Linear Algebra Problem: Finding the Matrix A for a 3-Dimensional Subspace

In summary, the conversation discusses how to represent a subspace W in a 3-dimensional vector space V with a chosen basis α = {e1,e2,e3} as span([u]α, [v]α, [w]α) and then write it as a solution space {X : AX = 0} for some matrix A. The vectors u, v, and w are given and it is shown that w can be represented as span([1 -1 1],[1 0 1],[1 1 1]). The conversation also discusses how to proceed with finding the matrix A by determining the number of parameters needed for the solution space of a hypothetical system of equations and finding the correct RREF of
  • #1
c00ter
1
0
1. The question is asking:

Let V be a 3-dimensional vector space with a chosen basis α = {e1,e2,e3}. Consider the subspace W = span(u,v,w). Represent W as span(α, [v]α, [w]α), and then write
W as a solution space {X : AX = 0} for some matrix A.

2. u = e1e2 + e3
v = e1 + e3
and w = e1 + e2 + e3




3. so i got w= span([1 -1 1],[1 0 1],[1 1 1])
and through row reduction I found that the vectors in the span are not linearly independent so removing one will make it linearly independent. I removed the last one so we have
w= span([1 -1 1],[1 0 1]) which is linearly indep.

From here I am not sure how to proceed. I was told that at this point I need to "find the number of parameters needed for the solution space (i.e. W) of a hypothetical system of equations" which will give me the number of equations( I am unsure of how the #of free parameters relates to the number of equations). And I think since the space is 3-dimensional this implies I will have 3 unknowns. Knowing # of equations = # of rows and #of unknowns = # of columns for the matrix A. Then find the possible RREF's of such a matrix and see which one has the correct # of free parameters and equations then use this to find the matrix A.

Any help would be greatly appreciated.
 
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  • #2
c00ter said:
1. The question is asking:

Let V be a 3-dimensional vector space with a chosen basis α = {e1,e2,e3}. Consider the subspace W = span(u,v,w). Represent W as span(α, [v]α, [w]α), and then write
W as a solution space {X : AX = 0} for some matrix A.

2. u = e1e2 + e3
v = e1 + e3
and w = e1 + e2 + e3




3. so i got w= span([1 -1 1],[1 0 1],[1 1 1])

You're saying [1 1 1] = span([1 -1 1],[1 0 1],[1 1 1]). w and W aren't the same thing.

and through row reduction I found that the vectors in the span are not linearly independent so removing one will make it linearly independent. I removed the last one so we have
w= span([1 -1 1],[1 0 1]) which is linearly indep.

From here I am not sure how to proceed. I was told that at this point I need to "find the number of parameters needed for the solution space (i.e. W) of a hypothetical system of equations" which will give me the number of equations( I am unsure of how the #of free parameters relates to the number of equations). And I think since the space is 3-dimensional this implies I will have 3 unknowns. Knowing # of equations = # of rows and #of unknowns = # of columns for the matrix A. Then find the possible RREF's of such a matrix and see which one has the correct # of free parameters and equations then use this to find the matrix A.

Any help would be greatly appreciated.
When you say a vector ##\vec{x}## is in W, what exactly does that mean?
 

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with linear equations, vectors, matrices, and their properties. It is used to solve problems in various fields such as engineering, physics, economics, and computer science.

2. What are the applications of linear algebra?

Linear algebra has many applications in real-world problems. Some common applications include data analysis, image processing, machine learning, and optimization. It is also used in physics and engineering to model and solve systems of linear equations.

3. What are the basic concepts in linear algebra?

The basic concepts in linear algebra include vectors, matrices, systems of linear equations, determinants, and eigenvalues and eigenvectors. These concepts are used to represent and solve various problems in the field.

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To solve a linear algebra problem, you need to understand the basic concepts and techniques such as Gaussian elimination, matrix operations, and vector spaces. It is important to carefully read and understand the problem, and then use the appropriate methods to find the solution.

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