Linear Transformations and Matrices

In summary, the conversation discusses the difficulty in understanding how to perform linear transformations on matrices. The example from the book shows how to find the result of T\left(\left[\begin{array}{cc}3\\3\end{array}\right]\right) using the definition of a linear transformation. The solution is found by multiplying the vector by the given transformation matrix. The conversation also mentions that this solution follows from the definition of a linear transformation, which states that the transformation of a linear combination of vectors is equal to the same linear combination of the transformed vectors.
  • #1
RadiationX
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I'm having some difficulty understanding how to perform linear transformations on matrices. I understand the definition but not how to perform the operations. I'm going to give a few examples from my book:

Suppose that [tex] T: R^2 \longrightarrow R^2[/tex] is a linear transformation such that.

[tex]T\left(\left[\begin{array}{cc}1\\1\end{array}\right]\right)=\left( \left[\begin{array}{cc}2\\3\end{array}\right]\right)[/tex]

And

[tex]T\left(\left[\begin{array}{cc}1\\-1\end{array}\right]\right)= \left(\left[\begin{array}{cc}4\\-1\end{array}\right]\right)[/tex]


(a) Find: [tex] T\left(\left[\begin{array}{cc}3\\3\end{array}\right]\right)[/tex]


Solution:


since:
[tex]\left(\left[\begin{array}{cc}3\\3\end{array}\right]\right) = 3\left(\left[\begin{array}{cc}1\\1\end{array}\right]\right)[/tex]

it follows that

[tex]T\left(\left[\begin{array}{cc}3\\3\end{array}\right]\right) = T3\left(\left[\begin{array}{cc}1\\1\end{array}\right]\right) = 3T\left(\left[\begin{array}{cc}1\\1\end{array}\right]\right) = 3\left(\left[\begin{array}{cc}2\\3\end{array}\right]\right) = \left(\left[\begin{array}{cc}6\\9\end{array}\right]\right)[/tex]


How do they come to this solution?
 
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  • #2
it follows from the definition of a linear transformation:

If T is a linear transformation, then
[tex]T(av_1 +bv_2) = aT(v_1)+bT(v_2)[/tex]

a and b are constants and [itex]v_1[/itex] and [itex]v_2[/itex] are vectors.
 

1. What is a linear transformation?

A linear transformation is a mathematical function that maps one vector space to another in such a way that the properties of linearity are preserved. This means that the transformation preserves parallel lines and the origin, and also maintains the scale and proportion of vectors.

2. What are matrices used for in linear transformations?

Matrices are used to represent linear transformations. They are a concise way of expressing a transformation and allow for efficient computation of transformations on vectors. Matrices can also be used to perform operations such as composition and inversion of transformations.

3. How do you determine the type of transformation represented by a matrix?

The type of transformation represented by a matrix can be determined by looking at the properties of the matrix. A matrix that preserves the length and angle between vectors is an orthogonal transformation, while a matrix that preserves only the length of vectors is a dilation or scaling transformation. A matrix that can be written as a product of rotation, scaling, and shearing matrices is a composite transformation.

4. Can a linear transformation be represented by multiple matrices?

Yes, a linear transformation can be represented by multiple matrices. This is because there are infinitely many ways to represent a given transformation using matrices. However, all of these matrices will have the same properties and will result in the same transformation when applied to a vector.

5. How are linear transformations and matrices used in real-world applications?

Linear transformations and matrices are used in a variety of real-world applications, including computer graphics, image processing, and data analysis. They are also used in fields such as engineering, physics, and economics to model and solve complex problems involving linear relationships.

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