MHB Differentiating an integral wrt a function

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The discussion revolves around differentiating the integral of the form $\int_S f \ln f$ with respect to the function $f$. Participants clarify that the integral likely represents $\int_S f(x) \ln f(x) dx$, leading to the conclusion that the derivative is $\ln f(x)$. Further clarification is sought regarding the notation and the context of the functional $J(f)$, which includes terms that involve $\lambda$ parameters and suggests $f$ may not be a simple function but rather an element of a convex set. The conversation highlights the need for clear definitions of symbols and notation from the referenced book to avoid confusion. Overall, the discussion emphasizes the importance of understanding the underlying mathematical concepts and notation in functional differentiation.
OhMyMarkov
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Hello everyone!

I've came across this problem: differentiate $\int _S f \ln f$ with respect to $f$. From previous explanation, I believe $\int _S f \ln f$ means $\int _S f(x) \ln f(x)dx$.

The answer is $\ln f(x)$... Could anyone indicate how they reached this answer?

Thanks!
 
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OhMyMarkov said:
Hello everyone!

I've came across this problem: differentiate $\int _S f \ln f$ with respect to $f$. From previous explanation, I believe $\int _S f \ln f$ means $\int _S f(x) \ln f(x)dx$.

The answer is $\ln f(x)$... Could anyone indicate how they reached this answer?

Thanks!

Hi OhMyMarkov! :)

I suspect that should read $\int _S^f \ln f df$.

Suppose the anti-derivative of ln(x) is LN(x), then it follows that:

$\frac{d}{df}(\int _S^f \ln f df) = \frac{d}{df}(\int _S^f \ln x dx) = \frac{d}{df}(LN( f ) - LN( S )) = \ln f$
 
Hello ILikeSerena, thanks for replying!

Okay, now I have the book, please let me give out the exact statement:

$h(f )$ is a concave function over a convex set. We form the functional:

\begin{equation}
\displaystyle J(f )= -\int f\ln f + \lambda _0 \int f + \sum _k \lambda _k \int f r_k
\end{equation}

and "differentiate" with respect to $f(x)$, the $x$th component of $f$, to obtain

\begin{equation}
\displaystyle \frac{\partial J}{\partial f(x)} = -\ln f(x) -1 +\lambda _0 + \sum _k \lambda _k r_k (x)
\end{equation}

Perhaps the problem statement is now clearer...
 
Hmm, things certainly have changed.

I'm looking at what is some unconventional notation.
Perhaps you can clarify some of it, because I'm guessing a little bit too much.
Your book should define the symbols and notation used somewhere, typically at the beginning of the chapter or the introduction of the book.

From h(f) is a concave function on a convex set, I deduce that f is an element of a convex set.
That suggests that f is not a function, but for instance an element of R^n.
Is it, or could it be a function?

Looking at the results, it appears that $\int f \ln f$ means $\int df \ln f$, that is ln f integrated with respect to f.
Could that be it?
In that case everything appears to work out, except for the "-1"...

For the integrals no boundary is specified.
But the calculation suggests a constant lower bound, perhaps minus infinity, and an upper bound of f, or something like that...?

Can you clarify what f(x), the xth component of f is supposed to mean?
 
We all know the definition of n-dimensional topological manifold uses open sets and homeomorphisms onto the image as open set in ##\mathbb R^n##. It should be possible to reformulate the definition of n-dimensional topological manifold using closed sets on the manifold's topology and on ##\mathbb R^n## ? I'm positive for this. Perhaps the definition of smooth manifold would be problematic, though.

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