Convergence with L2 norm functions

In summary, the conversation discusses how to show that if a sequence of square-integrable functions converges to a function in norm, then the inner product of the sequence with any function in the same space also converges to the inner product of the function with the same function. The approach involves using the Cauchy Schwarz inequality and the properties of norm convergence and inner products.
  • #1
tom_rylex
13
0

Homework Statement


(I'm posting this because my proofs seem to be lousy. I want to see if I'm missing anything.)
Show that if [tex] f_n \in L^2(a,b) [/tex] and [tex] f_n \rightarrow f [/tex] in norm, then [tex] <f_n,g> \rightarrow <f,g> [/tex] for all [tex] g \in L^2(a,b) [/tex]

Homework Equations


[tex] L^2(a,b) [/tex] is the space of square-integrable functions,
[tex] {f_n} [/tex] is a finite sequence of piecewise continuous functions, and
< , > is the inner product


The Attempt at a Solution



I started with a linear combination of inner products and applied the Cauchy Schwarz inequality:
[tex] \vert <f_n - f,g> \vert \leq \Vert f_n - f \Vert \Vert g \Vert [/tex]
By the definition of norm convergence, I have
[tex] \Vert f_n - f \Vert \rightarrow 0 [/tex], which means that
[tex] \vert <f_n - f,g> \vert \rightarrow 0 [/tex]
Since this is absolutely convergent, that means that
[tex] <f_n,g> - <f,g> [/tex] is also convergent to 0. So therefore,
[tex] <f_n,g> -<f,g> \rightarrow 0[/tex]
[tex] <f_n,g> \rightarrow <f,g> [/tex]

Is that reasonable? Or am I missing something?
 
Physics news on Phys.org
  • #2
I suggest going from <fn - f , g> ---> 0 to <fn , g> - <f , g> ---> 0 more explicitly.
 
  • #3
As in:
<fn-f,g> --> 0 (absolutely convergent series are convergent)
<fn,g> - <f,g> --> 0 (linearity property wrt the first variable for inner products)
 

1. What is the L2 norm?

The L2 norm is a mathematical concept that measures the distance between two points in a vector space. It is also known as the Euclidean norm and is calculated by taking the square root of the sum of squared values of a vector's elements.

2. What is convergence with L2 norm functions?

Convergence with L2 norm functions refers to the behavior of a series of functions that approach a limit as the number of iterations increases. In other words, the functions get closer and closer to a specific value as more and more iterations are performed.

3. How is convergence with L2 norm functions useful?

Convergence with L2 norm functions is useful in various fields of science and engineering, such as optimization, numerical analysis, and machine learning. It allows for the estimation of the accuracy of a solution and can help determine the optimal parameters for a given problem.

4. What are some examples of L2 norm functions?

Some common examples of L2 norm functions include the least squares method, which is used to find the best-fitting line for a set of data points, and the gradient descent algorithm, which is used for optimizing functions in machine learning and data science.

5. How is convergence with L2 norm functions different from other types of convergence?

Convergence with L2 norm functions is a specific type of convergence that is based on the L2 norm. It differs from other types of convergence, such as pointwise convergence, uniform convergence, and absolute convergence, which are based on other mathematical concepts and have different properties and applications.

Similar threads

  • Calculus and Beyond Homework Help
Replies
5
Views
1K
  • Calculus and Beyond Homework Help
Replies
6
Views
2K
  • Calculus and Beyond Homework Help
Replies
4
Views
311
  • Calculus and Beyond Homework Help
Replies
18
Views
1K
  • Calculus and Beyond Homework Help
Replies
12
Views
1K
Replies
0
Views
316
  • Calculus and Beyond Homework Help
Replies
5
Views
1K
  • Calculus and Beyond Homework Help
Replies
1
Views
893
  • Calculus and Beyond Homework Help
Replies
15
Views
1K
  • Calculus and Beyond Homework Help
Replies
2
Views
842
Back
Top