Linear Transformation S: Matrix A, Injective/Surjective

In summary, the linear transformation S is defined by the formula S(x) = b1a1T + b2a2T + b3a3T, where x is an element of R3. The standard matrix A for this transformation can be found by observing its effect on the identity columns. The matrix is not provided, but it should be easy to find using the given vectors a1,a2,a3 and b1,b2,b3. It is not specified in the conversation whether the linear transformation is injective or surjective.
  • #1
orange12
5
0
Let the vectors a1,a2,a3 €R3 and b1,b2,b3 € R4 be given by

a1 a2 a3
1 -2 3
2 2 1
1 1 2

b1 b2 b3
1 1 -1
2 -3 2
1 4 3
3 -2 1

The linear transformation S : R3 --> R4 is defined by

S(x)= b1a1Tx+b2a2Tx+b3a3Tx x€R3

1. Find the standard matrix A for the linear transformation S og decide if the linear transformation S er injective or surjective.
 
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  • #2
I smell homework. Tell us what you've tried.
 
  • #3
What is "b1a1T" and the others? That should be easy to find.
 
  • #4
HallsofIvy said:
What is "b1a1T" and the others? That should be easy to find.

I have tried to put the a1,a2 etc and b1,b2 etc into the formula for S(x).

First i put out x so it became

S(x)=(b1a1T+b2a2T+b3a3T)x, and then i get a Matrix, but i am not sure that it is the standard matrix. I read in my book that u have to see what it does to the Idendity colums, but can't figure out how to do that. I have tried out some things, but it would help a lot if you could show me which way is the right way to do it.
 

1. What is a linear transformation?

A linear transformation is a function that maps one vector space to another in a way that preserves vector addition and scalar multiplication. In other words, the output of a linear transformation is always a linear combination of its input.

2. What is a matrix A in a linear transformation?

In a linear transformation, a matrix A represents the coefficients of the input vectors in the output vector. Each column of the matrix represents the coefficients for a different input vector, and each row represents the coefficients for a different output vector.

3. What does it mean for a linear transformation to be injective?

A linear transformation is injective if each input vector corresponds to a unique output vector. In other words, no two input vectors are mapped to the same output vector. This is also known as a one-to-one mapping.

4. What does it mean for a linear transformation to be surjective?

A linear transformation is surjective if every output vector in the target vector space is mapped to by at least one input vector. In other words, the range of the transformation is equal to the entire target vector space. This is also known as an onto mapping.

5. Can a linear transformation be both injective and surjective?

Yes, a linear transformation can be both injective and surjective. This is known as a bijective mapping, and it means that each input vector corresponds to a unique output vector, and every output vector is mapped to by at least one input vector.

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