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The determinant of amatrix[abcd]isadbc (we have seen this quantity inExercise 2.1.13alreadyalready).Find the determinant of a matrix thatrepresents.a(n)

a. orthogonal projection

b. reflection about a line

c. rotation

d. (horizontal or vertical) shear.

What do your answers tell you about the invertibility of these matrices?

Short Answer

Expert verified

a. The orthogonal projection is,0.

b. The reflection about a line is,-1.

c. The rotation is,.1

d. The horizontal or vertical shear is1,.

Step by step solution

01

Compute the orthogonal projection. 

(a)

Consider the matrix,

a(n)=[a2ababb2]

The determinant of the matrix is,

det[a(n)]=det([a2ababb2])det[a(n)]=a2b2ababdet[a(n)]=a2b2a2b2det[a(n)]=0

As the determinant of the matrix is zero, thus, it is not invertible. The zero determinant of the matrix represents the orthogonal projection of .0

02

Compute the reflection about a line. 

(b)

Consider the matrix,

A=[abcd]

The reflection matrix is,

Ar=[abba]

The determinant of the matrix is,

det[Ar]=det([abba])det[Ar]=aabbdet[Ar]=a2b2det[Ar]=(a2+b2)

Thus,

det[Ar]=(a2+b2)det[Ar]=1鈥夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌夆赌(a2+b2=1)

As the determinant of the matrix is nonzero, thus, it is invertible. The determinant of the matrix represents the reflection about a line of -1.

03

Compute the rotation. 

(c)

Consider the matrix,

R=[cossinsincos]

The determinant of the matrix is,

det[R]=det([cossinsincos])det[R]=coscossinsindet[R]=cos2+sin2det[R]=1

As the determinant of the matrix is nonzero, thus, it is invertible. The determinant of the matrix represents the rotation of -1.

04

Compute the horizontal/vertical shear.

(d)

Consider the matrix,

K=[1k01]or[10k1]

The determinant of the matrix is,

det[K]=det([1k01])det[K]=110kdet[K]=10det[K]=1

As the determinant of the matrix is nonzero, thus, it is invertible. The determinant of the matrix represents the horizontal/vertical of 1 .

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Most popular questions from this chapter

In this exercise we will verify part (b) of Theorem 2.3.11 in the special case when A is the transition matrix [0.40.30.60.7]andxis the distribution vector[10]. [We will not be using parts (a) and (c) of Theorem 2.3.11]. The general proof of Theorem 2.3.11 runs along similar lines, as we will see in Chapter 7.

  1. ComputeA[12]andA[1-1]. WriteA[1-1]as a scalar multiple of the vector[1-1].
  2. Write the distribution vectorx=[10]as a linear combination of the vectors[12]and[1-1]
  3. Use your answers in part (a) and (b) to writeAxas a linear combination of the vectors[12]and[1-1]. More generally, write Amxas a linear combination of vectors[12]and[1-1], for any positive integer m. See Exercise 81.
  4. In your equation in part (c), let got to infinity to find limmAmx. Verify that your answer is the equilibrium distribution for A.

Question:TRUE OR FALSE?

The matrix product(abcd)d-b-ca is always a scalar multiple of l2.

TRUE OR FALSE?

If a matrixA=(abcd) represents the orthogonal projection onto a line L , then the equationa2+b2+c2+d2=1must hold.

TRUE OR FALSE?

There exists an invertible22 matrix A such thatA-1=-A.

Use the concept of a linear transformation in terms of the formula y=Ax鈬赌, and interpret simple linear transformations geometrically. Find the inverse of a linear transformation from localid="1659964769815" 2to2to (if it exists). Find the matrix of a linear transformation column by column.

Consider the transformations from3to3defined in Exercises 1 through 3. Which of these transformations are linear?

  1. y1=2x2y2=x2+2y3=2x2
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