Invertible linear transformation

In summary, the conversation is about proving that a linear transformation T on R^n is invertible if ||T-I|| < 1, using the fact that a matrix is singular if and only if it is not invertible. The conversation also discusses the properties of spectral radius and geometric series, and how it relates to the convergence of a matrix series. The final goal is to show that the series \sum_{n=0}^{\infty}(I-T)^n converges absolutely to T^-1.
  • #1
CarmineCortez
33
0

Homework Statement


If T is a linear transformation on R^n with || T-I || < 1, prove that T is invertible.



The Attempt at a Solution



So a linear transformation T is invertible iff the matrix T is not singular.
and I know for any matrix A, ||A|| > spectral radius(A).

so, spectral radius(T-I) < 1.
 
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  • #2
What would happen to T-I, if 0 was an eigenvalue of T? Is it compatible with the hypothesis?
 
  • #3
if 0 was an eigenvalue of T then T would be singular..
 
  • #4
CarmineCortez said:
if 0 was an eigenvalue of T then T would be singular..

Ok, so if T is not invertible then Tv=0 for some v. So v corresponds to what eigenvalue of T-I?
 
  • #5
Dick said:
Ok, so if T is not invertible then Tv=0 for some v. So v corresponds to what eigenvalue of T-I?

0 = λ*v + I*v
=> -1 = λ

but I know my spectral radius is <1 so contradiction...
 
  • #6
Yes. That's it. You could also say (T+I)v=(-v) means ||T+I||>=1 and not even say anything about spectral radius. Still a contradiction with ||T+I||<1.
 
  • #7
I need to show: sum from k=0 to infinity of (I-T)^k converges absolutely to T^(-1)

so if ||T-I|| <1 then is ||I-T|| < 1? and all the properties I listed carry over? I'm still not too sure where to go with this.

when the spectral radius is <1, the higher powers of the matrix tend to 0, so it clearly converges...
 
  • #8
For any norm [tex]\left\|v\right\|=\left\|-v\right\|[/tex]. Regarding the limit, remember the form of the geometric series.
 
  • #9
In fact, it's easier if you consider a matrix [tex]S[/tex], with [tex]\left\|S\right\|<1[/tex] and prove that:

[tex]\sum_{n=0}^{\infty}S^n[/tex]

Converges absolutely and compute the limit.
 
  • #10
JSuarez said:
In fact, it's easier if you consider a matrix [tex]S[/tex], with [tex]\left\|S\right\|<1[/tex] and prove that:

[tex]\sum_{n=0}^{\infty}S^n[/tex]

Converges absolutely and compute the limit.

There is a thm that says if spectral norm <1 then A^n -> 0 as n-> infinity.

and I proved above that spectral norm is <1

so I'm lost again...
 
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  • #11
What can you say about the real series:
[tex]
\sum_{n=0}^{\infty}\left\|S\right\|^n
[/tex]
When [tex]\left\|S\right\|<1[/tex]? Does it converge? if yes, what's the sum? Is it related to ypur original series if S = I-T?
 

FAQ: Invertible linear transformation

What is an invertible linear transformation?

An invertible linear transformation is a mathematical function that maps one vector space to another, where each input vector has a unique output vector. This means that the transformation can be undone by applying its inverse, resulting in the original input. In other words, the transformation preserves the information of the input vector.

How do you know if a linear transformation is invertible?

A linear transformation is invertible if its determinant is non-zero. This means that the transformation is not changing the scale or orientation of the vector space, and can be undone by applying its inverse. Additionally, a linear transformation is invertible if it is one-to-one and onto, meaning that each input vector has a unique output vector and no output vector is left out.

What is the importance of invertible linear transformations?

Invertible linear transformations are important in many areas of mathematics and science, such as in solving systems of linear equations and in understanding the behavior of matrices. They also have practical applications in fields like computer graphics and data compression.

Can a non-square matrix have an inverse?

No, a non-square matrix cannot have an inverse. In order for a matrix to be invertible, it must have the same number of rows and columns, meaning it must be a square matrix. Non-square matrices do not have an inverse because the transformation cannot be undone due to the difference in dimensions.

How do you find the inverse of a linear transformation?

The inverse of a linear transformation can be found by using the inverse matrix method, where the inverse of the transformation matrix is calculated using a series of steps and rules. Alternatively, for 2D and 3D transformations, the inverse can be found by using geometric methods such as reflection and rotation.

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