intermediate exponential calculation goes to infinity
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Albert Hall
am 19 Jun. 2019
Kommentiert: Steven Lord
am 24 Jun. 2019
trying to calculate y = exp(-t).*cumtrapz(t,(exp(t).*x));
were x is a bounded vector and t is corresponding time stamp vector
y Output is finite but intermediate values of the exponent exceed matlab capability for large numbers
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John D'Errico
am 19 Jun. 2019
Bearbeitet: John D'Errico
am 19 Jun. 2019
Calc 101.
An integral is a linear operator. You can move any multiplicative constant inside or outside of the integral.
Suppose you write t as:
tmax + (t - tmax)
where
tmax = max(t)
Does this help you? It should. Try substituting into your expression. What will happen? Look carefully.
y = exp(-(tmax + (t-tmax))).*cumtrapz(t,(exp(tmax + (t - tmax)).*x));
remember. tmax is a constant. What is
exp(-tmax)*exp(tmax)
Hint: exp(0) = 1
That lets you reduce the problem a bit:
y = exp(-(t-tmax)).*cumtrapz(t,(exp(t - tmax).*x));
Since t-tmax is now never larger than 0, exp(t-tmax) is never a large number.
3 Kommentare
Steven Lord
am 19 Jun. 2019
What are the bounds of your vector t? What are the minimum and maximum values it contains?
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Albert Hall
am 19 Jun. 2019
2 Kommentare
Steven Lord
am 24 Jun. 2019
Then you would need to use an arbitrary precision system like Symbolic Math Toolbox. Let's see what exp(79391) is:
>> vpa(exp(sym(79391)), 6)
ans =
1.18362e34479
To put that into perspective, that's a really big number. You're in the section about one googol to one googolplex in this Wikipedia article, which includes numbers like the number of legal positions in the game of Go (about 2e170), approximate number of Planck volumes in the observable universe (around 1e186), or number of distinguishable permutations in the 33-by-33-by-33 Rubix Cube (around 2e4099.) Your number is much larger than any of those.
By comparison, an upper bound on the number of legal chess positions is about 4.52e46, and the number of fundamental particles in the observable universe is estimated at 1e80 to 1e85.
What exactly are you trying to compute with this calculation? There may be a way to avoid needing to compute using such huge (and tiny, since you also use exp(-t) in your code) numbers. The probability that a monkey will type Shakespeare's Hamlet on its first try is much smaller than exp(-t), but it might be the probability of that monkey typing a sonnet or two on its first try.
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