Is there any matlab function to calculate moving mean square error?

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Kalasagarreddi Kottakota
回答： Mathieu NOE 2022-11-30
I am looking for a way to calculate mean square error for every 'n' sample in a signal of length N (total number of samples)
  2 个评论
Jonas
Jonas 2022-11-30
please make clear: do you calculate the least square line once and first and then you want the sliding window of mean error per n sample
OR
do you take a window of n samples, calculate least square line and want to measure the error of that part?
Kalasagarreddi Kottakota
Kalasagarreddi Kottakota 2022-11-30
Sorry its a mistake, I am looking for to calculate sliding mean square error between two signals.

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回答（2 个）

Bruno Luong
Bruno Luong 2022-11-30
Ran in:
Assuming you have 2 signals S1 and S2 in 1 x N arrays:
N = 1000;
S1 = randn(1,N);
S2 = randn(1,N);
n = 10;
dS = S1 - S2;
RMS = sqrt(conv(dS.^2, ones(1,n)/n, 'valid'))
RMS = 1×991
1.1971 1.2146 1.1593 1.0481 1.0444 1.0172 1.0472 1.0975 1.0711 0.9866 1.0295 0.9773 0.9768 1.0108 1.3782 1.3756 1.3565 1.7685 1.8392 1.8426 1.8149 1.8150 1.9150 1.8936 1.6972 1.7878 1.6632 1.1701 1.1023 1.0704
Mathieu NOE
Mathieu NOE 2022-11-30
hello
I doubt that there is a code for that
try this :
(based on formula) :
% dummy data
n=300;
x=linspace(0,2*pi,n);
f = cos(x) + 0.1*randn(1,n); % values of the model
y = smoothdata(f,'gaussian',30); % actual data
buffer = 10; % nb of samples in one buffer (buffer size)
overlap = 9; % overlap expressed in samples
%%%% main loop %%%%
m = length(f);
shift = buffer-overlap; % nb of samples between 2 contiguous buffers
for ci=1:fix((m-buffer)/shift +1)
start_index = 1+(ci-1)*shift;
stop_index = min(start_index+ buffer-1,m);
time_index(ci) = round((start_index+stop_index)/2); % time index expressed as sample unit (dt = 1 in this simulation)
mse(ci) = my_mse(f(start_index:stop_index) - y(start_index:stop_index)); %
end
xx = x(time_index); % new x axis
figure(1),
plot(x,f,xx,mse,'r*');
figure(1),
plot(x,f,'k',x,y,'b',xx,mse,'r');
legend('f data','y data','MSE');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function x_mse = my_mse(x)
x_mse = mean(x.^2);
end

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