Linear algebra+ linear operators

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Homework Help Overview

The discussion revolves around the induced norm of a linear operator in the context of linear algebra, specifically focusing on a norm defined in R³ as ||x|| = a₁|x₁| + a₂|x₂| + a₃|x₃|, where aᵢ > 0. Participants are exploring the implications of this norm on the operator A and its properties.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • Participants discuss the relationship between the matrix representation of the operator A and the defined norm, with some suggesting that the problem simplifies to maximizing an inner product. Others question the dependence of the induced norm on the coefficients aᵢ and seek proofs for various assertions regarding eigenvalues and properties of the operator.

Discussion Status

The discussion is active, with participants offering different interpretations of the problem and questioning each other's reasoning. Some have provided insights into the mathematical properties involved, while others express confusion about specific aspects, such as the proof of eigenvalue nonnegativity and the implications of the Cauchy-Schwarz inequality.

Contextual Notes

There is an ongoing debate about whether the expression given represents a matrix operator and how the defined norm influences the induced norm on linear operators. Participants are also navigating the implications of the definitions and properties of norms in this context.

Mechmathian
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Homework Statement



In R^{3} ||x||= a_{1}*|x_{1}|+ a_{2}*|x_{2}|+ a_{3}*|x_{3}|. where a_{i}>0

What is ||A||(indused norm = sup||Ax|| as ||x||=1). (Suppose we know the coeffisients of the matrix/operator A)??


Homework Equations





The Attempt at a Solution


 
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If A is given by a matrix, it's the square root of the largest eigenvalue of AA* (*=hermitian conjugate or transpose in the real case).
 
Thanks, but do you know how to proove it?
 
By the way, do you want to say that it does nod depend on a_i??
 
(i just need the real case)
 
Mechmathian said:
Thanks, but do you know how to proove it?

|Av|^2=v^(T)*A^T*A*v. A^T*A is a symmetric matrix, so it has a complete orthogonal set of eigenvectors. Can you show the eigenvalues are nonnegative? Now expand a general v in terms of those eigenvectors and go from there...
 
Mechmathian said:

Homework Statement



In R^{3} ||x||= a_{1}*|x_{1}|+ a_{2}*|x_{2}|+ a_{3}*|x_{3}|. where a_{i}>0

What is ||A||(indused norm = sup||Ax|| as ||x||=1). (Suppose we know the coeffisients of the matrix/operator A)??


Homework Equations





The Attempt at a Solution


Hey, that's not a matrix operator at all, is it? You just want to maximize the inner product of (a1,a2,a3) and x. That's much easier. Think Cauchy-Schwarz.
 
Unfortunately I do not understand why

|Av|^2=v^(T)*A^T*A*v is true.. Why does it not depend on a_i??
2. I don't think I know how to proove that the eigenvalues are nonnegative or where to go from there..
 
I think that it is a matrix operator..
 
  • #10
Mechmathian said:
I think that it is a matrix operator..

What you wrote is the dot product of (a1,a2,a3) with (x1,x2,x3). That's a matrix operator only in the sense it's a 1x3 matrix. You want to maximize it. Will you look up the Cauchy-Schwarz inequality. Please?
 
  • #11
The thing is that the dot product does not have the modules..
Even if I do maximize it.. I do not see where to go from there..
 
  • #12
Cauchy Shwartz: (x,y)<=||x||*||y||
 
  • #13
Mechmathian said:
Cauchy Shwartz: (x,y)<=||x||*||y||

Yes, and add "with equality holding only when y is a multiple of x". That's the part you want.
 
  • #14
Dick said:
Hey, that's not a matrix operator at all, is it? You just want to maximize the inner product of (a1,a2,a3) and x. That's much easier. Think Cauchy-Schwarz.

Dick said:
What you wrote is the dot product of (a1,a2,a3) with (x1,x2,x3). That's a matrix operator only in the sense it's a 1x3 matrix. You want to maximize it. Will you look up the Cauchy-Schwarz inequality. Please?

Dick, I think you have misinterpreted the question. What he wrote was the definition of norm (not an inner product between (a1, a2, a3) and (x1, x2, x3)- a1, a2, and a3 are fixed for all x) THEN he asked
"What is ||A||(indused norm = sup||Ax|| as ||x||=1). (Suppose we know the coeffisients of the matrix/operator A)??"

In other words, what norm does that defined norm on the vector space induce on the linear operators.

The definition of "induced norm" of A is ||A||= lub ||Ax|| for all x with norm 1.
 

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