© 2005 Baylor University Slide 1 Fundamentals of Engineering Analysis EGR 1302 - Adjoint Matrix and Inverse Solutions, Cramer’s Rule.

Slides:



Advertisements
Similar presentations
BAI CM20144 Applications I: Mathematics for Applications Mark Wood
Advertisements

Elementary Linear Algebra Anton & Rorres, 9th Edition
5.4. Additional properties Cofactor, Adjoint matrix, Invertible matrix, Cramers rule. (Cayley, Sylvester….)
3.2 Determinants; Mtx Inverses
© 2005 Baylor University Slide 1 Fundamentals of Engineering Analysis EGR 1302 Unit 1, Lecture C Approximate Running Time - 14 minutes Distance Learning.
Chap. 3 Determinants 3.1 The Determinants of a Matrix
Systems of Linear Equations
Economics 2301 Matrices Lecture 13.
Matrices and Determinants
Chapter 5 Determinants.
Copyright © Cengage Learning. All rights reserved. 7.6 The Inverse of a Square Matrix.
© 2005 Baylor University Slide 1 Fundamentals of Engineering Analysis EGR Determinants Approximate Running Time - 22 minutes Distance Learning /
© 2005 Baylor University Slide 1 Fundamentals of Engineering Analysis EGR 1302 Unit 1, Lecture F Approximate Running Time - 24 minutes Distance Learning.
EGR 1101 Unit 7 Systems of Linear Equations in Engineering (Chapter 7 of Rattan/Klingbeil text)
Gabriel Cramer was a Swiss mathematician ( )
Cramer's Rule Gabriel Cramer was a Swiss mathematician ( )
Spring 2013 Solving a System of Linear Equations Matrix inverse Simultaneous equations Cramer’s rule Second-order Conditions Lecture 7.
 Row and Reduced Row Echelon  Elementary Matrices.
Matrix Inversion.
Chapter 2 Determinants. The Determinant Function –The 2  2 matrix is invertible if ad-bc  0. The expression ad- bc occurs so frequently that it has.
Systems of Linear Equations Let’s say you need to solve the following for x, y, & z: 2x + y – 2z = 10 3x + 2y + 2z = 1 5x + 4y + 3z = 4 Two methods –Gaussian.
CHAPTER 2 MATRIX. CHAPTER OUTLINE 2.1 Introduction 2.2 Types of Matrices 2.3 Determinants 2.4 The Inverse of a Square Matrix 2.5 Types of Solutions to.
ENM 503 Block 2 Lesson 7 – Matrix Methods
Matrices & Determinants Chapter: 1 Matrices & Determinants.
1 © 2010 Pearson Education, Inc. All rights reserved © 2010 Pearson Education, Inc. All rights reserved Chapter 9 Matrices and Determinants.
WEEK 8 SYSTEMS OF EQUATIONS DETERMINANTS AND CRAMER’S RULE.
1 Ch. 4 Linear Models & Matrix Algebra Matrix algebra can be used: a. To express the system of equations in a compact manner. b. To find out whether solution.
1 MAC 2103 Module 3 Determinants. 2 Rev.F09 Learning Objectives Upon completing this module, you should be able to: 1. Determine the minor, cofactor,
Elementary Linear Algebra Anton & Rorres, 9 th Edition Lecture Set – 02 Chapter 2: Determinants.
Chapter 3 Determinants Linear Algebra. Ch03_2 3.1 Introduction to Determinants Definition The determinant of a 2  2 matrix A is denoted |A| and is given.
© 2005 Baylor University Slide 1 Fundamentals of Engineering Analysis EGR 1302 Unit 1, Lecture E Approximate Running Time - 7 minutes Distance Learning.
Fundamentals of Engineering Analysis
3.6 Solving Systems Using Matrices You can use a matrix to represent and solve a system of equations without writing the variables. A matrix is a rectangular.
Sec 3.6 Determinants 2x2 matrix Evaluate the determinant of.
Introduction and Definitions
4.7 Solving Systems using Matrix Equations and Inverses
Copyright © 2007 Pearson Education, Inc. Slide 7-1.
Chapter 2 Determinants. With each square matrix it is possible to associate a real number called the determinant of the matrix. The value of this number.
5.4 Third Order Determinants and Cramer’s Rule. Third Order Determinants To solve a linear system in three variables, we can use third order determinants.
System of Linear Equations with Unique Solution Budi Murtiyasa Universitas Muhammadiyah Surakarta 1budi murtiyasa / linear equation.
4-8 Cramer’s Rule We can solve a system of linear equations that has a unique solution by using determinants and a pattern called Cramer’s Rule (named.
BELL-WORK Solve the system of equations using matrices:
STROUD Worked examples and exercises are in the text Programme 5: Matrices MATRICES PROGRAMME 5.
LEARNING OUTCOMES At the end of this topic, student should be able to :  D efination of matrix  Identify the different types of matrices such as rectangular,
Section 2.1 Determinants by Cofactor Expansion. THE DETERMINANT Recall from algebra, that the function f (x) = x 2 is a function from the real numbers.
Notes Over 4.3 Evaluate Determinants of 2 x 2 Matrices
STROUD Worked examples and exercises are in the text PROGRAMME 5 MATRICES.
TYPES OF SOLUTIONS SOLVING EQUATIONS
Cramer’s Rule (because Cramer RULES!)
Sec 3.6 Determinants 2x2 matrix Evaluate the determinant of.
MAT 322: LINEAR ALGEBRA.
TYPES OF SOLUTIONS SOLVING EQUATIONS
LINEAR ALGEBRA.
Chapter 2 Determinants by Cofactor Expansion
Using Determinants to solve systems of equations
DETERMINANT MATRIX YULVI ZAIKA.
Using Matrices to Solve Systems of Equations
Chapter 2 Determinants Basil Hamed
Use Inverse Matrices to Solve 2 Variable Linear Systems
Students will write a summary explaining how to use Cramer’s rule.
Fundamentals of Engineering Analysis
Method 1: Substitution methods
Cramer's Rule Gabriel Cramer was a Swiss mathematician ( )
College Algebra Chapter 6 Matrices and Determinants and Applications
Chapter 2 Determinants.
Cramer's Rule Gabriel Cramer was a Swiss mathematician ( )
Chapter 2 Determinants.
Chapter 2 Determinants.
Matrices - Operations ADJOINT MATRICES
Presentation transcript:

© 2005 Baylor University Slide 1 Fundamentals of Engineering Analysis EGR Adjoint Matrix and Inverse Solutions, Cramer’s Rule

© 2005 Baylor University Slide 2 The Adjoint Matrix and the Inverse Matrix Recall the Rules for the Inverse of a 2x2: 1.Swap Main Diagonal 2.Change sign of a 12, a 21 3.Divide by determinant If the Cofactor Matrix is “transposed”, we get the same matrix as the Inverse And we define the “Adjoint” as the “Transposed Matrix of Cofactors”. And we see that the Inverse is defined as

© 2005 Baylor University Slide 3 Calculating the Adjoint Matrix and A detA Problem 7.13 in the Text adjA =

© 2005 Baylor University Slide 4 Complexity of Large Matrices Consider the 5x5 matrix, S To find the Adjoint of S (in order to find the inverse), would require Finding the determinants of 25 4x4s, which means Finding the determinants of 25*16 = 400 3x3s, which means Finding the determinants of 400*9 = x2s. (Wow!) Which is why we use computers (and explains why so many problems could not be solved before the advent of computers).

© 2005 Baylor University Slide 5 Class Exercise: Find the Adjoint of A Work this out yourself before going to the solution on the next slide

© 2005 Baylor University Slide 6 Class Exercise: Solution Notice that: detA = 0, therefore matrix A is singular. However, even though the Determinant is zero, the Adjoint still exists. This means that the Inverse does not exist.

© 2005 Baylor University Slide 7 Cramer’s Rule In many instances of complex problems, we may only need a partial solution. As we have seen, calculating an inverse takes a lot of computing power. However, calculating the determinant is much more manageable. Before the days of electronic computers, mathematician Gabriel Cramer devise a shortcut to the solution of linear systems. It also gives an explicit expression for the solution of the system Gabriel Cramer ( ).

© 2005 Baylor University Slide 8 solved as = Solving Systems of Linear Equations given a system becomes by row expansion etc. which is the same form as: for, replace in Col 1. where

© 2005 Baylor University Slide 9 Solution by Cramer’s Rule Replace Col. 3 for Replace Col. 1 for Replace Col. 2 for Cramer’s Rule is only valid for Unique Solutions. If detA = 0, Cramer’s Rule fails! Cramer’s Rule: Replace in the column # of the unknown variable you wish to find and solve for the “Ratio of Determinants”.

© 2005 Baylor University Slide 10 Solve a System of Equations with Cramer’s Rule the system of equations in matrix form is - Remember: “ratio of determinants”

© 2005 Baylor University Slide 11 Questions?