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In Exercises 1 and 2,find the change of variable \({\rm{x}} = P{\rm{y}}\) that transforms the quadratic form \({{\rm{x}}^T}A{\rm{x}}\) into \({{\rm{y}}^T}D{\rm{y}}\) as shown.

2. \(3x_1^2 + 3x_2^2 + 5x_3^2 + 6x_1^{}x_2^{} + 2x_1^{}x_3^{} + 2x_2^{}x_3^{} = 7y_1^2 + 4y_2^2\).

Short Answer

Expert verified

The required change of variable is:

\(P = \left[ {\begin{array}{*{20}{c}}{\frac{1}{{\sqrt 3 }}}&{ - \frac{1}{{\sqrt 6 }}}&{ - \frac{1}{{\sqrt 2 }}}\\{\frac{1}{{\sqrt 3 }}}&{ - \frac{1}{{\sqrt 6 }}}&{\frac{1}{{\sqrt 2 }}}\\{\frac{1}{{\sqrt 3 }}}&{\frac{2}{{\sqrt 6 }}}&0\end{array}} \right]\).

Step by step solution

01

Symmetric Matrices and Quadratic Forms.

When any Symmetric Matrix\(A\)is diagonalized orthogonallyas \(PD{P^{ - 1}}\) we have:

\(\begin{array}{l}{x^T}Ax = {y^T}Dy\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\left\{ {{\rm{as }}x = Py} \right\}\\{\rm{and}}\\\left\| x \right\| = \left\| {Py} \right\| = \left\| y \right\|\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\left\{ {\forall y \in \mathbb{R}} \right\}\end{array}\)

02

Find the Change of Variables. 

As per the question, we have:

\(3x_1^2 + 3x_2^2 + 5x_3^2 + 6x_1^{}x_2^{} + 2x_1^{}x_3^{} + 2x_2^{}x_3^{} = 7y_1^2 + 4y_2^2\)

The matrix of thequadratic formwill be:

\(A = \left[ {\begin{array}{*{20}{c}}3&3&1\\3&3&1\\1&1&5\end{array}} \right]\)

And for each eigenvalue of\(A\)defined in the right-hand side of the equation will be expressed as:

\(\begin{array}{l}{\lambda _1} = 7 \Rightarrow {P_1} = \left[ {\begin{array}{*{20}{c}}{\frac{1}{{\sqrt 3 }}}\\{\frac{1}{{\sqrt 3 }}}\\{\frac{1}{{\sqrt 3 }}}\end{array}} \right]\\{\lambda _2} = 4 \Rightarrow {P_2} = \left[ {\begin{array}{*{20}{c}}{ - \frac{1}{{\sqrt 6 }}}\\{ - \frac{1}{{\sqrt 6 }}}\\{\frac{2}{{\sqrt 6 }}}\end{array}} \right]\\{\lambda _3} = 0 \Rightarrow {P_3} = \left[ {\begin{array}{*{20}{c}}{ - \frac{1}{{\sqrt 2 }}}\\{\frac{1}{{\sqrt 2 }}}\\0\end{array}} \right]\end{array}\)

Hence,therequired change of variable is:

\(P = \left[ {\begin{array}{*{20}{c}}{\frac{1}{{\sqrt 3 }}}&{ - \frac{1}{{\sqrt 6 }}}&{ - \frac{1}{{\sqrt 2 }}}\\{\frac{1}{{\sqrt 3 }}}&{ - \frac{1}{{\sqrt 6 }}}&{\frac{1}{{\sqrt 2 }}}\\{\frac{1}{{\sqrt 3 }}}&{\frac{2}{{\sqrt 6 }}}&0\end{array}} \right]\).

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Most popular questions from this chapter

Question 11: Prove that any \(n \times n\) matrix A admits a polar decomposition of the form \(A = PQ\), where P is a \(n \times n\) positive semidefinite matrix with the same rank as A and where Q is an \(n \times n\) orthogonal matrix. (Hint: Use a singular value decomposition, \(A = U\sum {V^T}\), and observe that \(A = \left( {U\sum {U^T}} \right)\left( {U{V^T}} \right)\).) This decomposition is used, for instance, in mechanical engineering to model the deformation of a material. The matrix P describe the stretching or compression of the material (in the directions of the eigenvectors of P), and Q describes the rotation of the material in space.

Classify the quadratic forms in Exercises 9-18. Then make a change of variable, \({\bf{x}} = P{\bf{y}}\), that transforms the quadratic form into one with no cross-product term. Write the new quadratic form. Construct P using the methods of Section 7.1.

9. \({\bf{4}}x_{\bf{1}}^{\bf{2}} - {\bf{4}}{x_{\bf{1}}}{x_{\bf{2}}} + {\bf{4}}x_{\bf{2}}^{\bf{2}}\)

Let u be a unit vector in \({\mathbb{R}^n}\), and let \(B = {\bf{u}}{{\bf{u}}^T}\).

  1. Given any x in \({\mathbb{R}^n}\), compute Bx and show that Bx is the orthogonal projection of x onto u, as described in Section 6.2.
  2. Show that B is a symmetric matrix and \({B^{\bf{2}}} = B\).
  3. Show that u is an eigenvector of B. What is the corresponding eigenvalue?

Classify the quadratic forms in Exercises 9–18. Then make a change of variable, \({\bf{x}} = P{\bf{y}}\), that transforms the quadratic form into one with no cross-product term. Write the new quadratic form. Construct \(P\) using the methods of Section 7.1.

11. \({\bf{2}}x_{\bf{1}}^{\bf{2}} - {\bf{4}}{x_{\bf{1}}}{x_{\bf{2}}} - x_{\bf{2}}^{\bf{2}}\)

Question 8: Use Exercise 7 to show that if A is positive definite, then A has a LU factorization, \(A = LU\), where U has positive pivots on its diagonal. (The converse is true, too).

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