how can I write the MSE in matlab??

Dear All, can anyone help me in implementing this formula on matlab? where aX(λ,k) is the true (clean) magnitude spectrum at frame λ and bin k; a^X(λ,k) is the estimated magnitude spectrum (following enhancement), M is the total number of frames in a sentence, and N is the number of frequency bins. The signal are complex column vectors and both size Mx1. Thanks you.

Answer 1

[Image Analyst]

See my attached demo below. Here's a snippet from it:

%------ PSNR CALCULATION ----------------------------------------------------------
% Now we have our two images and we can calculate the PSNR.
% First, calculate the "square error" image.
% Make sure they're cast to floating point so that we can get negative differences.
% Otherwise two uint8's that should subtract to give a negative number
% would get clipped to zero and not be negative.
squaredErrorImage = (double(grayImage) - double(noisyImage)) .^ 2;
% Display the squared error image.
subplot(2, 2, 3);
imshow(squaredErrorImage, []);
title('Squared Error Image', 'FontSize', fontSize);
% Sum the Squared Image and divide by the number of elements
% to get the Mean Squared Error.  It will be a scalar (a single number).
mse = sum(squaredErrorImage(:)) / (rows * columns);
% Calculate PSNR (Peak Signal to Noise Ratio) from the MSE according to the formula.
PSNR = 10 * log10( 256^2 / mse);
% Alert user of the answer.
message = sprintf('The mean square error is %.2f.\nThe PSNR = %.2f', mse, PSNR);
msgbox(message);

[Nicola]

thanks for the reply, but my signals are audio signals. Is it the same?

[Image Analyst]

Yes, it's the same, though you could simplify a bit by getting rid of the (:) since your signal is already a 1D signal

mse = sum(squaredErrorImage) / numel(squaredErrorImage);