code for calculating root mean square error of two quantities having different dimensions?
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I am doing floating to fixed point conversion. output of Fixed point conversion has different dimensions than the same of floating point engine. How to calculate root mean square error in such a case?
er = M - x; er = sqrt((er(:)'*er(:))/length(er(:))); Using the above formulas, matlab's giving error that matrix dimensions must agree
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dpb
2014-5-27
Fix the output to have the same number or truncate the longer of the two to the shorter. It makes no sense to talk of a error if there's nothing to compare to.
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the cyclist
2014-5-27
I assume it is the line
er = M - x;
that is giving the error. Do M and x have different dimensions, but the same number of elements? If so, then try transposing one of the vectors like this:
er = M' - x;
If they have different number of elements, then I am completely befuddled as to how you expect to calculate the error from these two variables. There must be a one-to-one comparison for the error to make sense (most of the time).
2 个评论
Ishan
2014-5-27
the cyclist
2014-5-27
But, this is so confusing. Do M(1) and x(1) really correspond to each other, such that that is a valid measure of error? What about M(7234) and x(7234)?
Or is it more complicated, with M and x being sampled at different rates or times, such that there is not a one-to-one correspondence?
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dpb
2014-5-27
Agree w/ cycler that it's confusing why this should be so, but the answer to the question ...trying to truncate the larger of the two to the smaller one & then trying to find the error is pretty simple.
N=min(length(M), length(x));
er=M(1:N)-x(1:N);
Now, whether that really makes any sense or not is beyond the amount of information we have to judge but it should solve your immediate problem programmatically, anyway.
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