Downsampled data exceeds the input data
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Chandramouli Jambunathan
2022년 11월 18일
댓글: Chandramouli Jambunathan
2022년 11월 18일
I have an input data sampled at 64 Hz and I want it converted to 60Hz. I tried using 'resample' function and 'downsample' function within matlab,but in both the cases the output data exceeds the input data at some sample points. For example, the input data contains angles in degrees which is under -180 deg to +180 deg, but the downsampled data contains 220 deg,which is wrong. how to avoid these?
In the attached picture, you can find all the input and output are overlayed. Can someone please help me?
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Mathieu NOE
2022년 11월 18일
hello
for the resampling task , use interp1 with a new time vector defined at rate = 60 Hz
to avoid data above / below +/- 180 ° use wrap
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Mathieu NOE
2022년 11월 18일
a demo is maybe more efficient here
so the original data gets resampled at 60 Hz by using only the start / end points of the time vector of the original data (sampled at 64 Hz)
the two data sets do match visually on the graph even though the points are not on the same grid (of course)
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1198643/image.png)
samples=1000;
% original data at 64 Hz rate
dt1 = 1/64;
t1= 1 + (0:samples-1)*dt1;
y1 = 180*(square(t1));
plot(t1,y1,'b-*')
% resample the data at 60Hz
dt2 = 1/60;
t2= t1(1):dt2:t1(end); % NB wee use only the first and last value of t1 to create t2
y2 = interp1(t1,y1,t2);
plot(t1,y1,'b',t2,y2,'r')
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Jan
2022년 11월 18일
A linear interpolation avoids output points outside the range of input point. Use interp1 or the modern and faster griddedInterpolant .
A fast C-mex function for this job: https://www.mathworks.com/matlabcentral/fileexchange/25463-scaletime
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Jan
2022년 11월 18일
I do not understand the meaning of "Both 'interp1' and 'griddedInterpolant' function expects specific data points". But Mathieu has show already, how to use these interpolation methods.
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