Does the product rule fn->f , gn->g imply fngn->fg in (C[0,1],||.||)?

In summary: N, for ||f||1 that is the sum of |f| for all |n| ∈ N, and for ||fg||1 that is the sum of |g| for all |n| ∈ N.
  • #1
cummings12332
41
0

Homework Statement


the product rule fn->f , gn->g implies fngn->fg true in the normed
vector space (C[0,1],||.||) depends on the the norm||.||. Give a proof or a
counterexample for (C[0,1],||.||infinite),(C[0,1].||.||1)

Homework Equations


counterexample , you may wish to examine the case f=g=0 and choose fn=gn for
some piecewise linear functions.

The Attempt at a Solution


what i did for (||.|| infinite) is that ||fn||->||f||, ||gn||->||g|| ,then (||fn||-||f||)*(||gn||-||g||)->0 ,||g||(||fn||-||f||)->0,||f||(||gn||-||g||)->0
then get (||fn||-||f||)*(||gn||-||g||)+||g||(||fn||-||f||)+||f||(||gn||-||g||)=||fn||*||gn||-||f||*||g||->0
therefore ||fn||*||gn||->||f||*||g||
for it is infinite so we get ||fn|||*||gn||=max|fn|*max|gn|=max|fn||gn=max|fngn|=||fngn|| and ||f||*||g||=||fg|| ( by definition of norm) so ||fn*gn||->||fg||
i don't know it is right or wrong

and by the (C[0,1],||.||1) i have no idea to get the counterexample
 
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  • #2
How would you prove the "product rule" for convergent sequences of real numbers? i.e how do you prove, given [itex]a_n\rightarrow a\in\mathbb{R}[/itex] and [itex]b_n\rightarrow b\in\mathbb{R}[/itex], that [itex]a_nb_n\rightarrow ab[/itex]? Notice that [itex]|\cdot|[/itex] is a norm on the real vector space [itex]\mathbb{R}[/itex].

What part of that proof (if any) goes wrong if you try to apply it to the normed vector spaces that you're working with?
 
  • #3
gopher_p said:
How would you prove the "product rule" for convergent sequences of real numbers? i.e how do you prove, given [itex]a_n\rightarrow a\in\mathbb{R}[/itex] and [itex]b_n\rightarrow b\in\mathbb{R}[/itex], that [itex]a_nb_n\rightarrow ab[/itex]? Notice that [itex]|\cdot|[/itex] is a norm on the real vector space [itex]\mathbb{R}[/itex].

What part of that proof (if any) goes wrong if you try to apply it to the normed vector spaces that you're working with?

i proved the product rule by an->a bn->b then (an-a)(bn-b)->0 and a(bn-b)->0 b(an-a)->0 i.e. (an-a)(bn-b)+a(bn-b)+b(an-a)=anbn-ab->0 . should i prove that ||fn||*||gn||->||f||*||g|| instead of ||fngn||->||fg||? but if it is , i don't know what is the differences for the case for index infinite and index 1?
 
  • #4
I don't see anywhere that you are using the difference between those norms and the usual norm on functions.

What is the precise definition of those norms?
 
  • #5
HallsofIvy said:
I don't see anywhere that you are using the difference between those norms and the usual norm on functions.

What is the precise definition of those norms?

for ||fn||1 that is the sum of |fn| , for ||fn||infinte that is the max of |fn|
 

1. What is the product rule in a normed space?

The product rule in a normed space is a mathematical rule that describes how the norm of a product of two vectors in the space relates to the norms of each individual vector. It states that the norm of the product of two vectors is less than or equal to the product of the norms of the individual vectors. In other words, the norm of the product is bounded by the norms of the individual vectors.

2. How is the product rule used in real-world applications?

The product rule is used in many real-world applications, particularly in physics and engineering. It is used to determine the maximum possible error in a measurement or calculation, and to estimate the error in a derived quantity that depends on multiple measurements. It is also used in optimization problems, where it helps to find the minimum or maximum value of a function.

3. What are the main properties of the product rule in normed spaces?

There are several main properties of the product rule in normed spaces. First, it is a generalization of the product rule in calculus, which states that the derivative of a product of two functions is equal to the sum of the individual derivatives. Second, it is a consequence of the triangle inequality, which states that the length of any side of a triangle is less than or equal to the sum of the lengths of the other two sides. Third, it is a fundamental property of normed spaces, which are vector spaces equipped with a norm.

4. How does the product rule relate to other mathematical concepts?

The product rule is closely related to other mathematical concepts such as the triangle inequality, vector norms, and the Cauchy-Schwarz inequality. It is also related to other rules in calculus, such as the quotient rule and the chain rule. In linear algebra, the product rule can be seen as a special case of the Cauchy-Schwarz inequality, which states that the dot product of two vectors is less than or equal to the product of their norms.

5. Are there any exceptions to the product rule in normed spaces?

No, there are no exceptions to the product rule in normed spaces. It holds for all normed spaces, regardless of the specific norm used. However, it may not hold for non-normed vector spaces, where the concept of a norm is not defined. Additionally, in some special cases, the product rule may be simplified or reduced to an equality. For example, in inner product spaces, the product rule reduces to an equality known as the Cauchy-Schwarz inequality.

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