Linear Algebra II - Change of Basis

In summary, to find an invertible matrix P such that P-1MB0(T)P=MB(T), we first need to find MB0(T) and MB(T). MB0(T) is easily found by expressing each a, b, and c as linear combinations of the basis vectors in B0. To find MB(T), we can use the fact that the columns of this matrix are the result of T on each of the basis vectors. From the given T function, we can see that T(1,1,0) = (1,1,-3), which explains the first column in the textbook's MB(T) matrix. Similarly, using the coefficients of the linear combination of each basis vector, we can find
  • #1
lemonsare
3
0

Homework Statement



From Linear Algebra with applications 7th Edition by Keith Nicholson.
Chapter 9.2 Example 2.

Let T: R3 → R3 be defined by T(a,b,c) = (2a-b,b+c,c-3a).
If B0 denotes the standard basis of R3 and B = {(1,1,0),(1,0,1),(0,1,0)}, find an invertible matrix P such that P-1MB0(T)P=MB(T).

Homework Equations




The Attempt at a Solution



I know to find P, I have to first find MB0(T) and MB(T).

MB0(T) is easy because I have to just find each a, b, and c as linear combinations of B0 and the coefficients are MB0(T).

However, I'm not sure how to find MB(T). In the textbook, they write:

MB(T) = [CB(1,1,-3) CB(2,1,-2) CB(-1,1,0)]

I cannot figure out where they came up with these numbers (1,1,-3), (2,1,-2), and (-1,1,0).

Please help. Thank you!

 
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  • #2
##M_B(T) ## is the 3x 3 matrix where the columns are the result of T on each of the basis vectors.
T(1,1,0) = (1,1,-3).
So your matrix will look like:
##\begin{bmatrix} 1& 2& -1 \\ 1& 1& 1 \\ -3 & -2 & 0 \end{bmatrix}##
 
  • #3
Oh wow thanks! That was simple.

But in the textbook ##M_B(T)## = ##\begin{bmatrix} 4&4&-1\\-3&-2&0\\-3&-3&2\end{bmatrix}##

From trying to figure out where (1,1,-3) came from, I figured out that (4,-3,-3) came from the coefficients of the linear combination of each of the basis vectors. But is that wrong?
 

Related to Linear Algebra II - Change of Basis

1. What is the purpose of change of basis in linear algebra?

Change of basis is used to transform a vector from one coordinate system to another. It is particularly useful when working with linear transformations or matrices, as it allows for easier calculations and better understanding of how a transformation affects a vector.

2. How is change of basis related to eigenvalues and eigenvectors?

Change of basis involves finding a new set of basis vectors for a vector space. The eigenvectors of a matrix are a set of basis vectors for that matrix, and the eigenvalues determine how the basis vectors are scaled. Therefore, change of basis is closely related to eigenvalues and eigenvectors.

3. Can change of basis be used to solve systems of linear equations?

Yes, change of basis can be used to solve systems of linear equations. By converting the system of equations into matrix form, the change of basis can be used to transform the matrix into a diagonal form, making it easier to solve the system.

4. How does change of basis affect the geometric interpretation of a vector?

Change of basis does not change the geometric interpretation of a vector. The vector remains the same, but its representation in terms of different basis vectors may change. This can affect its coordinates and how it is represented in a specific coordinate system, but the geometric meaning of the vector remains unchanged.

5. What are some real-life applications of change of basis?

Change of basis is used in many fields, including computer graphics, data compression, and signal processing. For example, in computer graphics, change of basis is used to rotate and scale objects in a 3D space. In data compression, change of basis is used to reduce the size of large datasets without losing important information. In signal processing, change of basis is used to analyze and manipulate signals in different domains, such as time or frequency.

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