Hello,
[Edit: The whole thing has a very simple solution: the matrix used the single datatype instead of the default double]
I have just noticed a somewhat peculiar (I think) behaviour in matlab and wonder what's causing it. I have a 10000x500 matrix M with values ranging from
min(min(M)) = -226.9723 to
max(max(M)) = 92.8173
and
exp(-227) = 2.6011e-99
exp(93) = 2.4512e+40
but if I exp the entire matrix, this matrix has inf values:
ii = isinf(exp(M));
sum(sum(ii))
ans =
2
How does Matlab store the values in the matrix so that operations on individual elements can give a different result than when doing the same operation on the matrix itself?
I.e.
expM = exp(M);
exp(M(1)) == expM(1) ; %can be false, which I find surprising
I know I have to change the algorithm anyway as the high exponents will give inexact results even if I can avoid inf values. It happens in a formula for a artificial neural network calculation like:
sum(log(1+exp(ones(numcases,1)*b_h + data*w_vh)),2);
so my plan is to split this up into two cases, first where the exponent is small I do the calculation as above, for high values I approximate
log(1+exp(ones(numcases,1)*b_h + data*w_vh)
with
ones(numcases,1)*b_h + data*w_vh
Does that sound reasonable? My reasoning of course is that
log(1+exp(x)) ≈ log(exp(x)) ≈ x, for large x
btw: is there a better way to get the maximum element of a matrix other than doing max twice as in max(max(M))?