How to Estimate the Operator Norm ||A||_2 for a Difference Operator?

In summary, the conversation discusses the use of operator norms and inner product in solving a set of tasks. The person asks for help and shares their thoughts on how to calculate a non-trivial upper bound. They estimate ||A||_1 and ||A||_\infty, but are unsure about ||A||_2. Another person suggests using the singular value decomposition to find the operator norm and recommends double-checking the estimations for ||A||_1 and ||A||_\infty. They also mention that it may not be necessary to use the max function to find an upper bound.
  • #1
Max Fleiss
1
0
Greetings everyone!

I have a set of tasks I need to solve using using operator norms, inner product... and have some problems with the task in the attachment. I would really appreciate your help and advice.

This is what I have been thinking about so far:
I have to calculate a non trivial upper bound, so maybe it could be done by:
[tex] b=max( ||A||_1,||A||_2,||A||_\infty ) [/tex]

Since [tex] A [/tex] is a difference operator I estimated the following:
[tex] ||A||_1= 4 [/tex]
[tex] ||A||_\infty= 2 [/tex]
But how can I estimate [tex]||A||_2=?[/tex]
If I know that abs row sum is 2 (besides 0 there appears only one 1 and one -1 in the rows) and abs column sum is 4 (it is two times the size of row length dim(A)=2mn x mn). Can I estimate [tex]||A||_2[/tex] by:
[tex]||A||_2=\sqrt{rows^2+columns^2 }=\sqrt{(2 \cdot 2mn)^2+(4 \cdot mn)^2}[/tex][tex]=4 \sqrt{(mn)^2+(mn)^2}=4 \sqrt{2} \sqrt{m^2n^2}[/tex] since [tex]mn[/tex] are positive [tex]||A||_2=4 \sqrt{2} mn[/tex]
So I would say [tex]b=max(L_1,L_2,L_\infty)=L_2=4 \sqrt{2} mn[/tex]

Is my conclusion, approximation of a non trivial upper bound b right?

Thank you in advance for your help!
 

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  • #2
It is not clear why you use different norms here. In any case, you need to investigate ##||Ax||## for any ##x##. Application of ##A## on ##x## should give you an idea for un upper bound, i.e. you need to use the definition of ##A## somewhere, since not all operators are bounded.
 
  • #3


Hi there,

Thanks for sharing your thoughts on this problem. It seems like you have made some good progress so far. However, I have a few suggestions for your approach.

Firstly, it is important to note that the operator norm ||A||_2 is defined as the maximum singular value of A, which is different from your estimation of ||A||_2 as the square root of the sum of squares of the row and column sums. So, your estimation may not be accurate.

To calculate the operator norm, you can use the singular value decomposition (SVD) of A, which gives you the singular values of A in descending order. The maximum singular value will give you the operator norm.

Also, it is not necessary to use the max function to find the upper bound b. You can simply use the operator norms ||A||_1, ||A||_2, and ||A||_\infty to find an upper bound.

I would also recommend double-checking your estimations for ||A||_1 and ||A||_\infty, as they seem a bit low for a difference operator.

I hope this helps. Good luck with your task!
 

Related to How to Estimate the Operator Norm ||A||_2 for a Difference Operator?

What is the "operator norm upper bound"?

The operator norm upper bound is a mathematical concept used in functional analysis to measure the size or magnitude of a linear operator on a vector space. It is also known as the operator norm or operator norm bound.

How is the operator norm upper bound calculated?

The operator norm upper bound is calculated as the maximum value that the operator norm can take on a given vector. This value is obtained by taking the supremum (or least upper bound) of the operator norm over all possible vectors in the vector space.

What is the significance of the operator norm upper bound?

The operator norm upper bound provides a useful upper limit for the size of a linear operator, allowing for comparisons between different operators and for convergence tests in functional analysis. It also has applications in other areas such as numerical analysis and optimization.

How is the operator norm upper bound related to other mathematical concepts?

The operator norm upper bound is closely related to the concept of bounded linear operators, which are operators that do not grow too quickly in magnitude. It is also connected to the spectral norm, which is another norm used to measure the size of an operator.

What are some practical applications of the operator norm upper bound?

The operator norm upper bound has numerous applications in mathematics, physics, and engineering. It is used in areas such as differential equations, control theory, signal processing, and quantum mechanics. It also has applications in machine learning and data analysis.

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