Change of Basis: Finding PC<->B Matrix for V=R^2 with Given B and C

In summary, the change of basis matrix is a matrix that, when multiplied by a column B-coordinate vector, gives the same vector represented as a column C-coordinate vector. To find this matrix, you can solve relevant systems of equations using the given ordered bases B and C.
  • #1
snoggerT
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find the change of basis matrix PC<->B from the given ordered basis B to the given ordered basis C of the vector space V:

V=R^2; B={(-5,-3),(4,28)}; C={(6,2),(1,-1)}






The Attempt at a Solution



I'm having a hard time grasping the concept of changing basis. Can someone please explain it to me? my books explanation seems rather abstract and hard to follow.
 
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  • #2
Can you write an arbitrary vector [itex]\vec{v}=<v_x,v_y>[/itex] in terms of either basis?
 
  • #3
The change of basis matrix is a matrix that when multiplied by a column B-coordinate vector gives the same vector represented as a column C coordinate vector.

(a b)(-5) = (6)
(c d)(-3) (2)

(a b)(4 ) = (1)
(c d)(28) (-1)

Do the multiplication and solve the relevant systems to find a,b,c,d.
 
  • #4
First of all, to "change bases", you have to have two bases! Let's use P2, the set of quadratic polynomials, ax2+ bx+ c, as an example (we can add two polynomials and multiply a polynomial by a real number so that is a vector space over the real numbers). The "standard" basis is x2, x, and 1. As long as we understand we are using those "vectors" as basis, in that order, we can use <a, b, c> to represent ax2+ bx+ c: the "x2, x, and 1 are "understood".

But (x- 1)2= x2- 2x+ 1, x- 1, and 1 is also a basis. Since the "standard" basis for P2 has 3 vectors, it has dimension 3. This new set also contains 3 "vectors" so as long as they are independent . To show they are independent, look at p(x-1)2+ q(x-1)+ r= 0 (the 0 function: 0 for all x). Since that is 0 for all x, taking x= 1gives r= 0. If that is 0 for all x, it is a constant and so its derivative, 2p(x-1)+ q= 0 for all x. Again taking x= 1, we get q= 0. That is, the original equation was really p(x-1)2= 0 and, taking x= 2 now, p= 0. Since p= q= r= 0, those "vectors" are independent and so a basis.

If I wanted to write ax2+ bx+ c in that new basis, I would have to find p, q, r so that p(x- 1)2+ q(x-1)+ r= ax2+ bx+ c for all x. Do pretty much what we did before: taking x= 1, r= a+ b+ c. Taking the derivative of each side,
2p(x-1)+ q= 2ax+ b, again for all x. Taking x= 1 again, q= 2a+ b. Taking the second derivative of both sides, 2p= 2a so p= a. (Multiplying p(x-1)2 and q(x-1) out, collecting coefficients of like and setting corresponding coefficients on both sides equal would give the same thing: p= a, q= 2a+ b, and r= a+ b+ c.) That is, the polynomial represented by <a, b, c> in the first basis (that is, ax2+ bx+ c) is represented by (a, 2a+ b, a+ b+ c) (which is a(x- 1)2+ (2a+ b)(x-1)+ (a+b+c)) in the new basis. If you multiply those out you should see that you get the same thing.

The "change of basis" matrix must convert the <a, b, c> of a vector written in one basis into the components for the same vector as written in a new basis. In the example above, multiplying the basis by <a, b, c> must give <a, 2a+ b, a+ b+ c> . In particular, it must change <1, 0, 0> to <1, 2, 1> (a= 1, b= 0, c= 0 here), change <0, 1, 0> to <0, 1, 1> (a= 0, b= 1, c= 0), and change <0, 0, 1> to <0, 0, 1> (a= 0, b= 0, c= 1). The reason I like to use <1, 0, 0>, <0, 1, 0>, and <0, 0, 1> is because it is easy to see that a matrix multiplied by <1, 0, 0> just gives the numbers in the first column, multiplied by <0, 1, 0> gives the numbers in the second column, multiplied by <0, 0, 1> gives the numbers in the third column. In other words, the "change of basis" matrix must have <1, 2, 1>, <0, 1, 0> and <0, 0, 1> as the first, second and third columns: it is
[tex]\left(\begin{array}{ccc} 1 & 2 & 1 \\0 & 1 & 0 \\ 0 & 0 & 1\end{array}\right)[/tex]
 
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1. What is "change of basis" in linear algebra?

Change of basis is a fundamental concept in linear algebra that refers to the process of representing a vector or a linear transformation in terms of a different set of basis vectors. It involves finding the coordinates of a vector or a transformation with respect to a new basis, which can help simplify calculations and provide a different perspective on the data.

2. Why is change of basis important in linear algebra?

Change of basis is important because it allows us to work with vectors and linear transformations in different coordinate systems, which can be useful in various applications. It also helps in understanding the relationship between different vector spaces and transformations, and can lead to more efficient and elegant solutions to problems.

3. How do you perform a change of basis?

To perform a change of basis, we first need to identify the old basis and the new basis. Then, we can use a change of basis matrix to transform the coordinates of the vector or transformation from the old basis to the new basis. This matrix is usually obtained by expressing the old basis vectors in terms of the new basis vectors.

4. What is the role of change of basis in solving systems of linear equations?

Change of basis can be useful in solving systems of linear equations by transforming the system into a new coordinate system where the solution may be easier to find. This can also help in understanding the geometric interpretation of the solutions and how they relate to the original system of equations.

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

Eigenvectors and eigenvalues play an important role in change of basis as they provide a way to find a new basis that may be more suitable for a given problem. In fact, the eigenvectors of a linear transformation form a basis for the vector space, and using them as the new basis can simplify calculations involving that transformation. Additionally, the eigenvalues of a transformation may reveal important properties about the transformation and its behavior under a change of basis.

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