Linear Algebra- Quadratic form and change of basis

In summary, to find q(v) with respect to B, use the formula q(v) = YT PTP Y and note that the resulting matrix may not be diagonal if the basis B is not a basis for Rn.
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Homework Statement



Suppose that for each v = (x1, x1, ... xn) in Rn, q(v) = XTAX for the given matrix A. For the given basis B of Rn, find the expression for q(v) in terms of the coordiantes yi of v relative to B.

a) A = [tex]
\begin{bmatrix}3/2&{\sqrt{2}}&-1/2\\{\sqrt{2}}&1&-{\sqrt{2}}\\-1/2&{\sqrt{2}}&-5/2\end{bmatrix}


B = {(1,0,1), (3, {\sqrt{2}}, 1), (3{\sqrt{2}}, -4, {\sqrt{2}}) [/tex]

Homework Equations


The Attempt at a Solution



So I read the theorem about A wrt to B is PTAP where P is the change of basis matrix from B to E3.. so I can just get A wrt to B by doing that right? I transpose P and the multiply it out like that? And it should give me a diagonal matrix?

But when I do that I get something really wrong? Like nothing is diagonal.
Is it possible for the result to have a zero column and q(v) wrt to B will not have all the terms?
 
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  • #2


Yes, it is possible for the result to have a zero column and for q(v) with respect to B to not have all the terms. This would occur if the basis B is not a basis for Rn, meaning that the vectors in B are not linearly independent. In this case, the matrix P would not be invertible and the change of basis formula would not work.

To find q(v) with respect to B, you can use the formula q(v) = YT PTP Y, where Y is the coordinate vector of v with respect to B. This can be derived from the change of basis formula PTAP. The resulting matrix will not necessarily be diagonal, as it depends on the specific values of the coordinates yi and the matrix A.
 

Related to Linear Algebra- Quadratic form and change of basis

1. What is a quadratic form in linear algebra?

A quadratic form is an expression in linear algebra that involves squares and products of variables. It typically takes the form of a polynomial of degree two in multiple variables. Quadratic forms are useful for solving optimization problems and representing geometric objects such as ellipsoids and hyperbolas.

2. How do you change the basis in linear algebra?

To change the basis in linear algebra, you can use a change of basis matrix. This matrix contains the basis vectors of the new basis as its columns. To transform a vector from the old basis to the new basis, you multiply the vector by the change of basis matrix. To transform a linear transformation from the old basis to the new basis, you multiply the matrix representing the linear transformation by both the change of basis matrix and its inverse.

3. What is the role of eigenvalues and eigenvectors in quadratic forms?

Eigenvalues and eigenvectors play a crucial role in quadratic forms. The eigenvalues of a symmetric matrix are the coefficients in the quadratic form. The eigenvectors of a symmetric matrix are the directions in which the quadratic form takes on its maximum and minimum values. Furthermore, the eigenvectors can be used to change the basis to a coordinate system in which the quadratic form takes on a simpler form.

4. How are quadratic forms used in machine learning?

In machine learning, quadratic forms are used to define and solve optimization problems. Many machine learning algorithms involve finding the maximum or minimum of a quadratic form, often with constraints. Quadratic forms are also used to represent cost functions and decision boundaries in classification problems.

5. What are the applications of quadratic forms in real life?

Quadratic forms have many applications in real life. They are used in physics to model the motion of objects under the influence of forces. In engineering, quadratic forms are used to analyze the stability of systems. In economics, they are used to model utility functions and production functions. Additionally, they are used in statistics to estimate parameters and make predictions in regression models.

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