Finding the Image of a Vector under a Linear Transformation

In summary, the conversation discusses a linear transformation L: R^3 -> R^3 and its corresponding matrix representation. The problem involves finding L([2 -1 3]) and there is confusion about whether the answer should be a single number or a vector. The solution involves understanding how the transformation acts on the basis {i, j, k} and using the matrix representation to calculate the answer.
  • #1
superdave
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3

Homework Statement



Let L: R^3 -> R^3 be a linear transformation such that

L(i) = [1 2 -1], L(j) = [1 0 2] and L(k) = [1 1 3].

Find L([ 2 -1 3)].

All the numbers in [ ] should be vertical, but I don't know how to set that up.

Homework Equations





The Attempt at a Solution



I'm not sure how to even approach this. I've tried looking at examples in the text and they aren't clear.

I would think that you make a matrix L with the three columns i j k as above. and x = [2 -1 3] and just calculate Lx=b to find b.

But a similar problem in the text has a single number answer. I would've guessed that it gives a vector.
 
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  • #2
You know how the transformation acts on the basis {i, j, k}. Let v be any vector, then v = αi + βj + γk. Then L(v) = αL(i) + βL(j) + γL(k).

The vectors L(i), L(j) and L(k) are the columns of the matrix representation of the operator L.
 
  • #3
superdave said:
But a similar problem in the text has a single number answer. I would've guessed that it gives a vector.

You should get a vector here. Maybe you should post the similar problem and we can help you figure out what the difference is?
 

FAQ: Finding the Image of a Vector under a Linear Transformation

What is a linear transformation matrix?

A linear transformation matrix is a mathematical representation of a linear transformation, which is a function that maps one vector space to another in a way that preserves linearity. It is a square matrix with the same number of rows and columns, and it can be used to perform operations such as scaling, rotating, shearing, and reflecting on vectors.

How is a linear transformation matrix calculated?

A linear transformation matrix is calculated by representing the linear transformation as a system of equations, and then solving for the coefficients of the variables in each equation. These coefficients are then arranged in a matrix to form the linear transformation matrix.

What are the properties of a linear transformation matrix?

A linear transformation matrix has several properties, including:

  • It is a square matrix with the same number of rows and columns.
  • The determinant of the matrix is not equal to 0.
  • The columns of the matrix are linearly independent.
  • It can be used to perform operations such as scaling, rotating, shearing, and reflecting on vectors.

How is a linear transformation matrix applied to a vector?

To apply a linear transformation matrix to a vector, the vector is represented as a column matrix, and then the matrix multiplication operation is performed between the linear transformation matrix and the vector matrix. The resulting matrix is the transformed vector.

What is the importance of linear transformation matrices in science?

Linear transformation matrices are important in science because they allow for the efficient representation and manipulation of data and equations. They are used in fields such as physics, engineering, computer graphics, and data analysis to model and solve problems involving linear transformations and transformations of data. They also have applications in machine learning and artificial intelligence algorithms.

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