Transition Matrices: Solving X[T]X & T(v_1)=v_2

In summary, the conversation is about understanding a page that was attached, specifically part (ii) which involves computing X[T]X and determining the linear transformation given certain properties. The confusion is around the equations T(v_1) = v_2 and T(v_2) = av_1 + bv_2, which seem to be just an example rather than derived from somewhere. The conversation ends with the clarification that it is indeed just an example.
  • #1
Artusartos
247
0
I am a bit confused about the page that I attached...

I don't understand part (ii)...

How can you compute X[T]X? So why is [tex]T(v_1)=v_2[/tex] and [tex]T(v_2)=av_1 + bv_2[/tex]?

Thanks in advance...
 

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  • #2
Hey Artusartos.

Are you just trying to find the linear transformation given those properties of how v1 and v2 maps to v1' and v2'?
 
  • #3
chiro said:
Hey Artusartos.

Are you just trying to find the linear transformation given those properties of how v1 and v2 maps to v1' and v2'?


Hi,


I'm not trying to find anything. I was just trying to undestand the page that I attached (Part ii)...I don't understand why they wrote [tex]T(v_1) = v_2 [/tex] and [tex]T(v_2) = av_1 + bv_2[/tex]
 
  • #4
I think (but am not certain) that this is just an example transformation.
 
  • #5
chiro said:
I think (but am not certain) that this is just an example transformation.

Oh...so are they just making that up to give an example? I thought they were deriving those equations from somewhere, and that's why I was confused...
 
  • #6
I'm pretty sure it is just an example.
 
  • #7
chiro said:
I'm pretty sure it is just an example.

Ok thanks :)
 

1. What is a transition matrix?

A transition matrix is a square matrix that represents a linear transformation from one vector space to another. It is used to describe how one set of coordinates or basis vectors can be transformed into another set of coordinates or basis vectors.

2. How do you solve for X[T]X?

To solve for X[T]X, you can use the properties of matrix multiplication and transpose. First, multiply the transpose of X with X to get a square matrix. Then, you can use methods like Gaussian elimination or matrix inversion to solve for the values of X.

3. What is the significance of T(v_1)=v_2 in transition matrices?

T(v_1)=v_2 represents the transformation of a vector v_1 to a new vector v_2 using the transition matrix T. This transformation allows us to change the basis of a vector space, which is useful in solving problems in linear algebra and other fields of mathematics.

4. Can a transition matrix have non-numeric elements?

No, a transition matrix can only have numerical elements since it is a mathematical object used for transformations. However, these numerical elements can represent any type of data, such as real numbers, complex numbers, or even binary numbers.

5. How are transition matrices used in real-world applications?

Transition matrices have various applications in fields such as physics, engineering, and computer science. They can be used in image processing to transform images, in economics to model changes in economic systems, and in machine learning to represent neural networks. They are also useful in analyzing Markov chains and solving problems in quantum mechanics.

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