Linear Transformation problem. .

In summary, the problem asks to determine all linear transformations T from a vector space V to itself such that T is equal to its own square. By using a hint given, it can be shown that V can be represented as the direct sum of the kernel and image of T. The opposite question is then posed, whether given the direct sum of two subspaces, a T can be found to match them.
  • #1
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Homework Statement


Let [tex]\mathrm{V}[/tex] be a vector space. Determine all linear transformations [tex]\mathrm{T}:V\rightarrow V[/tex] such that [tex]\mathrm{T}=\mathrm{T}^2[/tex].


Homework Equations


Hint was given and it was like this:
Note that [tex]x=\mathrm{T}(x)+(x-\mathrm{T}(x))[/tex] for every [tex]x[/tex] in [tex]V[/tex], and show that [tex]V=\{y:\mathrm{T}(y)=y\}\oplus\mathrm{N}(T)[/tex]



The Attempt at a Solution


I tried to calculate [tex]T(x)[/tex] and [tex]T^2(x)[/tex] using [tex]x=T(x)+(x-T(x))[/tex] and put [tex]T[/tex] and [tex]T^2[/tex] equal. But, I do not think this is how to solve this problem... =(
 
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  • #2
Each x can be written as x = T(x) + (x-T(x)) so note that:

T(T(x)) = T(x) so T(x) is in the set {y:T(y)=y}

And T(x-T(x)) = T(x) - T2(x) = T(x) - T(x) = 0 so x-T(x) is in N(T).

So given a T, we can represent V as the direct sum of the kernel of T and the image of T. The opposite question is, given V as the direct sum of two subspaces, can we find a T such that one is the kernel and the other is the image?
 

FAQ: Linear Transformation problem. .

What is a linear transformation problem?

A linear transformation problem is a mathematical concept that involves transforming a set of data or variables using a linear function. This function maps the original data to a new set of data in a linear manner.

What are some real-world applications of linear transformation problems?

Linear transformation problems have many applications in fields such as physics, engineering, economics, and data analysis. For example, they can be used to model the growth of a population, predict the trajectory of a projectile, or analyze the relationship between different variables in a dataset.

How do you solve a linear transformation problem?

To solve a linear transformation problem, you need to first identify the input and output variables, as well as the linear function that relates them. Then, you can use various mathematical techniques such as matrix operations and vector calculations to transform the data and find the solution.

Can a non-linear function be used for a linear transformation problem?

No, a non-linear function cannot be used for a linear transformation problem. The key characteristic of a linear transformation is that the relationship between the input and output variables is linear, meaning that it can be represented by a straight line. Non-linear functions do not have this property and therefore cannot be used for linear transformation problems.

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

While both linear transformations and linear regressions involve linear functions, they are used for different purposes. A linear transformation is used to transform data or variables, while a linear regression is used to model the relationship between two or more variables and make predictions based on that relationship. Linear transformations are often used as a step in the process of linear regression.

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