Proving the Continuity of Norms in Hilbert Spaces for q>=p

In summary, the problem is proving that for q>=p and any continuous function f on [a,b], the L^p norm of f is less than or equal to some positive constant c multiplied by the L^q norm of f. The norm is defined as the integral of f^p raised to the power of 1/p over the interval [a,b]. The attempt at a solution involves using the maximum and minimum values of f^p and f^q on the interval, which are both positive, to show that the inequality holds. However, the norm used in the argument is incorrect and should instead use |f|.
  • #1
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Homework Statement


Prove that for q>=p and any f which is continuous in [a,b] then [tex]|| f ||_p<=c* || f ||_q[/tex], for some positive constant c.


Homework Equations


The norm is defined as: [tex]||f||_p=(\int_{a}^{b} f^p)^\frac{1}{p}[/tex].


The Attempt at a Solution


Well, I think that because f is continuous so are f^p and f^q are continuous and on a closed interval which means they get a maximum and a minimum in the interval which are both positive (cause if f were zero then the norm would be zero and the ineqaulity will be a triviality), so f^q>=M2, f^p<=M1, and we get that:
[tex]||f||_p/||f||_q<=M1^{1/p}/M2^{1/q}(b-a)^{1/p-1/q}[/tex] which is a constant.

QED, or not?

Thanks in advance.
 
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  • #2
Your norm is wrong. It should be

[tex]
\|f\|_p=\left(\int_{a}^{b} |f|^p\right)^\frac{1}{p}
[/tex]

This means that you need to argue using |f|, not f. Otherwise, the argument is OK.
 

Related to Proving the Continuity of Norms in Hilbert Spaces for q>=p

1. What is a norm in Hilbert Spaces?

A norm in Hilbert Spaces is a mathematical concept used to measure the size or length of a vector in the space. It is a function that assigns a non-negative value to each vector, with the property that the norm of a vector is equal to zero if and only if the vector is the zero vector.

2. How is a norm defined in Hilbert Spaces?

A norm in Hilbert Spaces is defined as a function that satisfies three properties: non-negativity, homogeneity, and the triangle inequality. Non-negativity means that the norm of a vector is always greater than or equal to zero. Homogeneity means that multiplying a vector by a scalar will result in the norm being multiplied by the absolute value of that scalar. The triangle inequality means that the norm of the sum of two vectors is less than or equal to the sum of their individual norms.

3. What is the purpose of norms in Hilbert Spaces?

The purpose of norms in Hilbert Spaces is to provide a way to measure the size or length of vectors in the space. This is useful in many areas of mathematics, such as functional analysis and optimization, where it is necessary to compare the size of different vectors or determine the convergence of sequences of vectors.

4. Can different norms be defined in the same Hilbert Space?

Yes, it is possible to define multiple norms in the same Hilbert Space. However, the most commonly used norm in Hilbert Spaces is the Euclidean norm, also known as the 2-norm or the L2 norm.

5. How are norms used in the study of Hilbert Spaces?

Norms are used in various ways in the study of Hilbert Spaces. They are used to define inner products, which in turn are used to define orthogonality and projections in the space. Norms are also used to define completeness and convergence in Hilbert Spaces, which are important concepts in functional analysis.

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