Linear Transformations and Image of a Matrix

In summary, the problem asks about the relationship between a 2x2 matrix A and a vector w in its image. The image of a matrix is the span of its column vectors and can be represented by a linear transformation T(x)=Ax. If vector w is in the image of A, then it can also be written as Aw. By substituting [x1 x2] for the second column vector in A, it can be shown that A(Aw)=Aw. This leads to the concept of a projection operator, which may be the intended solution for the problem.
  • #1
Ekaterina
1
0

Homework Statement


Consider a 2x2 matrix A with A2=A.
If vector w is in the image of A, what is the relationship between w and Aw?

Homework Equations


Linear transformation T(x)=Ax
Image of a matrix is the span of its column vectors

The Attempt at a Solution


I know that vector w is one of the column vectors of A, seeing as it is in the image of A.
At first, I tried to work out Aw on paper by substituting [x1 x2] for the second column vector in A, since it isn't specified.
I got the following four equations:
w1 = w1^2+x1w2
w2=w1w2+x2w2
x1=w1x1+x1x2
x2=x1w2+w2^2
However, I couldn't get anything from there.

Now, I'm trying to think of it more conceptually (I believe the point of the problem is to think about it more abstractly), but I'm not sure which direction to head in. All I know is that Ax can equal w, so Aw may also equal w, but the problem doesn't say that w IS the image of A, just that it is IN the image of A.

Any suggestions on how to think about this?
 
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  • #2
Ekaterina said:

Homework Statement


Consider a 2x2 matrix A with A2=A.
If vector w is in the image of A, what is the relationship between w and Aw?

Homework Equations


Linear transformation T(x)=Ax
Image of a matrix is the span of its column vectors

The Attempt at a Solution


I know that vector w is one of the column vectors of A, seeing as it is in the image of A.
At first, I tried to work out Aw on paper by substituting [x1 x2] for the second column vector in A, since it isn't specified.
I got the following four equations:
w1 = w1^2+x1w2
w2=w1w2+x2w2
x1=w1x1+x1x2
x2=x1w2+w2^2
However, I couldn't get anything from there.

Now, I'm trying to think of it more conceptually (I believe the point of the problem is to think about it more abstractly), but I'm not sure which direction to head in. All I know is that Ax can equal w, so Aw may also equal w, but the problem doesn't say that w IS the image of A, just that it is IN the image of A.

Any suggestions on how to think about this?

Asking "what is the relationship" is a pretty ambiguous question. I'd think about it more conceptually this way: A(Aw)=A^2(w)=Aw. What is A(Aw-w)? What do those tell you conceptually? Here's a hint about what they might be fishing for, look up projection operator. That's my best guess.
 

Related to Linear Transformations and Image of a Matrix

1. What is a linear transformation?

A linear transformation is a mathematical operation that maps one vector space to another in a way that preserves the linear structure of the original space. This means that the operations of addition and scalar multiplication are maintained after the transformation.

2. How is a linear transformation represented mathematically?

A linear transformation can be represented using a matrix. The matrix contains the coefficients that are used to transform the input vector into the output vector. The matrix is multiplied by the input vector, resulting in the transformed output vector.

3. What is the image of a matrix?

The image of a matrix is the set of all possible output vectors that can be obtained by applying the linear transformation represented by the matrix. It is the span of the column vectors of the matrix, also known as the column space.

4. How can I determine if a matrix is a linear transformation?

A matrix is a linear transformation if and only if it satisfies two conditions: the sum of two input vectors is equal to the transformation of the sum of the input vectors, and the scalar multiple of an input vector is equal to the transformation of the scalar multiple of the input vector. These conditions are known as the additivity and homogeneity properties.

5. Can a linear transformation be represented by a non-square matrix?

Yes, a linear transformation can be represented by a non-square matrix. The number of columns in the matrix corresponds to the dimension of the input vector space, and the number of rows corresponds to the dimension of the output vector space. This means that the transformation can map a vector from a higher or lower dimensional space to another space.

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