Can a Functional Analysis Problem Be Solved Using a Sequence of Regions?

In summary: I don't know. Let's try that and see what happens. Taking the absolute value of a real-valued function just takes the square of the function.
  • #1
wdlang
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see the attachment
 

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  • #2
Since, in the statement of the problem, f is only required to be continuous, not differentiable, what does f ' mean?
 
  • #3
HallsofIvy said:
Since, in the statement of the problem, f is only required to be continuous, not differentiable, what does f ' mean?

f is continuous means f is infinitely differentiable
 
  • #4
wdlang said:
f is continuous means f is infinitely differentiable

No it doesn't. Assume ##\displaystyle f\left(x\right)=\left|x\right|##. It's obviously continuous (##\displaystyle\forall a\in\mathbb{R}\ \left(\lim_{x\to a}\left|x\right|=\left|a\right|\right)##), but its derivative at 0 doesn't exist.
 
  • #5
Whovian said:
No it doesn't. Assume ##\displaystyle f\left(x\right)=\left|x\right|##. It's obviously continuous (##\displaystyle\forall a\in\mathbb{R}\ \left(\lim_{x\to a}\left|x\right|=\left|a\right|\right)##), but its derivative at 0 doesn't exist.

ok, i mean smooth

sorry for that
 
  • #6
wdlang said:
ok, i mean smooth

sorry for that

Okay. ##\displaystyle\dfrac{x\cdot\left|x\right|}{2}##. It's smooth, but its derivative is |x|.

Though I'm pretty sure you mean continuously differentiable, which is ideally what we'd assume.
 
  • #7
Whovian said:
Okay. ##\displaystyle\dfrac{x\cdot\left|x\right|}{2}##. It's smooth, but its derivative is |x|.

Though I'm pretty sure you mean continuously differentiable, which is ideally what we'd assume.

Actually, I think he DOES mean smooth, a function is smooth (by definition) if it is infinitely differentiable. So your "counter-example" is not valid; in other words, ##\displaystyle\dfrac{x\cdot\left|x\right|}{2}## is not smooth.
 
  • #8
"smooth" is not a standardized term. In some texts it means "infinitely differentiable" but in others it only means "the first derivative is continuous" and "infinitely smooth" is used to mean "infinitely differentiable". In some texts you will even see "sufficiently smooth" meaning "differentiable to whatever extent is necessary to prove this".
 
  • #9
I've also seen "smooth" to mean "analytic" in the sense of Taylor series convergence, which would be separate from "infinitely differentiable".
 
  • #10
OKAY! We get it, there are a lot of different terms for the same thing, and sometimes the same term means different things. Let's focus on the post's question, not some terms; all we need to know is that the function "f is continuous means f is infinitely differentiable", and that's all we need to know to attempt to find a solution. Focus on that.
 
  • #11
Why take the absolute value squared, if the function is real valued? Just take the square of the function, right? Or is that the supremum norm of the function? i.e. [itex] |f| = sup(f) [/itex]
 
  • #12
It loosk like you might be able to make one of those proofs like considering the sequence of regions where |f|<1/n, then blah blah. Not sure if that'll work, but t's first thing that popped into my head.
 

Related to Can a Functional Analysis Problem Be Solved Using a Sequence of Regions?

What is a functional analysis problem?

A functional analysis problem is a type of mathematical problem that involves finding the optimal function that satisfies a given set of constraints. This type of problem is commonly encountered in fields such as economics, engineering, and physics.

What are the steps involved in solving a functional analysis problem?

The first step in solving a functional analysis problem is to define the problem and identify the relevant variables. Next, mathematical models are created and various techniques such as calculus and optimization are used to analyze the problem. Finally, a solution is found by identifying the function that maximizes or minimizes the given objective function while satisfying all constraints.

What are the applications of functional analysis problems?

Functional analysis problems have a wide range of applications in various fields such as economics, engineering, physics, and biology. They are used to analyze and optimize systems, predict outcomes, and make decisions.

What are the common techniques used to solve functional analysis problems?

Some common techniques used to solve functional analysis problems include calculus, linear algebra, convex analysis, and optimization methods such as gradient descent, Lagrange multipliers, and dynamic programming.

What are the limitations of functional analysis problems?

Functional analysis problems can become very complex and difficult to solve for real-world systems with many variables and constraints. In some cases, the optimal solution may not be practical or feasible in the real world due to various limitations and uncertainties.

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