Question Regarding Linear Transformation

In summary, the conversation is about finding matrices A, B, and C that represent the transformations T1 and T2 and their products and sums. The basis vectors e1 and e2 are used in the problem, and they are assumed to be the standard basis vectors (1,0) and (0,1). The matrix representing the sum of T1 and T2 is simply the sum of their individual matrices, while the matrices representing their products can be calculated by multiplying their individual matrices in the given orders.
  • #1
scienceguy288
14
0
I can't figure out how to take the first bite out of this one.

Homework Statement



Let T1: R^2 --> R^2 and T2: R^2 --> R^2 have the indicated properties. Find matrices A, B, and C such that:

T2T1x=Ax, T1T2x=Bx, (T1+T2)x=Cx

Homework Equations



T1e1=(1,3), T1e2=(2,2), T2e1=(-1,1), T2e2=(2,-1)

The Attempt at a Solution



I start by saying that T1e1+T2e1=(T1+T2)e1=(0,4)=Ce1 by adding the two matrices.

Using the same logic, I claim that T2e2+T1e2=(2,2)=(5,1)=Ce2

However, I can't go any further with that because I don't know e1 and e2, don't know T1, T2 (so I can't do the inverse of the transformation). Thus, I cannot find A, B, or C, that is, the sum and products of T1 and T2.

Thanks.
 
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  • #2
are e1 & e2 the standard basis vectors (1,0) & (0,1)?
 
  • #3
it doesn't really matter if the ej are the standard basis or not. they are obviously "some" basis, and we can only give a matrix relative to two bases (the domain basis and the co-domain basis), so we may as well choose {e1,e2} as the domain basis.
 
  • #4
lanedance said:
are e1 & e2 the standard basis vectors (1,0) & (0,1)?

I don't know. Are e1 and e2 standard symbols for the standard basis vectors? Otherwise I think they are just referring to the general vectors {e1, e2}, rather than any specific vector. Perhaps I have to find those vectors first?

Deveno said:
it doesn't really matter if the ej are the standard basis or not. they are obviously "some" basis, and we can only give a matrix relative to two bases (the domain basis and the co-domain basis), so we may as well choose {e1,e2} as the domain basis.

That is how I have been approaching the problem thusfar, but as stated in the original problem post, cannot get any further.
 
  • #5
lanedance said:
are e1 & e2 the standard basis vectors (1,0) & (0,1)?

It turns out that this is in fact the case. Still stuck, though...
 
  • #6
scienceguy288 said:
It turns out that this is in fact the case. Still stuck, though...

Nevermind...I got C.

Still running into some trouble finding A and B, but will continue to work on it. If someone can give me a shove in the right direction, that would make my life that much easier...
 
  • #7
If you have matrices representing [itex]T_1[/itex] and [itex]T_2[/itex] in the given basis (which are trivial to get), then, as you say, the matrix representing [itex]T_1+ T_2[/itex] is just the sum of those two matrices. And, of course, the matrices representing [itex]T_1T_2[/itex] and [itex]T_2T_1[/itex] are just the products of those two matrices in the given orders.
 
  • #8
I have solved the problem. Thanks for the help.
 

FAQ: Question Regarding Linear Transformation

What is a linear transformation?

A linear transformation is a mathematical function that maps a vector or set of vectors from one vector space to another, while preserving the basic structure of the original vector. It involves multiplying the vector by a matrix and adding a constant vector.

What are the properties of a linear transformation?

A linear transformation has two main properties: additivity and homogeneity. Additivity means that the transformation of a sum of vectors is equal to the sum of the individual transformations. Homogeneity means that the transformation of a scalar multiple of a vector is equal to the scalar multiple of the transformation of the vector.

How is a linear transformation represented?

A linear transformation is typically represented by a matrix. The transformation of a vector can be calculated by multiplying the vector by the transformation matrix. The resulting vector will have the same dimensions as the original vector.

What are some real-life applications of linear transformations?

Linear transformations have many applications in science and engineering, such as in computer graphics, physics, economics, and statistics. They are used to model and analyze various systems, such as electrical circuits, chemical reactions, and population dynamics.

What is the difference between a linear transformation and a nonlinear transformation?

A linear transformation follows the rules of additivity and homogeneity, while a nonlinear transformation does not. This means that the transformation of a sum of vectors may not be equal to the sum of the individual transformations, and the transformation of a scalar multiple of a vector may not be equal to the scalar multiple of the transformation of the vector. Nonlinear transformations are more complex and have a wider range of applications, but linear transformations are often easier to understand and work with.

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