Linear transformation and change of basis

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Homework Help Overview

The discussion revolves around linear transformations and change of basis in the context of linear algebra, specifically focusing on a transformation matrix expressed in terms of different bases.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants explore the concept of change of basis matrices and their application in expressing linear transformations. There are attempts to derive the transformation matrix in terms of a non-standard basis, and questions arise regarding the understanding of the transformation process and the representation of vectors in different bases.

Discussion Status

Some participants have provided links to external resources for further guidance, while others are engaged in clarifying their understanding of the transformation process and the implications of expressing vectors in different bases. There is an ongoing exploration of the mathematical relationships involved, with no explicit consensus reached yet.

Contextual Notes

Participants mention spending significant time on the problem and express a desire for step-by-step guidance, indicating a potential lack of clarity in the foundational concepts being discussed.

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Homework Statement



Let B = {(1, -2),(2, -3)} and S be the standard basis of R2
and [-8,-4;9,4]
be a linear transformation expressed in terms of the standard basis?




The Attempt at a Solution



1) What is the change of basis matrix PSB ?
1,2
-2,-3

2)What is the change of basis matrix PBS ?
-3,-2
2,1

What is the linear transform expressed in terms of the basis B?
i spent 4 hours going through the proof for this part but unable to bridge a connection. Something is lacking in my understanding.
Give me a step by step guidance on this one.
 
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pondzo said:
I won't give you a step by step guide but i will provide a link that gives a better one than i ever could!
https://www.khanacademy.org/math/li...transformation-matrix-with-respect-to-a-basis

Khan is good but his proof and subscript can at times be sloppy. I enjoy Mathispower4u (discovered it before Physicforum did) but it seems there are no videos on change on basis on Mathispower4u.

But anyway, I have a much rigorous proof on hand that I wish to understand fully.

The transformation machine that maps the vector v with respect to the standard basis, s, is given as [f(v)]s.
[f(v)]s = Ass [v]s
Ass = [ [f(e1)]s [f(e2)]s...[f(en)]s ] (I don't get this part)

There's more to come but I hope to understand this part first before proceeding...
 
Last edited:
The basic point is this: if we have basis {u, v} then every vector can be written in the form au+ bv and represented as "\begin{bmatrix}a \\ b\end{bmatrix}". In particular, u= 1u+ 0v and is represented as \begin{bmatrix}1 \\ 0\end{bmatrix} while v= 0u+ 1v and is represented as \begin{bmatrix}0 \\ 1 \end{bmatrix}. Now suppose linear transformation, A, is represented by the matrix
\begin{bmatrix}a & b \\ c & d\end{bmatrix}
Then Au is
\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}1 \\ 0 \end{bmatrix}= \begin{bmatrix}a \\ c \end{bmatrix}
and Av is
\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}0 \\ 1 \end{bmatrix}= \begin{bmatrix}b \\ d\end{bmatrix}

That is, applying the linear transformation to the basis vectors, and then writing the result as a linear combination of the basis vectors, the coefficents give the columns.

In this particular case,
\begin{bmatrix}-8 & -4\\ 9 & 4\end{bmatrix}\begin{bmatrix}1 \\ -2\end{bmatrix}= \begin{bmatrix}0 \\ 1\end{bmatrix}
and we can write \begin{bmatrix}0 \\ 1\end{bmatrix}= -2\begin{bmatrix}1 \\ -2\end{bmatrix}+ 1\begin{bmatrix}2 \\ -3\end{bmatrix}

so the first column of the matrix representation is \begin{bmatrix}-2 \\ 1\end{bmatrix}

Similarly,
\begin{bmatrix}-8 & -4\\ 9 & 4\end{bmatrix}\begin{bmatrix}2 \\ -3\end{bmatrix}= \begin{bmatrix}-4 \\ 6\end{bmatrix}
and \begin{bmatrix}-4 \\ 6\end{bmatrix}= 0\begin{bmatrix}1 \\-2\end{bmatrix}- 2\begin{bmatrix}2 \\ -3\end{bmatrix}
so the second column is \begin{bmatrix}0 \\ -2\end{bmatrix}

The matrix representation in this (ordered) basis is
\begin{bmatrix}-2 & 0 \\1 & -2\end{bmatrix}
 
HallsofIvy said:
The basic point is this: if we have basis {u, v} then every vector can be written in the form au+ bv and represented as "\begin{bmatrix}a \\ b\end{bmatrix}". In particular, u= 1u+ 0v and is represented as \begin{bmatrix}1 \\ 0\end{bmatrix} while v= 0u+ 1v and is represented as \begin{bmatrix}0 \\ 1 \end{bmatrix}. Now suppose linear transformation, A, is represented by the matrix
\begin{bmatrix}a & b \\ c & d\end{bmatrix}
Then Au is
\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}1 \\ 0 \end{bmatrix}= \begin{bmatrix}a \\ c \end{bmatrix}
and Av is
\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}0 \\ 1 \end{bmatrix}= \begin{bmatrix}b \\ d\end{bmatrix}

That is, applying the linear transformation to the basis vectors, and then writing the result as a linear combination of the basis vectors, the coefficents give the columns.

In this particular case,
\begin{bmatrix}-8 & -4\\ 9 & 4\end{bmatrix}\begin{bmatrix}1 \\ -2\end{bmatrix}= \begin{bmatrix}0 \\ 1\end{bmatrix}
and we can write \begin{bmatrix}0 \\ 1\end{bmatrix}= -2\begin{bmatrix}1 \\ -2\end{bmatrix}+ 1\begin{bmatrix}2 \\ -3\end{bmatrix}

so the first column of the matrix representation is \begin{bmatrix}-2 \\ 1\end{bmatrix}

Similarly,
\begin{bmatrix}-8 & -4\\ 9 & 4\end{bmatrix}\begin{bmatrix}2 \\ -3\end{bmatrix}= \begin{bmatrix}-4 \\ 6\end{bmatrix}
and \begin{bmatrix}-4 \\ 6\end{bmatrix}= 0\begin{bmatrix}1 \\-2\end{bmatrix}- 2\begin{bmatrix}2 \\ -3\end{bmatrix}
so the second column is \begin{bmatrix}0 \\ -2\end{bmatrix}

The matrix representation in this (ordered) basis is
\begin{bmatrix}-2 & 0 \\1 & -2\end{bmatrix}
Would the outcome be any different if I first went down the route of

[-8;-9] = α1[1;0] + α2[0;1]
[-4;4] = β1[1;0] + β1[0;1]

that is, I express each column of the matrix A as a linear combination of the vectors in S.
 
HallsofIvy said:
The basic point is this: if we have basis {u, v} then every vector can be written in the form au+ bv and represented as "\begin{bmatrix}a \\ b\end{bmatrix}". In particular, u= 1u+ 0v and is represented as \begin{bmatrix}1 \\ 0\end{bmatrix} while v= 0u+ 1v and is represented as \begin{bmatrix}0 \\ 1 \end{bmatrix}.


Now suppose linear transformation, A, is represented by the matrix
\begin{bmatrix}a & b \\ c & d\end{bmatrix}
Then Au is
\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}1 \\ 0 \end{bmatrix}= \begin{bmatrix}a \\ c \end{bmatrix}
and Av is
\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}0 \\ 1 \end{bmatrix}= \begin{bmatrix}b \\ d\end{bmatrix}

That is, applying the linear transformation to the basis vectors, and then writing the result as a linear combination of the basis vectors, the coefficents give the columns.

In this particular case,
\begin{bmatrix}-8 & -4\\ 9 & 4\end{bmatrix}\begin{bmatrix}1 \\ -2\end{bmatrix}= \begin{bmatrix}0 \\ 1\end{bmatrix}
and we can write \begin{bmatrix}0 \\ 1\end{bmatrix}= -2\begin{bmatrix}1 \\ -2\end{bmatrix}+ 1\begin{bmatrix}2 \\ -3\end{bmatrix}

so the first column of the matrix representation is \begin{bmatrix}-2 \\ 1\end{bmatrix}

Similarly,
\begin{bmatrix}-8 & -4\\ 9 & 4\end{bmatrix}\begin{bmatrix}2 \\ -3\end{bmatrix}= \begin{bmatrix}-4 \\ 6\end{bmatrix}
and \begin{bmatrix}-4 \\ 6\end{bmatrix}= 0\begin{bmatrix}1 \\-2\end{bmatrix}- 2\begin{bmatrix}2 \\ -3\end{bmatrix}
so the second column is \begin{bmatrix}0 \\ -2\end{bmatrix}

The matrix representation in this (ordered) basis is
\begin{bmatrix}-2 & 0 \\1 & -2\end{bmatrix}

Ok I got this. Basically, all I had to find was [T(x)s]B.
 

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