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Consider the following geometric 2D transformations: D, a dilation (in which x-coordinates and y-coordinates are scaled by the same factor); R, a rotation; and T a translation. Does D commute with R? That is, is \(D\left( {R\left( {\bf{x}} \right)} \right) = R\left( {D\left( {\bf{x}} \right)} \right)\)for all \({\bf{x}}\) in \({\mathbb{R}^{\bf{2}}}\)? Does D commute with T? Does R commute with T?

Short Answer

Expert verified

D commutes with R, and matrices D and R do not commute with T.

Step by step solution

01

Write the transformation matrix for dilation, rotation, and translation

Let the transformation matrices in homogenous coordinates for dilation, rotation and translation be

\(D = \left[ {\begin{array}{*{20}{c}}s&0&0\\0&s&0\\0&0&1\end{array}} \right]\), \(R = \left[ {\begin{array}{*{20}{c}}{\cos \phi }&{ - \sin \phi }&0\\{\sin \phi }&{\cos \phi }&0\\0&0&1\end{array}} \right]\), and \(T = \left[ {\begin{array}{*{20}{c}}1&0&h\\0&1&k\\0&0&1\end{array}} \right]\).

02

Compute the product of transformation matrices

Calculate the value of \(DR\).

\(DR = \left[ {\begin{array}{*{20}{c}}{s\cos \phi }&{ - s\sin \phi }&0\\{s\sin \phi }&{s\cos \phi }&0\\0&0&1\end{array}} \right]\)

Calculate the value of \(RD\).

\[RD = \left[ {\begin{array}{*{20}{c}}{s\cos \phi }&{ - s\sin \phi }&0\\{s\sin \phi }&{s\cos \phi }&0\\0&0&1\end{array}} \right]\]

Calculate the value of \(DT\).

\(DT = \left[ {\begin{array}{*{20}{c}}s&0&{sh}\\0&s&{sk}\\0&0&1\end{array}} \right]\)

Calculate the value of \(TD\).

\(TD = \left[ {\begin{array}{*{20}{c}}s&0&h\\0&s&k\\0&0&1\end{array}} \right]\)

Calculate the value of \(RT\).

\(RT = \left[ {\begin{array}{*{20}{c}}{\cos \phi }&{ - \sin \phi }&{h\cos \phi - k\sin \phi }\\{\sin \phi }&{\cos \phi }&{h\sin \phi + k\cos \phi }\\0&0&1\end{array}} \right]\)

Calculate the value of \(TR\).

\(TR = \left[ {\begin{array}{*{20}{c}}{\cos \varphi }&{ - \sin \varphi }&h\\{\sin \varphi }&{\cos \varphi }&k\\0&0&1\end{array}} \right]\)

03

Check the commutation of transformation matrices

For the transformation matrices, \(DR = RD\).

So, D commutes with R.

\(DT \ne TD\)

So, D does not commute with T.

And

\(RT \ne TR\)

So, R does not commute with T.

Hence, D commutes with R, and matrices D and R do not commute with T.

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Most popular questions from this chapter

Exercises 15 and 16 concern arbitrary matrices A, B, and Cfor which the indicated sums and products are defined. Mark each statement True or False. Justify each answer.

15. a. If A and B are \({\bf{2}} \times {\bf{2}}\) with columns \({{\bf{a}}_1},{{\bf{a}}_2}\) and \({{\bf{b}}_1},{{\bf{b}}_2}\) respectively, then \(AB = \left( {\begin{aligned}{*{20}{c}}{{{\bf{a}}_1}{{\bf{b}}_1}}&{{{\bf{a}}_2}{{\bf{b}}_2}}\end{aligned}} \right)\).

b. Each column of ABis a linear combination of the columns of Busing weights from the corresponding column of A.

c. \(AB + AC = A\left( {B + C} \right)\)

d. \({A^T} + {B^T} = {\left( {A + B} \right)^T}\)

e. The transpose of a product of matrices equals the product of their transposes in the same order.

In Exercises 1–9, assume that the matrices are partitioned conformably for block multiplication. Compute the products shown in Exercises 1–4.

3. \[\left[ {\begin{array}{*{20}{c}}{\bf{0}}&I\\I&{\bf{0}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}W&X\\Y&Z\end{array}} \right]\]

[M] Suppose memory or size restrictions prevent your matrix program from working with matrices having more than 32 rows and 32 columns, and suppose some project involves \(50 \times 50\) matrices A and B. Describe the commands or operations of your program that accomplish the following tasks.

a. Compute \(A + B\)

b. Compute \(AB\)

c. Solve \(Ax = b\) for some vector b in \({\mathbb{R}^{50}}\), assuming that \(A\) can be partitioned into a \(2 \times 2\) block matrix \(\left[ {{A_{ij}}} \right]\), with \({A_{11}}\) an invertible \(20 \times 20\) matrix, \({A_{22}}\) an invertible \(30 \times 30\) matrix, and \({A_{12}}\) a zero matrix. [Hint: Describe appropriate smaller systems to solve, without using any matrix inverse.]

Let \(T:{\mathbb{R}^n} \to {\mathbb{R}^n}\) be an invertible linear transformation, and let Sand U be functions from \({\mathbb{R}^n}\) into \({\mathbb{R}^n}\) such that \(S\left( {T\left( {\mathop{\rm x}\nolimits} \right)} \right) = {\mathop{\rm x}\nolimits} \) and \(\)\(U\left( {T\left( {\mathop{\rm x}\nolimits} \right)} \right) = {\mathop{\rm x}\nolimits} \) for all x in \({\mathbb{R}^n}\). Show that \(U\left( v \right) = S\left( v \right)\) for all v in \({\mathbb{R}^n}\). This will show that Thas a unique inverse, as asserted in theorem 9. [Hint: Given any v in \({\mathbb{R}^n}\), we can write \({\mathop{\rm v}\nolimits} = T\left( {\mathop{\rm x}\nolimits} \right)\) for some x. Why? Compute \(S\left( {\mathop{\rm v}\nolimits} \right)\) and \(U\left( {\mathop{\rm v}\nolimits} \right)\)].

3. Find the inverse of the matrix \(\left( {\begin{aligned}{*{20}{c}}{\bf{8}}&{\bf{5}}\\{ - {\bf{7}}}&{ - {\bf{5}}}\end{aligned}} \right)\).

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