c(:,i)=c(:,i)+c(:,i)*e; c(:,i+n)=c(:,i)-c(:,i)*e; d=disteu(v,c); [m,i]=min(d,[],2); [rows,cols]=size(c); end figure(12); plot(c(:,:),'.'); title('updated'); %pause % The centroids of the vectors are found using the mean function. for j=1:cols if find(i==j)~isempty(c); c(:,j)=mean(v(:,find(i==j)),2); end end n=n*2; end

Answer 1

[Pedro Villena]

function d = disteu(x, y)
% DISTEU Pairwise Euclidean distances between columns of two matrices
% Input:
%       x, y:   Two matrices whose each column is an a vector data.
% Output:
%       d:      Element d(i,j) will be the Euclidean distance between two
%               column vectors X(:,i) and Y(:,j)
% Note:
%       The Euclidean distance D between two vectors X and Y is:
%       D = sum((x-y).^2).^0.5

[M, N] = size(x);
[M2, P] = size(y); 

if(M ~= M2),
  error('Matrix dimensions do not match.')
end
d = zeros(N, P);
if(N < P),
  copies = zeros(1,P);
  for n = 1:N,
    d(n,:) = sum((x(:, n+copies) - y) .^2, 1);
  end
else
  copies = zeros(1,N);
  for p = 1:P,
    d(:,p) = sum((x - y(:, p+copies)) .^2, 1)';
  end
end
d = d.^0.5;

[deepak]

sir thank u so much sir i am beginner in matlab. sir some error in this line, i will try to solve if you know pleas tell me sir d(:,p) = sum((x - y(:, p+copies)) .^2, 1)'; once again thank u

[deepak]

ya c and v are same number of row M & M2 of 768. but P have only 3 & N have 3072 columns here