math 22 linear algebra and its applications - lecture 7

24
Math 22 Linear Algebra and its applications - Lecture 7 - Instructor: Bjoern Muetzel

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Page 1: Math 22 Linear Algebra and its applications - Lecture 7

Math 22 –

Linear Algebra and its

applications

- Lecture 7 -

Instructor: Bjoern Muetzel

Page 2: Math 22 Linear Algebra and its applications - Lecture 7

GENERAL INFORMATION

▪ Office hours: Tu 1-3 pm, Th, Sun 2-4 pm in KH 229

▪ Tutorial: Tu, Th, Sun 7-9 pm in KH 105

▪ Homework: Homework 2 due Wednesday at 4 pm in the boxes

outside Kemeny 008. Separate your homework into

part A, part B, part C and part D and staple it.

▪ Midterm 1: Monday Oct 7 from 4-6 pm in Carpenter 013

Topics: till this Thursday (included)

Page 3: Math 22 Linear Algebra and its applications - Lecture 7

1

1.8

Linear Equations

in Linear Algebra

INTRODUCTION TO LINEAR

TRANSFORMATIONS

Page 4: Math 22 Linear Algebra and its applications - Lecture 7
Page 5: Math 22 Linear Algebra and its applications - Lecture 7

LINEAR TRANSFORMATIONS

▪ Summary: If a transformation T from Rn to Rm is

linear, then it maps Euclidean subspaces to Euclidean

subspaces.

Page 6: Math 22 Linear Algebra and its applications - Lecture 7

GEOMETRIC INTERPRETATION

▪ Example:

Page 7: Math 22 Linear Algebra and its applications - Lecture 7

GEOMETRIC INTERPRETATION

Page 8: Math 22 Linear Algebra and its applications - Lecture 7
Page 9: Math 22 Linear Algebra and its applications - Lecture 7

Slide 1.8- 9

TRANSFORMATIONS

Page 10: Math 22 Linear Algebra and its applications - Lecture 7

Slide 1.8- 10

TRANSFORMATIONS

Page 11: Math 22 Linear Algebra and its applications - Lecture 7

Slide 1.8- 11

MATRIX TRANSFORMATIONS

▪ Definition: Let A be an matrix. A matrix transformation

is the associated map given by T(x) = Ax, for any x in Rn

▪ For simplicity, we denote such a matrix transformation often by

.

▪ As each column of A has m columns, the domain of T is Rn and

the codomain of T is Rm.

m n

x xA

Page 12: Math 22 Linear Algebra and its applications - Lecture 7

Slide 1.8- 12

LINEAR TRANSFORMATIONS

(u v) (u) (v)T T T+ = +

( u) (u)T c cT=

x xA

Page 13: Math 22 Linear Algebra and its applications - Lecture 7

LINEAR TRANSFORMATIONS

▪ Consequences:

▪ As and we have:

iii. T(0) = 0

iv.

▪ If v1, …, vp in Rn are vectors then iv. implies that

T(Span{v1, …, vp }) = Span{T (v1), …, T (vp)}

Proof:

1 1 1 1( v ... v ) (v ) ... (v )

p p p pT c c cT c T+ + = + +

(u v) (u) (v)T T T+ = + ( u) (u)T c cT=

Page 14: Math 22 Linear Algebra and its applications - Lecture 7
Page 15: Math 22 Linear Algebra and its applications - Lecture 7

Slide 1.8- 15

LINEAR TRANSFORMATIONS

▪ Consequences:

iv.

▪ In engineering and physics, iv. is referred to as a superposition

principle.

▪ Think of v1, …, vp as signals that go into a system and

T (v1), …, T (vp) as the responses of that system to the signals.

▪ The system satisfies the superposition principle if whenever an

input is expressed as a linear combination of such signals, the

system’s response is the same linear combination of the

responses to the individual signals.

1 1 1 1( v ... v ) (v ) ... (v )

p p p pT c c cT c T+ + = + +

Page 16: Math 22 Linear Algebra and its applications - Lecture 7

Slide 1.8- 16

MATRIX TRANSFORMATIONS

▪1 3

3 5

1 7

A

− = −

2u

1

= −

(x) xT A=

a. Find T (u), the image of u under the transformation T.

b. Find an x in Rn whose image under T is b.

c. Is there more than one x whose image under T is b?

d. Determine if c is in the range of the transformation T.

Page 17: Math 22 Linear Algebra and its applications - Lecture 7

MATRIX TRANSFORMATIONS

▪ Solution:

.

Page 18: Math 22 Linear Algebra and its applications - Lecture 7
Page 19: Math 22 Linear Algebra and its applications - Lecture 7

MATRIX TRANSFORMATIONS

Page 20: Math 22 Linear Algebra and its applications - Lecture 7
Page 21: Math 22 Linear Algebra and its applications - Lecture 7

SHEAR TRANSFORMATION

▪ 1 3

0 1A

=

(x) xT A=

Page 22: Math 22 Linear Algebra and its applications - Lecture 7
Page 23: Math 22 Linear Algebra and its applications - Lecture 7

Slide 1.8- 23

SCALAR MULTIPLICATION

▪(x) xT r=

0 1r

1r

Page 24: Math 22 Linear Algebra and its applications - Lecture 7

Slide 1.8- 24

ROTATION