Linear algebra - transformations

Click For Summary

Homework Help Overview

The discussion revolves around linear transformations in linear algebra, specifically focusing on the relationship between a linear transformation represented by a matrix and a vector, as well as the properties of vectors that span R^n.

Discussion Character

  • Exploratory, Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • The original poster attempts to determine if a vector w is in the range of a linear transformation L by solving the equation Ax=w. They also question the necessity of orthogonality in vectors that span R^n, seeking clarification on linear independence versus orthogonality.

Discussion Status

Participants are engaging with the original poster's questions, providing insights into the concepts of linear transformations and vector spaces. Some participants affirm that a consistent system indicates that w is in the range, while others clarify that spanning vectors do not need to be orthogonal, emphasizing the distinction between bases and spanning sets.

Contextual Notes

There is a noted confusion from the original poster regarding the definitions and properties of spanning sets and bases in vector spaces, as well as the implications of orthogonality.

Niles
Messages
1,834
Reaction score
0
[SOLVED] Linear algebra - transformations

Homework Statement


I actually have two questions:

1) I have a linear transformation L and it is represented by a matrix A. I also have a vector w, and I want to find out if w gets "hit" by L - see "answer-part" for my approach, and please comment.

2) Does the vectors that span R^n have to be orthogonal and linearly independent or only linearly independent? And is this the same for a vector-space in R^n? Please see comments in "answer-part" as well.

The Attempt at a Solution



1) Can I just solve the system Ax=w? If it is consistent, w gets "hit" by L?

2) The reason why I ask is that e.g. in R^3, the three unit vectors are orthogonal and linearly independent. And I have worked with vector-spaces in R^n where the vectors that span the space are not orthogonal. So I am a little confused here.
 
Last edited:
Physics news on Phys.org
Concerning 1): I don't understand what you mean by 'w gets "hit" be L'.

Concerning 2): Which vectors are you talking about? If S spans R^n, the vectors in S need not be linearly independent. If they are though, then the vectors in S can be used as a basis for R^n.
 
1) Yes, if the system of equations is 'consistent' that means you can find a solution. So w is in the range. It is hit.

2) You've asked this before and I've answered it before. A basis doesn't have to be orthogonal. Are you going to ask again?
 
Thanks to both of you.

I know I asked it before, and it's not nice of me to ask again - but as I wrote, I got a little confused, but I've bookmarked this topic.

Thanks again.
 
Dick said:
1) Yes, if the system of equations is 'consistent' that means you can find a solution. So w is in the range. It is hit.
More correctly, w is in the image of the linear transformation. If L: U->V, the V is the "range" and the image is a subspace of V.
 
Niles said:
2) Does the vectors that span R^n have to be orthogonal and linearly independent or only linearly independent? And is this the same for a vector-space in R^n? Please see comments in "answer-part" as well.

Strictly speaking the vectors that span a vector space don't even have to be independent! A basis for a vector space must both span the space and be linearly independent. A basis still doesn't have to be orthogonal. That's just often used because orthonormal bases are particularly simple. In fact, a general vector space does not necessairily have an "inner product" defined and so the concepts of "orthogonal" and "normalized" may not even be defined.
 

Similar threads

Replies
15
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 8 ·
Replies
8
Views
1K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 30 ·
2
Replies
30
Views
2K
  • · Replies 10 ·
Replies
10
Views
2K
Replies
8
Views
2K
  • · Replies 10 ·
Replies
10
Views
3K
  • · Replies 15 ·
Replies
15
Views
3K