Proof of composite linear transformations

In summary, a composite linear transformation is a combination of two or more linear transformations, where the output of the first transformation becomes the input of the second transformation, resulting in a new transformation that can be represented as a single matrix or function. This is different from a single linear transformation, which only involves applying one transformation to a vector. To determine the matrix representation of a composite linear transformation, the individual matrices for each transformation must be determined and then multiplied in the order they are applied. The order of transformations is significant as it affects the final result and changing it can result in a different transformation and matrix representation. Composite linear transformations are used in various fields, including computer graphics, robotics, and economics, to efficiently and accurately perform complex transformations in applications
  • #1
Flyboy27
6
0
Prove that if [tex]T:R^{m} \rightarrow R^{n}[/tex] and [tex]U:R^{n} \rightarrow R^{p}[/tex] are linear transformations that are both onto, then [tex]UT:R^{n} \rightarrow R^{p}[/tex] is also onto.

Can anyone point me in the right direction? Is there a theorem that I can pull out of the def'n of onto that I can begin this proof?
 
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  • #2
this is trivial, direct from definition of onto.
 
  • #3


To prove that UT is onto, we need to show that for every vector y in R^p, there exists a vector x in R^m such that UT(x) = y.

Since U is onto, for every vector y in R^p, there exists a vector z in R^n such that U(z) = y.

And since T is onto, for every vector z in R^n, there exists a vector x in R^m such that T(x) = z.

Therefore, for every vector y in R^p, there exists a vector x in R^m such that UT(x) = U(T(x)) = U(z) = y.

Hence, UT is onto, and the proof is complete.

This proof uses the definition of onto, which states that a linear transformation is onto if every element in the codomain (R^p in this case) has at least one preimage in the domain (R^m in this case). By using the onto property of both T and U, we can show that UT also satisfies this property and is therefore onto.
 

Related to Proof of composite linear transformations

1. What is a composite linear transformation?

A composite linear transformation is a combination of two or more linear transformations, where the output of the first transformation becomes the input of the second transformation, and so on. This results in a new transformation that can be represented as a single matrix or function.

2. How is a composite linear transformation different from a single linear transformation?

A single linear transformation involves applying one transformation to a vector, while a composite linear transformation involves applying multiple transformations in a specific order. This allows for more complex transformations to be performed.

3. How do you determine the matrix representation of a composite linear transformation?

To determine the matrix representation of a composite linear transformation, you must first determine the individual matrices for each transformation. Then, you can multiply these matrices in the order they are applied to get the final matrix representation of the composite transformation.

4. What is the significance of the order in which transformations are applied in a composite linear transformation?

The order in which transformations are applied in a composite linear transformation is significant because it affects the final result. Changing the order of transformations can result in a different transformation and matrix representation.

5. How is a composite linear transformation used in real-world applications?

Composite linear transformations are used in many fields, such as computer graphics, robotics, and economics. They allow for complex transformations to be performed efficiently and accurately, making them useful in various applications, such as image processing, motion planning, and financial modeling.

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