Linear algebra proof (matrices and linear transformations)

Click For Summary
SUMMARY

The discussion centers on the relationship between linear transformations and their corresponding matrices in the context of linear algebra. Specifically, it addresses the transformation T from vector space V to vector space W, defined by the matrix A, where T(v_i) is expressed as a linear combination of basis vectors w_j. The key conclusion is that the action of T on a vector x in V can be represented through matrix multiplication Ax, confirming the correspondence between linear transformations and matrices. The participants highlight challenges in transitioning from the basis vectors of V to those of W during calculations.

PREREQUISITES
  • Understanding of linear transformations and their properties
  • Familiarity with matrix representation of linear transformations
  • Knowledge of vector spaces and basis vectors
  • Proficiency in matrix multiplication and summation notation
NEXT STEPS
  • Study the concept of isomorphism in vector spaces
  • Learn about the properties of linear transformations in linear algebra
  • Explore matrix representation techniques for linear transformations
  • Investigate the relationship between different bases in vector spaces
USEFUL FOR

Students of linear algebra, educators teaching linear transformations, and anyone seeking to deepen their understanding of matrix representations in vector spaces.

Ryker
Messages
1,080
Reaction score
2

Homework Statement


Let T \in L(V, W), where dim(V) = m and dim(W) = n. Let {v1, ..., vm} be a basis of V and {w1, ..., wn} a basis for W. Define the matrix A of T with respect to the pair of bases {vi} and {wj} to be the n-by-m matrix A = (aij), where

T(v_{i}) = \displaystyle\sum_{j=1}^{n}a_{ji}w_{j}, 1 \le i \le m, 1 \le j \le n.

The vector spaces V and W are isomorphic via the bases {vi} and {wj} to the spaces Fm and Fn, respectively. Show that ifx \in Fm is the column vector corresponding to the vector x \in V via the isomorphism, then Ax is the column vector in Fn corresponding to T(x). In other words, the correspondence between linear transformations and matrices is such that the action of T on a vectorx is realized by the matrix multiplication Ax.

Homework Equations


The Attempt at a Solution


I can see this is true, and when we learned this in class, it was pretty clear to me. But now I'm going through some linear algebra book and the stuff is introduced in a different way that confuses the hell out of me.

What I've tried to do here is just show what T(x) and Ax get you, and that they are equal. But I just can't get to that, it seems.

For T(x), I get the following:

T(x) = T(\displaystyle\sum_{i=1}^{m}b_{i}v_{i}) = \displaystyle\sum_{i=1}^{m}b_{i} \displaystyle\sum_{j=1}^{n}a_{ji}w_{i},

and for Ax:Ax = \displaystyle\sum_{j=1}^{n} (\displaystyle\sum_{i=1}^{m}a_{ji}x_{i}) = \displaystyle\sum_{j=1}^{n} (\displaystyle\sum_{i=1}^{m}a_{ji}b_{i}v_{i}).

I don't know how to make the jump from vi to wj. Or have I gone completely in the wrong direction? Any help would be greatly appreciated.
 
Last edited:
Physics news on Phys.org
I believe there is a problem with matrix multiplication in your solution. The first warning: how did you get v_i's into the result? It clearly shouldn't have happened, since the dimensions don't match. I'd say
Ax=\sum_{j=1}^n\left(\sum_{i=1}^m a_{ji}b_i w_j\right)
because that transformed coordinates are for this other basis, not V's basis.
Good luck!
 
Hmm, I got vi in my result, because I figured if x ϵ V, then xi = b1v1 + b2v2 + ... + bmvm. So that's where I get stuck, I don't know how to get to having it expressed in terms of wj, because A is defined in terms of aij and x as a linear combination of the basis vectors {vi}.

How did you get to that solution you offered? If I got to that, then clearly I'd be good to go, since it would match T(x), but I just can't get to that.
 
Last edited:

Similar threads

  • · Replies 13 ·
Replies
13
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
1K
  • · Replies 5 ·
Replies
5
Views
3K
Replies
15
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 1 ·
Replies
1
Views
3K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 7 ·
Replies
7
Views
2K