So, my question is, where did I go wrong in my approach?

In summary, the conversation discusses using Bessel's inequality to show that the dimension of a subspace S of L^2([0,1]) is at most K^2, where K is a constant such that |f(x)| ≤ K||f|| for all f in S. The conversation includes attempts to use an orthonormal basis for S and a function f= u1 + ... + um, but leads to a contradiction. It is also suggested that the problem may be incorrect.
  • #1
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Let S be a subspace of [tex]L^{2}(\left[0,1\right])[/tex] and suppose [tex]\left|f(x)\right|\leq K \left\| f \right\|[/tex] for all f in S.

Show that the dimension of S is at most [tex]K^{2}[/tex]

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The prof hinted us to use Bessel's inequality.

Namely, let [tex]\left\{ u_1,\dots, u_m \right\}[/tex] be a set of orthonormal vectors in [tex]L^{2}(\left[0,1\right])[/tex]. Then [tex]\left\| f \right\|^2 \geq \sum_{k=1}^m \left| \left\langle f, u_k \right\rangle\right|^2[/tex]

I just keep getting stuck, and getting things like

[tex]\left\|f \right\|^2 =\int_0^1 \left|f(x)\right|^2 dx \leq \int_0^1 K^2 \left\|f \right\|^2 dx = K^2 \left\|f \right\|^2[/tex]

and I can't figure out how to apply Bessel's inequality.

I guess the goal is to assume m linear independent vectors, and show that m is less than K^2. Help, please?
 
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  • #2
haven't totally put it together yet, but I'm thinking start with assuming an orthonormal basis for S:{...,ui ...} of dimension m.

Try expanding f in terms of the basis function & then knowing both the ui and f satsify the given inequality, hopefully you can find a contradiction if m>K2 as you say
 
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  • #3
considering a function which is a certain linear combination of an orthogonal basis for S should help. As S is a subspace, its closed under linear combinations, so the function is contained in S
 
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  • #4
Still at a loss...

So: Assume {u1, ..., um} is an orthonormal basis of S.
I'm trying the function f= u1 + ... + um. Is this the right one to consider? It certainly is the nicest.

Then ||f|| = sqrt(m).

I still don't know where exactly to apply the Bessels inequality. If I do, all I keep getting is that
m^2 < m^2 K
which tells me nothing.

More help? Thanks for the response.
 
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  • #5
must be missing something.. thought it would follow on, but when i went to work it completely, went in a circle...

now I'm not even so sure i understand the question correctly, what about sinusoidal basis functions, couldn't you have an infinite orthogonal number of those with ||f|| =1, and maximum magnitude ~ sqrt(2)

will pass it on to some of the other guys to have a look
 
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  • #6
Ok, I'm started off with a different approach to see if I could understand this a bit better... and it only leads me to believe that the problem must be wrong.
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Assume K=1 (since that is the smallest it can be). Then S is the set of functions on [0,1] such that |f(x)| < ||f|| for all x in [0,1]. For simplicity, let's just say that ||f|| =1.

But the integral of |f(x)|^2 from 0 to 1 must be 1, and |f(x)| can never be less than 1. Thus, it must be the case that |f(x)|=1 for all x on the interval.

So the modulus of f(x) is always 1, and thus [tex]f(x)=e^{ia(x)}[/tex] for some function a(x).

Then the inner product of f with some other function g is
[tex]\left\langle f,g\right\rangle=\int_0^1 e^{i(a(x)-b(x))}dx[/tex].

But this integral does not necessarily have to have a modulus of 1 (indeed consider a(x)=2x and b(x)=x), and thus g is not a multiple of f. This leads me to believe that there must be more than one function in the basis for S, a contradiction to the dimension of S being less than or equal to K=1.
 
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1. What is a finite subspace of L2?

A finite subspace of L2 is a subset of the space L2 (the space of square-integrable functions) that contains a finite number of elements. In other words, it is a vector space of functions that is finite-dimensional.

2. What are the properties of a finite subspace of L2?

A finite subspace of L2 has the following properties:

  • It is a vector space, meaning that it is closed under addition and scalar multiplication.
  • It is finite-dimensional, meaning that it has a finite basis.
  • It is a closed subspace, meaning that it contains all of its limit points.
  • It is a bounded subspace, meaning that all of its elements have finite norm.

3. How is a finite subspace of L2 different from an infinite subspace?

A finite subspace of L2 is different from an infinite subspace in that it contains a finite number of elements, while an infinite subspace contains an infinite number of elements. This means that a finite subspace has a finite basis, while an infinite subspace may not have a basis at all.

4. How is a finite subspace of L2 used in mathematics?

A finite subspace of L2 is used in mathematical analysis, particularly in the study of Hilbert spaces. It is also used in functional analysis, where it serves as a finite-dimensional approximation to the infinite-dimensional space L2.

5. Can a finite subspace of L2 be extended to an infinite subspace?

Yes, a finite subspace of L2 can be extended to an infinite subspace by adding more elements to the subspace. However, this extension may not always be possible or desirable, depending on the specific application and properties of the subspace.

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