What is the meaning of the norm of a linear functional?

In summary, the norm of a linear functional can be expressed in alternative ways, one of which is sup(|f(x)|/||x||). The definition for the norm of a linear functional can be modified to also include sup(|f(x)|) for ||x|| <= 1.
  • #1
zok_peltek
3
0
Hi everyone,

I have been studying "Optimization by Vector Space Methods", written by David Luenberger and I am stuck in an obvious point at first glance. My problem is in page 105, where the norm of a linear functional is expressed in alternative ways. The definition for the norm of a linear functional f is (from now on ||y|| denotes the norm of y and |y| the absolute value of y):
||f|| = inf{M: |f(x)| <= M*||x|| for every x in X} where X is the vector space the functional is defined on.

now this definition can be modified and give:
||f|| = inf{M: |f(x/||x||)| <= M for every x in X and x not zero} since f is linear which is equivalent to:
||f|| = sup(|f(x)|/||x||) for x not zero or
||f|| = sup(|f(x)|) for ||x|| = 1

now in the book it states that also:
||f|| = sup(|f(x)|) for ||x|| <= 1
which I can't compehend given the previous definition.

any help is much appreciated,
zok
 
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  • #3
welcome to pf!

hi zok! welcome to pf! :smile:
zok_peltek said:
||f|| = sup(|f(x)|) for ||x|| = 1

now in the book it states that also:
||f|| = sup(|f(x)|) for ||x|| <= 1
which I can't compehend given the previous definition.

aren't they the same?

eg if ||x|| = 1, then f(0.5x) = 0.5f(x) since f is linear, so |f(0.5x)| < |f(x)| ?
 
  • #5
Note that [itex]\big\{|f(x)|\, \big| \,\|x\|=1\big\}\subset \big\{|f(x)|\,\big|\,\|x\|\leq 1\big\}[/itex]. Let's call the first set A and the second set B. We have [itex]A\subset B[/itex]. This means that [itex]\sup A\leq\sup B[/itex]. On the other hand, you can easily show that an arbitrary member of B is smaller than sup A. This means that sup A is an upper bound of B, but sup B is the least upper bound, so [itex]\sup B\leq\sup A[/itex].

(Click the quote button if you want to see how I did the math).

You might also want to check out this thread.
 

1. What is the norm of a linear functional?

The norm of a linear functional is a measure of its size or magnitude. It represents the distance from the origin to the point where the functional takes its maximum value.

2. How is the norm of a linear functional calculated?

The norm of a linear functional can be calculated using the supremum or the maximum value of the functional. It is the smallest upper bound of the functional's values, and is usually denoted by ||f|| or ||f||.

3. What is the significance of the norm of a linear functional?

The norm of a linear functional is important in functional analysis as it provides a way to measure the distance between different functionals. It is also used in various mathematical fields and has applications in physics and engineering.

4. How does the norm of a linear functional relate to the dual space?

The norm of a linear functional is closely related to the dual space, which is the set of all linear functionals on a given vector space. The norm of a functional is used to define a topology on the dual space, making it a metric space.

5. Can the norm of a linear functional be infinite?

Yes, the norm of a linear functional can be infinite. This occurs when the supremum or maximum value of the functional is unbounded. In such cases, the functional is said to be unbounded and does not have a finite norm.

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