Math 2331 Linear Algebra

Similar documents
Math 4377/6308 Advanced Linear Algebra

Math 2331 Linear Algebra

Math 2331 Linear Algebra

Math 2331 Linear Algebra

Math 3191 Applied Linear Algebra

Math 2331 Linear Algebra

Math 2331 Linear Algebra

Math 4377/6308 Advanced Linear Algebra

Math 2331 Linear Algebra

Math 3191 Applied Linear Algebra

Elementary Matrices. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Matrix operations Linear Algebra with Computer Science Application

7.6 The Inverse of a Square Matrix

3.4 Elementary Matrices and Matrix Inverse

Math 4377/6308 Advanced Linear Algebra

February 20 Math 3260 sec. 56 Spring 2018

Math 60. Rumbos Spring Solutions to Assignment #17

Section 2.2: The Inverse of a Matrix

Inverting Matrices. 1 Properties of Transpose. 2 Matrix Algebra. P. Danziger 3.2, 3.3

Math 4377/6308 Advanced Linear Algebra

Fall Inverse of a matrix. Institute: UC San Diego. Authors: Alexander Knop

Applied Matrix Algebra Lecture Notes Section 2.2. Gerald Höhn Department of Mathematics, Kansas State University

Linear Algebra The Inverse of a Matrix

MAC Module 2 Systems of Linear Equations and Matrices II. Learning Objectives. Upon completing this module, you should be able to :

Math 1B03/1ZC3 - Tutorial 2. Jan. 21st/24th, 2014

Elementary maths for GMT

Section 12.4 Algebra of Matrices

6-2 Matrix Multiplication, Inverses and Determinants

Matrix Inverses. November 19, 2014

Math 147 Section 3.4. Application Example

Math 2331 Linear Algebra

MAT 1332: CALCULUS FOR LIFE SCIENCES. Contents. 1. Review: Linear Algebra II Vectors and matrices Definition. 1.2.

Matrix Algebra. Matrix Algebra. Chapter 8 - S&B

Kevin James. MTHSC 3110 Section 2.2 Inverses of Matrices

Review Let A, B, and C be matrices of the same size, and let r and s be scalars. Then

Chapter 2 Notes, Linear Algebra 5e Lay

MATH 2331 Linear Algebra. Section 2.1 Matrix Operations. Definition: A : m n, B : n p. Example: Compute AB, if possible.

Matrix & Linear Algebra

The matrix will only be consistent if the last entry of row three is 0, meaning 2b 3 + b 2 b 1 = 0.

Lecture 6 & 7. Shuanglin Shao. September 16th and 18th, 2013

Math Camp II. Basic Linear Algebra. Yiqing Xu. Aug 26, 2014 MIT

Matrix Algebra. Learning Objectives. Size of Matrix

MATH2210 Notebook 2 Spring 2018

A FIRST COURSE IN LINEAR ALGEBRA. An Open Text by Ken Kuttler. Matrix Arithmetic

x + 2y + 3z = 8 x + 3y = 7 x + 2z = 3

Elementary Row Operations on Matrices

GROUPS. Chapter-1 EXAMPLES 1.1. INTRODUCTION 1.2. BINARY OPERATION

MATRICES AND MATRIX OPERATIONS

MATH 2360 REVIEW PROBLEMS

Solutions to Exam I MATH 304, section 6

Linear Algebra Practice Problems

Math 4377/6308 Advanced Linear Algebra

Methods for Solving Linear Systems Part 2

Matrix Arithmetic. j=1

Linear Systems and Matrices

Math 240 Calculus III

Linear Algebra and Matrix Inversion

Finite Mathematics Chapter 2. where a, b, c, d, h, and k are real numbers and neither a and b nor c and d are both zero.

Lectures on Linear Algebra for IT

MA 138 Calculus 2 with Life Science Applications Matrices (Section 9.2)

We could express the left side as a sum of vectors and obtain the Vector Form of a Linear System: a 12 a x n. a m2

Math 313 Chapter 1 Review

E k E k 1 E 2 E 1 A = B

Section 4.5. Matrix Inverses

MATH Mathematics for Agriculture II

Math 2331 Linear Algebra

MATH 323 Linear Algebra Lecture 6: Matrix algebra (continued). Determinants.

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS. + + x 1 x 2. x n 8 (4) 3 4 2

Chapter 4 Systems of Linear Equations; Matrices

Components and change of basis

ECON 186 Class Notes: Linear Algebra

7.5 Operations with Matrices. Copyright Cengage Learning. All rights reserved.

Numerical Linear Algebra Homework Assignment - Week 2

Vectors and matrices: matrices (Version 2) This is a very brief summary of my lecture notes.

5x 2 = 10. x 1 + 7(2) = 4. x 1 3x 2 = 4. 3x 1 + 9x 2 = 8

If A is a 4 6 matrix and B is a 6 3 matrix then the dimension of AB is A. 4 6 B. 6 6 C. 4 3 D. 3 4 E. Undefined

1 Multiply Eq. E i by λ 0: (λe i ) (E i ) 2 Multiply Eq. E j by λ and add to Eq. E i : (E i + λe j ) (E i )

Assignment 1 Math 5341 Linear Algebra Review. Give complete answers to each of the following questions. Show all of your work.

Lesson 3. Inverse of Matrices by Determinants and Gauss-Jordan Method

GAUSSIAN ELIMINATION AND LU DECOMPOSITION (SUPPLEMENT FOR MA511)

MATH 221: SOLUTIONS TO SELECTED HOMEWORK PROBLEMS

ORIE 6300 Mathematical Programming I August 25, Recitation 1

POLI270 - Linear Algebra

Math 4377/6308 Advanced Linear Algebra

Chapter 1 Matrices and Systems of Equations

MATH 300, Second Exam REVIEW SOLUTIONS. NOTE: You may use a calculator for this exam- You only need something that will perform basic arithmetic.

Linear Algebra. Matrices Operations. Consider, for example, a system of equations such as x + 2y z + 4w = 0, 3x 4y + 2z 6w = 0, x 3y 2z + w = 0.

Chapter 1: Systems of linear equations and matrices. Section 1.1: Introduction to systems of linear equations

Math 3C Lecture 20. John Douglas Moore

Introduction. Vectors and Matrices. Vectors [1] Vectors [2]

Section 1.1 System of Linear Equations. Dr. Abdulla Eid. College of Science. MATHS 211: Linear Algebra

2.1 Matrices. 3 5 Solve for the variables in the following matrix equation.

Introduction to Determinants

MATH 152 Exam 1-Solutions 135 pts. Write your answers on separate paper. You do not need to copy the questions. Show your work!!!

MATH 260 LINEAR ALGEBRA EXAM II Fall 2013 Instructions: The use of built-in functions of your calculator, such as det( ) or RREF, is prohibited.

Chapter 3: Theory Review: Solutions Math 308 F Spring 2015

Math 4377/6308 Advanced Linear Algebra

Math 314H EXAM I. 1. (28 points) The row reduced echelon form of the augmented matrix for the system. is the matrix

Matrix Algebra & Elementary Matrices

Chapter 1: Systems of Linear Equations and Matrices

Transcription:

2.2 The Inverse of a Matrix Math 2331 Linear Algebra 2.2 The Inverse of a Matrix Shang-Huan Chiu Department of Mathematics, University of Houston schiu@math.uh.edu math.uh.edu/ schiu/ Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 1 / 16

2.2 The Inverse of a Matrix The Inverse of a Matrix: Definition The Inverse of a Matrix: Facts The Inverse of a 2-by-2 Matrix The Inverse of a Matrix: Solution of Linear System The Inverse of a Matrix: Theorem Elementary Matrix Multiplication by Elementary Matrices The Inverse of Elementary Matrix Examples Theorem Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 2 / 16

The Inverse of a Matrix: Definition The inverse of a real number a is denoted by a 1. For example, 7 1 = 1/7 and 7 7 1 = 7 1 7 = 1. The Inverse of a Matrix An n n matrix A is said to be invertible if there is an n n matrix C satisfying CA = AC = I n where I n is the n n identity matrix. We call C the inverse of A. Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 3 / 16

The Inverse of a Matrix: Facts Fact If A is invertible, then the inverse is unique. Proof: Assume B and C are both inverses of A. Then B = BI = B ( ) = ( ) = I = C. So the inverse is unique since any two inverses coincide. Notation The inverse of A is usually denoted by A 1. We have AA 1 = A 1 A = I n Not all n n matrices are invertible. A matrix which is not invertible is sometimes called a singular matrix. An invertible matrix is called nonsingular matrix. Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 4 / 16

The Inverse of a 2-by-2 Matrix Theorem [ a b Let A = c d ]. If ad bc 0, then A is invertible and A 1 = 1 ad bc If ad bc = 0, then A is not invertible. [ d b c a ]. Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 5 / 16

The Inverse of a Matrix: Solution of Linear System Theorem If A is an invertible n n matrix, then for each b in R n, the equation Ax = b has the unique solution x = A 1 b. Proof: Ax = b. Assume A is any invertible matrix and we wish to solve Then Ax = b and so I x = or x =. Suppose w is also a solution to Ax = b. Then Aw = b and Aw = b which means w =A 1 b. So, w =A 1 b, which is in fact the same solution. Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 6 / 16

Solution of Linear System Example Use the inverse of A = [ 7 3 5 2 ] to solve 7x 1 + 3x 2 = 2 5x 1 2x 2 = 1. Solution: Matrix form of the linear system: [ ] [ ] [ 7 3 x1 2 = 5 2 1 A 1 = 1 14 15 [ 2 3 x =A 1 b = 5 7 x 2 [ ] 2 3 = 5 7 ] [ 2 3 5 7 ]. ] [ ] [ ] = Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 7 / 16

The Inverse of a Matrix: Theorem Theorem Suppose A and B are invertible. a. A 1 is invertible and ( A 1) 1 = A (i.e. A is the inverse of A 1 ). b. AB is invertible and (AB) 1 = B 1 A 1 c. A T is invertible and ( A T ) 1 = ( A 1 ) T Partial proof of part b: Then the following results hold: (AB) ( B 1 A 1) = A ( ) A 1 = A ( ) A 1 = =. Similarly, one can show that ( B 1 A 1) (AB) = I. Part b of Theorem can be generalized to three or more invertible matrices: (ABC) 1 = Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 8 / 16

The Inverse of Elementary Matrix Earlier, we saw a formula for finding the inverse of a 2 2 invertible matrix. How do we find the inverse of an invertible n n matrix? To answer this question, we first look at elementary matrices. Elementary Matrices An elementary matrix is one that is obtained by performing a single elementary row operation on an identity matrix. Example Let E 1 = E 3 = 0 2 0 0 0 1 3 0 1, E 2 = and A = 0 0 1 a b c d e f g h i E 1, E 2, and E 3 are elementary matrices.,. Why? Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 9 / 16

Multiplication by Elementary Matrices Observe the following products and describe how these products can be obtained by elementary row operations on A. a b c a b c E 1 A = 0 2 0 d e f = 2d 2e 2f 0 0 1 g h i g h i E 2 A = E 3 A = 0 0 1 3 0 1 a b c d e f g h i a b c d e f g h i = = a b c g h i d e f a b c d e f 3a + g 3b + h 3c + i If an elementary row operation is performed on an m n matrix A, the resulting matrix can be written as EA, where the m m matrix E is created by performing the same row operations on I m. Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 10 / 16

The Inverses of Elementary Matrices: Example Elementary matrices are invertible because row operations are reversible. To determine the inverse of an elementary matrix E, determine the elementary row operation needed to transform E back into I and apply this operation to I to find the inverse. Example E 3 = 3 0 1 E 1 3 = Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 11 / 16

The Inverses of Elementary Matrices: Example Example Let A = E 1 A = 3 1 2 0 2. Then 0 2 0 0 0 1 E 2 (E 1 A) = 0 0 1 E 3 (E 2 E 1 A) = 3 1 2 0 2 = 3 0 1 3 0 1 3 0 1 3 0 1 = 3 0 1 = 0 0 1 Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 12 / 16

The Inverses of Elementary Matrices: Example (cont.) Example (cont.) So E 3 E 2 E 1 A = I 3. Then multiplying on the right by A 1, we get So E 3 E 2 E 1 A = I 3. E 3 E 2 E 1 I 3 = A 1 Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 13 / 16

The Inverses of Elementary Matrices: Theorem The elementary row operations that row reduce A to I n are the same elementary row operations that transform I n into A 1. Theorem An n n matrix A is invertible if and only if A is row equivalent to I n, and in this case, any sequence of elementary row operations that reduces A to I n will also transform I n to A 1. Algorithm for Finding A 1 Place A and I side-by-side to form an augmented matrix [A I ]. Then perform row operations on this matrix (which will produce identical operations on A and I ). So by Theorem: or A is not invertible. [A I ] will row reduce to [ I A 1] Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 14 / 16

The Inverses of Matrix: Example Example Find the inverse of A = Solution: [A I ] = 2 0 0 3 1 0 0 0 1 So A 1 = 1 2 0 0 0 0 1 3 2 1 0 2 0 0 3 0 1, if it exists. 1 2 0 0 0 0 1 0 0 1 3 2 1 0 Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 15 / 16

The Inverses of Matrix: Order Order of multiplication is important! Example Suppose A,B,C, and D are invertible n n matrices and A = B(D I n )C. Solve for D in terms of A, B, C and D. Solution: A = B(D I n )C D I n = B 1 AC 1 D I n + = B 1 AC 1 + D = Shang-Huan Chiu, University of Houston Math 2331, Linear Algebra Fall, 2017 16 / 16