Linear Transformation Question: Solving for Im(T) in R^4 Dimension Space

In summary, the conversation discusses a linear transformation question in linear algebra, specifically finding the specific linear transformation for a given 4x4 matrix. The theorem of dimensions is mentioned, stating that the dimension of the vector space is equal to the sum of the dimension of the kernel and the dimension of the image. It is noted that the dimension of the kernel is 2 and the dimension of the vector space is 4, leading to the conclusion that the dimension of the image must be 2. The conversation ends with a request for help in solving the problem and a suggestion to use a projection matrix.
  • #1
stud
3
0
I need help with question from homework in linear algebra.

This question (linear transformation):
http://i43.tinypic.com/15reiic.gif

According to theorem dimensions:
dim(V) = dim(Ker(T)) + dim(Im(T)).

dim(Ker(T))=2.
dim(V) in R^4, meaning =4.

We can therefore conclude that dim(Im(T))=2.
But how can find this specific linear transformation?

Please help me to solve this problem.
Thanks.
 
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  • #2
So let's write the transform as a 4x4 matrix A, giving 16 unknowns.

Now you you know Ax=0 for, x in the kernal. This gives you 8 equations, and is equivalent to mappint the plane contain the 2 kernal vectors to zero.

Clearly you still have more unknowns, so you will need to make some assumptions.

One of the simpler ones, might be to try and find the "projection matrix" which maps components in the kernal plane to zero, but leaves components perpindicular to that plane unchanged
 

Related to Linear Transformation Question: Solving for Im(T) in R^4 Dimension Space

1. What is a linear transformation?

A linear transformation is a mathematical function that maps a set of input values to a set of output values in a linear manner. This means that the output values are proportional to the input values, and the function follows the properties of linearity, such as preserving addition and scalar multiplication.

2. What are the properties of a linear transformation?

The properties of a linear transformation include:

  • Preservation of addition: f(x+y) = f(x) + f(y)
  • Preservation of scalar multiplication: f(kx) = kf(x)
  • Preservation of zero: f(0) = 0

3. How is a linear transformation represented?

A linear transformation can be represented using a matrix, which is a rectangular array of numbers. Each column of the matrix represents the output values for a specific input value, and the rows represent the different input values. The matrix can be multiplied with a vector of input values to obtain the corresponding output vector.

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

The main difference between a linear and nonlinear transformation is that a linear transformation follows the properties of linearity, while a nonlinear transformation does not. This means that a nonlinear transformation does not preserve addition, scalar multiplication, or zero. Nonlinear transformations can also result in curved or non-straight lines, while linear transformations always result in straight lines or planes.

5. What are real-world applications of linear transformation?

Linear transformations have numerous applications in various fields, including:

  • Image and signal processing, such as image scaling and compression
  • Economics, to model supply and demand relationships
  • Geometry, to transform shapes and objects
  • Physics, to describe the motion of objects in a straight line
  • Machine learning, for linear regression and classification algorithms

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