Linear Algebra Change Matrices Confusion

In summary, the conversation discusses how to show that MBD(1Rn) = N, given that N is an invertible n x n matrix and D = {f1, f2, ... , fn} is the standard basis of Rn. The matrix M is defined and used to show the validity of the statement. It is noted that N is invertible if and only if its columns in D span Rn, and this is used to prove that MBD(1Rn) = N.
  • #1
jumbogala
423
4

Homework Statement


Suppose N is an invertible n x n matrix, and let D = {f1, f2, ... , fn} where fi is column i of N for each i. If B is the standard basis of Rn, show that MBD(1Rn) = N.

Call the standard basis of Rn = {E1, ... , En}

Homework Equations


The Attempt at a Solution


The first thing I don't get is whether D is a basis. I thought it had to be a basis to do this kind of question, but the problem doesn't specify! I'm going to assume it is...

Now I'm going to write the matrix M, specifying its entries. For example, f11 is the entry at row 1, column 1. f1 will just denote column 1 of M.
M =
[f11 ... f1n
: :
: :
fn1 ... fnn]

1Rn(f1) = f1, 1Rn(fn) = fn.

f1 can be written as f11E1 + ... + fn1En
fn can be written as fn1E1 + ... + fnnEn

Then MBD(1Rn) is the coefficients of the above, written in column form, so we get exactly the matrix M.

This seems to prove it! But the question specifies that M is invertible, and I didn't use that fact at all. So I think I may have done something wrong. Can anyone help?
 
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  • #2
N is invertible if and only if the columns are a linearly independent set. You didn't use that N is invertible because you just assumed D is a basis.
 
  • #3
Ooh, right - I completely forgot about that. I'm confused about what D is actually a basis FOR. Is it a basis of R^n?

If so I can say that because there are n elements in D, and it's linearly independent, it spans. Therefore it's a basis.

If it's not a basis of R^n, I'm not sure.
 
  • #4
jumbogala said:
Ooh, right - I completely forgot about that. I'm confused about what D is actually a basis FOR. Is it a basis of R^n?

If so I can say that because there are n elements in D, and it's linearly independent, it spans. Therefore it's a basis.

If it's not a basis of R^n, I'm not sure.

Well, sure. If D is invertible its columns have to span R^n. Otherwise it wouldn't be onto, would it?
 
  • #5
What does onto have to do with it? I thought it had to span because A is invertible if and only if AX = B has a solution for every B, not anything to do with transformations...
 
  • #6
jumbogala said:
What does onto have to do with it? I thought it had to span because A is invertible if and only if AX = B has a solution for every B, not anything to do with transformations...

Sorry, I mean N is invertible only if its columns D span R^n. N(E1)=f1. N(E2)=f2. Etc. So N(a1*E1+...+an*En)=a1*f1+...+an*fn. If the f's don't span, then there is a B that's not a combination of the f's. Then Nx=B can't have a solution.
 
  • #7
That makes a lot of sense. I understand now, thank you!
 

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with the study of linear equations, vectors, and matrices. It is used to solve problems involving systems of linear equations and to represent and manipulate data in multiple dimensions.

2. What do you mean by change matrices?

Change matrices refer to the process of transforming a matrix by multiplying it with another matrix. This process allows for the manipulation and rearrangement of data within a matrix, which is useful for solving linear algebra problems.

3. How do change matrices work?

Change matrices work by multiplying a given matrix with a transformation matrix, resulting in a new matrix with altered values. This process can include operations such as scaling, rotating, or reflecting the original matrix.

4. What is the purpose of using change matrices in linear algebra?

The purpose of using change matrices in linear algebra is to simplify and solve complex problems involving systems of linear equations. By transforming matrices, it is possible to manipulate data in a way that makes it easier to analyze and solve problems.

5. Why is there confusion surrounding change matrices in linear algebra?

Change matrices can be confusing for some because they involve multiple mathematical concepts, such as matrix operations and transformations. Additionally, there are different methods and notations for representing change matrices, which can lead to confusion and misunderstandings.

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