- Please post a copy of the complete error message. This would reveal, which line is failing.
- What are the inputs x and y in your case?
- sqrt(x) is faster than x.^0.5.
- Since Matlab R2016b you can omit the "+copies".
Matrix dimensions for Euclidean Distance
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Bisma Waheed
el 25 de Mzo. de 2018
Comentada: Antonio Argentieri
el 22 de Ag. de 2020
I am working on project "Speaker Recognition using PNCC and MFCC". For recognition I have to do matching step . For which I have to compare the feature matrix of test voice sample with the feature matrix of the rest of the voice samples. Matching is done using euclidean distance between the test sample and the samples in database. For MFCC my code works correctly. However, for PNCC the code might seem to change the dimensions and an error: "Matrix dimensions must agree" is generated. My question is that how to find the euclidean distance with different dimensions or how to change the dimensions such that my results are not affected.
My CODE:
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
% 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;
4 comentarios
Respuesta aceptada
Matt J
el 25 de Mzo. de 2018
Editada: Matt J
el 25 de Mzo. de 2018
Rather than debugging disteu, I invite you to use my own implementation (attached). The help doc should be pretty straightforward.
4 comentarios
Antonio Argentieri
el 22 de Ag. de 2020
Hi, I have the same error, have you solved this problem?
Thanks.
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