Proving Alternating Derivatives with Induction in Mathematical Analysis I

In summary, the author claims that for every two integers ##n\ge 2##, there exists a function satisfying the assumptions listed which alternates its sign in a finite number of points in the interval (-1,1).
  • #1
Unconscious
74
12
Hi forum.
I'm trying to prove a claim from Mathematical Analysis I - Zorich since some days, but I succeeded only in part.
The complete claim is:

$$\left\{\begin{matrix} f\in\mathcal{C}^{(n)}(-1,1) \\ \sup_{x\in (-1,1)}|f(x)|\leq 1 \\ |f'(0)|>\alpha _n \end{matrix}\right. \Rightarrow \exists x_1,...,x_n \in (-1,1) : f^{(n)}(x_i)f^{(n)}(x_{i+1})=\pm (-1)^i $$

for ##i=1,...,n-1##.

In natural language: there exists an ##\alpha _n## such that for every ##f## satisfying the properties listed, then we have that ##f^{(n)}(x)## alternates its sign in ##n## points inside ##(-1,1)##.

I thought that induction can solve the problem.
So, I started proving the claim for ##n=2##, and this can be done simply by reductio ad absurdum using Taylor expansion at order 2 with Lagrange remainder.

I can't start the induction chain, supposing that it's true for ##n## and proving it by ##n+1##.
The book suggests me to use this property:

$$\inf_{x\in I}|f(x)| \leq \frac{1}{|I_2|}\left(\inf_{x\in I_1}|f(x)|+\inf_{x\in I_3}|f(x)|\right)$$

which is valid for every interval (open or closed) ##I\subset (-1,1)## partitioned as ##I=I_1 \cup I_2 \cup I_3## (##I_1##, ##I_2## and ##I_3## with no points in common except at most the boundary points).
An example of partition can be ##I=[a,b]\cup [b,c]\cup [c,d]##.

Any hint?

Thanks in advance.
 
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  • #2
This problem is not stated in a clear way. At least, it is not clear to me what is assumed and what is the conclusion to be proved.
 
  • #3
Erland said:
it is not clear to me what is assumed and what is the conclusion to be proved.
Property listed (assumptions):

$$\left\{\begin{matrix} f\in\mathcal{C}^{(n)}(-1,1) \\ \sup_{x\in (-1,1)}|f(x)|\leq 1 \\ |f'(0)|>\alpha _n \end{matrix}\right.$$

What we have to deduce from the assumptions:

##f^{(n)}## alternates its sign in ##n## points in ##(-1,1)##.
 
  • #4
Unconscious said:
Property listed (assumptions):

$$\left\{\begin{matrix} f\in\mathcal{C}^{(n)}(-1,1) \\ \sup_{x\in (-1,1)}|f(x)|\leq 1 \\ |f'(0)|>\alpha _n \end{matrix}\right.$$

What we have to deduce from the assumptions:

##f^{(n)}## alternates its sign in ##n## points in ##(-1,1)##.
But this is not true even for ##n=1##. No matter how big ##\alpha_1>0## is, there are always functions satifying the assumptions, with the given ##\alpha_1##, such that the conclusion is false.

For example, take:
$$f(x)=\frac2\pi\arctan( \frac\pi2(\alpha_1+1)x).$$
Then, ##f'## is positive everywhere, and thus does not change sign anywhere. Yet, the assumptions hold, with ##f'(0)=\alpha_1+1##.
 
  • #5
The statement has sense only for ##n=2## on, because:

f' changes its sign in one point

has no sense.
It is clearer if we look at the statement in its math language and not in its natural language, in particular the expression after the "##\Rightarrow##" in #1.
 
Last edited:
  • #6
OK, sorry for the misunderstanding about changing/alternating sign. I think I understand what you mean now. You mean:

For each integer ##n\ge 2## there exists an ##\alpha_n\in \Bbb R##, such that for all functions ##f## who satisfy
$$\left\{\begin{matrix} f\in\mathcal{C}^{(n)}(-1,1) \\ \sup_{x\in (-1,1)}|f(x)|\leq 1 \\ |f'(0)|>\alpha _n\,, \end{matrix}\right.$$
there are ##x_1,\, x_2,\,\dots x_n\in \Bbb R## such that ##-1<x_1<x_2<\dots <x_n<1## and such that ##f^{(n)}(x_i)f^{(n)}( x_{i+1})<0## for ##i=1,\,2,\,\dots n-1##.

This is what you mean, right?

Not so easy, it seems to me.
 
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  • #7
Yes, this is what we have to prove.
For ##n=2## all right, but for ##n>2##... :cry:
 
  • #8
Well, if we have ##-1<x_1<x_2<\dots<x_n<1## such that ##f^{(n)}(x_i)f^{(n)}(x_{i+1})<0## for ##i=1,\,2,\dots,n-1##, then it follows easily by the Mean Value Theorem that there are ##y_1, \,y_2,\dots,y_{n-1}## such that ##-1<x_1<y_1<x_2<y_2<\dots<y_{n-1}<x_n<1##, with ##f^{(n+1)}(y_i)f^{(n+1)}(y_{i+1})<0## for ##i=1,\,2,\dots,n-2##. But we need two more such ##y_i##:s. Can we prove that there are ##y_0<x_1## and ##y_n>x_n## extending this sequence of points with alternating sign of ##f^{(n+1)}##, or that the conclusion still holds if this is not true?
 
  • #9
This is exactly my proof attempt!
We have done the same mind-path, and I can’t go further from this point.
So, I can’t answer your last question because I don’t know the answer.
 
  • #10
In order to get a proof by induction to work, I think we need bounds for the derivatives, independent of ##f##. I think it suffices to give bounds for the derivatives not everywhere in ##(-1,1)##, but at separate points with arbitrary density, where the bound may depend upon the density.

I think the following might be useful, which is proved by induction on ##n##:

If ##f## satisfies the first two conditions in post #6, and ##m \ge n##, then, to every open subinterval ##I\subset (-1,1)## of length ##3^{n-m}##, there exists a ##c\in I## such that
$$|f^{(n)}(c)|\le 2^n3^{\frac{n(2m-n+1)}2}.$$
 
  • #11
I'm thinking on this.
If I have news I'll post them here.

Thanks for your time.
 

1. What is the concept of boundedness of derivatives?

Boundedness of derivatives is a mathematical concept that refers to the behavior of a function's derivative at a specific point or interval. It describes whether the rate of change of a function is limited or unbounded in a given region.

2. How is boundedness of derivatives related to continuity?

A function is said to be continuous if it is differentiable at all points in its domain. If a function's derivative is bounded at a point, it means that the function is continuous at that point. However, a continuous function may not necessarily have a bounded derivative.

3. What is the significance of boundedness of derivatives in real-world applications?

In real-world applications, boundedness of derivatives is important in understanding the behavior of physical systems and predicting their future states. For example, in physics, the derivative of an object's position with respect to time can provide information about its velocity, and the boundedness of this derivative can indicate whether the object is accelerating or moving at a constant speed.

4. How can we determine if a function's derivative is bounded?

To determine if a function's derivative is bounded, we can use the Mean Value Theorem, which states that if a function is continuous on a closed interval and differentiable on the open interval, then there exists at least one point within the interval where the derivative is equal to the average rate of change of the function over that interval. If the function's derivative is bounded on the interval, then it must also be bounded at that point.

5. What are some common misconceptions about boundedness of derivatives?

One common misconception is that if a function's derivative is bounded, then the function itself must also be bounded. However, this is not always true, as a function can have a bounded derivative but still have unbounded values. Another misconception is that a function must have a bounded derivative to be continuous, but as mentioned earlier, this is not always the case.

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