L2 Norm of +Infinity: Admitted & Defined

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Discussion Overview

The discussion revolves around the properties of infinite-dimensional vector spaces, specifically focusing on the L2 norm and inner products. Participants explore the implications of defining inner products on sequences of real numbers and the conditions under which these norms can be infinite. The conversation also touches on the definition of orthonormal bases in such spaces and the relationship between different spaces, such as l2 and L2, as well as the role of complex sinusoids and Fourier transforms.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • Some participants question whether vectors in an infinite-dimensional space can have an L2 norm that equals +Infinity and discuss the conditions under which this is admitted.
  • One participant suggests that sequences with infinite norms can still be part of an inner product space if the series defining the inner product does not converge.
  • Another participant clarifies the distinction between the spaces l2 and L2, emphasizing that l2 consists of sequences where the sum of squares is finite, while L2 involves functions with finite integrals.
  • A later reply introduces the concept of complex sinusoids and their infinite norm, questioning the implications for orthogonality and basis definitions in the context of Fourier transforms.
  • One participant proposes that the Fourier transform of complex exponentials results in a delta distribution, suggesting that the appropriate space for such transforms is that of distributions rather than L2.
  • There is uncertainty regarding whether complex exponentials form a basis in the context of distributions, with one participant expressing doubt about their status as a Hamel basis.

Areas of Agreement / Disagreement

Participants express differing views on the treatment of infinite norms in inner product spaces, with some arguing that such norms are permissible while others emphasize the need for convergence. The discussion remains unresolved regarding the nature of bases for spaces involving complex sinusoids and the implications of Fourier transforms.

Contextual Notes

Limitations include the dependence on definitions of convergence and the nature of inner product spaces. The discussion also highlights the potential ambiguity in the treatment of infinite-dimensional spaces and the mathematical rigor required in defining norms and bases.

mnb96
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Hello,
I have a (infinite dimensional) vector space and defined an inner product on it.
The vectors element are infinite sequence of real numbers (x_1, x_2,\ldots).
The inner product has the common form: x_iy_i

The problem now is that the vectors have an infinite number of elements, so the L2-norm of many vectors would be eventually equal to +Infinity.

- Is that admitted?
- How can one define an orthonormal base for such a space?
 
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Are the vectors sequences that are eventually zero?
 
mnb96 said:
Hello,
I have a (infinite dimensional) vector space and defined an inner product on it.
The vectors element are infinite sequence of real numbers (x_1, x_2,\ldots).
The inner product has the common form: x_iy_i
You mean \sum^{\infty}_{i=1}x_iy_i
mnb96 said:
The problem now is that the vectors have an infinite number of elements, so the L2-norm of many vectors would be eventually equal to +Infinity.

- Is that admitted?
Yes, provided you restrict yourself to the subspace of sequences that have a finite norm, that is, for which the infinite series \sum x_i^2 converges to a finite limit. Ignore the series that do not converge -- those sequences are not elements of the inner product space.

mnb96 said:
- How can one define an orthonormal base for such a space?
How would you answer this for the space of sequences of length N? It's almost the same answer here.

(By the way, this post should really be in the Linear & Abstract Algebra forum!)
 
I am not sure about what I am about to say, but as far as I understood, the inner-product that goes to +Infinity is always admitted: there is nothing in the definition of inner-product that prevents it to be so.

Since an inner-product-space is apparently just a vector space with an inner product, we have to admit that also those series \sum^{\infty}_{i=1}x_iy_i which do not converge are allowed. So, the vectors with Infinite norm are still in the inner product space.

If you add the requirement that those series have always to converge, then you are defining an Hilbert-Space (complete metric).

Now, if we have an Hilbert-space, it is probably easier to define an orthonormal basis.
I am not sure it is possible to define always an orthonormal base for inner products, as I can't see how you could (for example) normalize the squared integral of a sinusoid extendind through the whole real line.
 
I think there is confusion here as to what, exactly L2 means.

The space l2 (small l) is defined as "the set of all infinite sequences {an} such that \sum a_n^2 is finite". The l2 norm is then defined as \sum a_n^2 which is now guaranteed to be finite. And that norm can be derived from an "inner product" \{a_n\}\cdot\{b_n\}= \sum a_nb_n which can be shown to always exist.

The space L2 Is defined as the set of functions, f(x), is defined to be the set of functions, defined on some set A, such that \int_A (f(x))^2 dx is finite. Now the "L2" is defined to be that integral which is not guaranteed to be finite. And, again, it can be derived from the inner product, f\cdot g= \int_A f(x)g(x) dx.

That is, the "L2 norm" and "l2" are not defined independently of the set of "vectors".
 
thanks for the clarification!
Now, in this context, could you please explain what happens if we consider the space of the real functions obtainable by sum of complex sinusoids?

The complex sinusoids (from -Inf to +Inf) have infinite norm. This means we are not in L_{2} anymore. However the sinusoids are still orthogonal(?), so we must conclude they are a basis for some space, but what space?

In other words, when we simply take a Fourier Transform of a function from -Inf to +Inf, what are we actually doing?
 
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To ease explanation, consider the complex exponentials e-ikx instead of sines and cosines, and consider the complex exponential version of the Fourier transform.

If you give it a bit of thought, you will realize that the Fourier transform of e-ikx is not actually a function, but rather a delta "function" (really, the delta distribution). Why? e-ikx is a perfect wave of a single frequency, so it's Fourier transform has all of the weight concentrated at a single point k, and no weight at any other frequencies.

Therefore the natural space to think about Fourier transforms of things like e-ikx is a space of distributions. The space commonly used is the dual space to the Schwarz space, and then the Fourier transform is F:S'->S' rather than F:L2->L2.

The complex exponentials might form a Schauder basis for S', though I highly doubt it. They certainly don't form a Hamel basis. This is actually an interesting question.
 
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