MATH 2000 Gauss-Jordan Elimination and the TI-83 [Underlined bold terms are defined in the glossary]

Size: px
Start display at page:

Download "MATH 2000 Gauss-Jordan Elimination and the TI-83 [Underlined bold terms are defined in the glossary]"

Transcription

1 x y z MATH 000 Gauss-Jordan Elimination and the TI-3 [Underlined bold terms are defined in the glossary] 3z = A linear system such as x + 4y z = x + 5y z = can be solved algebraically using ordinary elimination or by using an augmented matrix and elementary row operations. When we write a matrix, we are using only the coefficients, so it is imperative that all equations be in standard form. An augmented matrix includes the constant terms also. The augmented matrix for this system is given below. In larger matrices where variables may get confused, we will put the appropriate variable at the top of each column as I have done here. In small systems this is not usually necessary. The vertical line indicates the location of the = signs. There are three elementary row operations that produce row-equivalent matrices Two rows are interchanged Ri Rj A row is replaced by a nonzero multiple of itself kri Ri A row is replaced by the sum of itself and a nonzero kr j + Ri Ri multiple of another row. (NOTE : means "replaces") You are responsible for performing all of these operations by hand, if asked, but you will be allowed to use your calculator most of the time. Make certain you know how to do all row operations on your calculator, or you will have to do all the computations by hand! The result of a row operation is displayed on the home screen, but it is not automatically stored (on a TI-3)! You should immediately store the result under a different name. It is convenient (and frequently useful) to store the results alphabetically. Row Swap: To interchange rows and 3 of matrix A: MATRIX MATH C:rowSwap( ENTER MATRIX NAMES :[A] ENTER,, 3 ) ENTER STO$ MATRIX NAMES :[B] ENTER You must write down which row operation you are using. Please put this notation beside the resulting row in the new matrix. Note the calculator command on each screen shot. The original matrix The matrix after swapping rows and R R 3 MATH Gauss-Jordan Elimination and the TI-3 ~ page J. Ahrens //005

2 Multiplying a row by a nonzero scalar: This operation automatically replaces the old row with the new one. To multiply row of matrix A by : 3 MATRIX MATH E:*row( ENTER 3, MATRIX NAMES :[A] ENTER, ) ENTER STO$ MATRIX NAMES 3:[C] ENTER The original matrix The matrix after multiplying row by R R 3 Adding a nonzero scalar multiple of one row to another row: Perform the multiplication first, then add that result to the second equation. Replace the second equation with the result. To multiply row of matrix A by and add it to row 3 MATRIX MATH F:*row+( ENTER, MATRIX NAMES :[A] ENTER,, 3 ) ENTER STO$ MATRIX NAMES 4:[D] ENTER The original matrix The matrix after multiplying row by and adding it to row R + R R 3 3 General directions for using Gauss-Jordan elimination: a) Write the system of equations as an augmented matrix b) Begin with the original matrix and use elementary row operations until the coefficient matrix becomes an identity matrix. c) List each row operation used to the left of the new matrix beside the new row. d) Store each result in your calculator (as a new matrix). e) Please work DOWN! 4x + y 4z = 4 Example: Solve this system of linear equations: 3x + 6y + 5z = 3 x + y + x = 7. Write the system as an augmented matrix and store it in your calculator as matrix [A] store as [A] MATH Gauss-Jordan Elimination and the TI-3 ~ page J. Ahrens //005

3 . Desired result: Change element a to. Row op: *row,[a], 4 R R store as [B] 3. Desired result: Change element a to 0 by using row. Row op: *row + ( 3,[B],,) 3R + R R store as [C] 4. Desired result: Change element a3 to 0 by using row Row op: *row + (,[C],,3) R + R3 R store as [D] 5. Desired result: Change a to This is not a typical problem! We would normally multiply row by the reciprocal of a. Since we must have a nonzero number in that location we will need to do a row swap. We do not want to swap rows and because we would then have a nonzero number for element a. Cardinal rule: Do not undo something you just worked hard to fix! Swapping rows and 3 is not a big deal, but it is unusual to have to do so at this point. Row op: rowswap([d],, 3] R R store as [E] Row op: *row,[e], 5 R R store as [F] Let s go off on a tangent for a few moments: A. If we multiply row 3 by, we will change element a 33 to. Row op: *row,[f],3 R 3 R B. Our matrix is now in row echelon form. We can solve using back substitution:. The third row means that z =!, i.e. z =! Back substitute into row : y + (!) =!3, so y = Back substitute into row : x + ()! (!) =, so x =!3 The solution is (!3,,!) Check by substituting result in all original equations. This method of solution is called Gaussian Elimination. MATH Gauss-Jordan Elimination and the TI-3 ~ page 3 J. Ahrens //005

4 Meanwhile, back to the original problem! 6. Desired result: Change element a to 0 using row Row op: *row + (,[F],,) R + R R save as [G] 7. Desired result: Change element a 33 to Row op: *row,[g],3 R 3 R save as [H]. Desired result: Change element a3 5R3 + R R to 0 using row save as [I] Row op: *row + (5,[H],3,) Desired result: Change element a3 to 0 using row 3 Row op: *row + (,[I],3,) R3 + R R The solution can now be read directly from the matrix: x =!3 y = z =!, in other words, (!3,,!) This method is called the Gauss-Jordan Elimination Method. Its algorithm is ideal for use with calculator and/or computer programs and is the basis for linear programming problems. Summary of the Gauss-Jordan Elimination Method: Get a " in position,. Then use row to get 0"s in the rest of column. Get a " in position,. Then use row to get 0"s in the rest of column. Get a " in position 3,3. Then use row 3 to get 0"s in the rest of column 3. You will be required to solve one problem on the test by showing the individual row operations as demonstrated above. You may use your calculator to do the actual calculations on each step. Study your owners manual to see if your calculator has a row reduced echelon form command. If so, it will save you a lot of time and effort! If not, practice until you can do the necessary steps quickly and accurately. On the TI-3, matrix A can be changed from augmented form to row reduced echelon form in one step using: MATRIX MATH B:rref( ENTER MATRIX NAMES :[A] ENTER! MATH Gauss-Jordan Elimination and the TI-3 ~ page 4 J. Ahrens //005

5 Not all linear systems have solutions The augmented matrix is Solve: x + 6x = 3 x + 3x = 3 The row reduced echelon form is The last row of the row reduced echelon form means that 0x + 0x = 7, i.e. 0 = 7. This system has no solution. Such a system is said to be inconsistent. Some linear systems have multiple solutions The augmented matrix is Solve x x = 4 6x + 3x = The row reduced echelon form is The last row of the row reduced echelon form means that 0x + 0x = 0, which is true regardless of the values of the variables. Since the bottom row is always true, we must determine when the first row is true. Introduce a parameter t, and let x = t. [t is a real number] Then x x = x = t + All solutions to this system have the form t, t t + R Examples of solutions are (, 0), (!,!6), and (4, 4). This is a consistent system. MATH Gauss-Jordan Elimination and the TI-3 ~ page 5 J. Ahrens //005

3. Replace any row by the sum of that row and a constant multiple of any other row.

3. Replace any row by the sum of that row and a constant multiple of any other row. Math Section. Section.: Solving Systems of Linear Equations Using Matrices As you may recall from College Algebra or Section., you can solve a system of linear equations in two variables easily by applying

More information

10/26/ Solving Systems of Linear Equations Using Matrices. Objectives. Matrices

10/26/ Solving Systems of Linear Equations Using Matrices. Objectives. Matrices 6.1 Solving Systems of Linear Equations Using Matrices Objectives Write the augmented matrix for a linear system. Perform matrix row operations. Use matrices and Gaussian elimination to solve systems.

More information

EXTENSION. a 1 b 1 c 1 d 1. Rows l a 2 b 2 c 2 d 2. a 3 x b 3 y c 3 z d 3. This system can be written in an abbreviated form as

EXTENSION. a 1 b 1 c 1 d 1. Rows l a 2 b 2 c 2 d 2. a 3 x b 3 y c 3 z d 3. This system can be written in an abbreviated form as EXTENSION Using Matrix Row Operations to Solve Systems The elimination method used to solve systems introduced in the previous section can be streamlined into a systematic method by using matrices (singular:

More information

For example, the system. 22 may be represented by the augmented matrix

For example, the system. 22 may be represented by the augmented matrix Matrix Solutions to Linear Systems A matrix is a rectangular array of elements. o An array is a systematic arrangement of numbers or symbols in rows and columns. Matrices (the plural of matrix) may be

More information

Solving Systems Using Row Operations 1 Name

Solving Systems Using Row Operations 1 Name The three usual methods of solving a system of equations are graphing, elimination, and substitution. While these methods are excellent, they can be difficult to use when dealing with three or more variables.

More information

2. Use elementary row operations to rewrite the augmented matrix in a simpler form (i.e., one whose solutions are easy to find).

2. Use elementary row operations to rewrite the augmented matrix in a simpler form (i.e., one whose solutions are easy to find). Section. Gaussian Elimination Our main focus in this section is on a detailed discussion of a method for solving systems of equations. In the last section, we saw that the general procedure for solving

More information

x = 12 x = 12 1x = 16

x = 12 x = 12 1x = 16 2.2 - The Inverse of a Matrix We've seen how to add matrices, multiply them by scalars, subtract them, and multiply one matrix by another. The question naturally arises: Can we divide one matrix by another?

More information

Section 3.1 Gaussian Elimination Method (GEM) Key terms

Section 3.1 Gaussian Elimination Method (GEM) Key terms Section 3.1 Gaussian Elimination Method (GEM) Key terms Rectangular systems Consistent system & Inconsistent systems Rank Types of solution sets RREF Upper triangular form & back substitution Nonsingular

More information

Basic Matrix Manipulation with a TI-89/TI-92/Voyage 200

Basic Matrix Manipulation with a TI-89/TI-92/Voyage 200 Basic Matrix Manipulation with a TI-89/TI-92/Voyage 200 Often, a matrix may be too large or too complex to manipulate by hand. For these types of matrices, we can employ the help of graphing calculators

More information

Solving Systems of Equations Using Matrices With the TI-83 or TI-84

Solving Systems of Equations Using Matrices With the TI-83 or TI-84 Solving Systems of Equations Using Matrices With the TI-83 or TI-84 Dimensions of a matrix: The dimensions of a matrix are the number of rows by the number of columns in the matrix. rows x columns *rows

More information

6.3 Notes O Brien F15

6.3 Notes O Brien F15 CA th ed HL. Notes O Brien F. Solution of Linear Systems by ow Transformations I. Introduction II. In this section we will solve systems of first degree equations which have two or more variables. We will

More information

MATH 423 Linear Algebra II Lecture 17: Reduced row echelon form (continued). Determinant of a matrix.

MATH 423 Linear Algebra II Lecture 17: Reduced row echelon form (continued). Determinant of a matrix. MATH 423 Linear Algebra II Lecture 17: Reduced row echelon form (continued). Determinant of a matrix. Row echelon form A matrix is said to be in the row echelon form if the leading entries shift to the

More information

Exercise Set Decide whether each matrix below is an elementary matrix. (a) (b) (c) (d) Answer:

Exercise Set Decide whether each matrix below is an elementary matrix. (a) (b) (c) (d) Answer: Understand the relationships between statements that are equivalent to the invertibility of a square matrix (Theorem 1.5.3). Use the inversion algorithm to find the inverse of an invertible matrix. Express

More information

Linear Equations in Linear Algebra

Linear Equations in Linear Algebra 1 Linear Equations in Linear Algebra 1.2 Row Reduction and Echelon Forms ECHELON FORM A rectangular matrix is in echelon form (or row echelon form) if it has the following three properties: 1. All nonzero

More information

Matrix Inverse 2 ( 2) 1 = 2 1 2

Matrix Inverse 2 ( 2) 1 = 2 1 2 Name: Matrix Inverse For Scalars, we have what is called a multiplicative identity. This means that if we have a scalar number, call it r, then r multiplied by the multiplicative identity equals r. Without

More information

A Poorly Conditioned System. Matrix Form

A Poorly Conditioned System. Matrix Form Possibilities for Linear Systems of Equations A Poorly Conditioned System A Poorly Conditioned System Results No solution (inconsistent) Unique solution (consistent) Infinite number of solutions (consistent)

More information

Chapter 2 Systems of Linear Equations and Matrices

Chapter 2 Systems of Linear Equations and Matrices Chapter 2 Systems of Linear Equations and Matrices LOCATION IN THE OTHER TEXTS: Finite Mathematics and Calculus with Applications: Chapter 2 Solution of Linear Systems by the Gauss-Jordan Method. Row Operations.

More information

6-2 Matrix Multiplication, Inverses and Determinants

6-2 Matrix Multiplication, Inverses and Determinants Find AB and BA, if possible. 4. A = B = A = ; B = A is a 2 1 matrix and B is a 1 4 matrix. Because the number of columns of A is equal to the number of rows of B, AB exists. To find the first entry of

More information

Matrices and Systems of Equations

Matrices and Systems of Equations 1 CA-Fall 2011-Jordan College Algebra, 4 th edition, Beecher/Penna/Bittinger, Pearson/Addison Wesley, 2012 Chapter 6: Systems of Equations and Matrices Section 6.3 Matrices and Systems of Equations Matrices

More information

Paul's Online Math Notes. Online Notes / Algebra (Notes) / Systems of Equations / Augmented Matricies

Paul's Online Math Notes. Online Notes / Algebra (Notes) / Systems of Equations / Augmented Matricies 1 of 8 5/17/2011 5:58 PM Paul's Online Math Notes Home Class Notes Extras/Reviews Cheat Sheets & Tables Downloads Algebra Home Preliminaries Chapters Solving Equations and Inequalities Graphing and Functions

More information

Column and row space of a matrix

Column and row space of a matrix Column and row space of a matrix Recall that we can consider matrices as concatenation of rows or columns. c c 2 c 3 A = r r 2 r 3 a a 2 a 3 a 2 a 22 a 23 a 3 a 32 a 33 The space spanned by columns of

More information

February 01, Matrix Row Operations 2016 ink.notebook. 6.6 Matrix Row Operations. Page 49 Page Row operations

February 01, Matrix Row Operations 2016 ink.notebook. 6.6 Matrix Row Operations. Page 49 Page Row operations 6.6 Matrix Row Operations 2016 ink.notebook Page 49 Page 50 6.6 Row operations (Solve Systems with Matrices) Lesson Objectives Page 51 Standards Lesson Notes Page 52 6.6 Matrix Row Operations Press the

More information

3.1 Solving Systems Using Tables and Graphs

3.1 Solving Systems Using Tables and Graphs Algebra 2 Chapter 3: Systems of Equations Mrs. Leahy 3.1 Solving Systems Using Tables and Graphs A solution to a system of linear equations is an that makes all of the equations. To solve a system of equations

More information

Maths for Signals and Systems Linear Algebra in Engineering. Some problems by Gilbert Strang

Maths for Signals and Systems Linear Algebra in Engineering. Some problems by Gilbert Strang Maths for Signals and Systems Linear Algebra in Engineering Some problems by Gilbert Strang Problems. Consider u, v, w to be non-zero vectors in R 7. These vectors span a vector space. What are the possible

More information

Math 355: Linear Algebra: Midterm 1 Colin Carroll June 25, 2011

Math 355: Linear Algebra: Midterm 1 Colin Carroll June 25, 2011 Rice University, Summer 20 Math 355: Linear Algebra: Midterm Colin Carroll June 25, 20 I have adhered to the Rice honor code in completing this test. Signature: Name: Date: Time: Please read the following

More information

January 24, Matrix Row Operations 2017 ink.notebook. 6.6 Matrix Row Operations. Page 35 Page Row operations

January 24, Matrix Row Operations 2017 ink.notebook. 6.6 Matrix Row Operations. Page 35 Page Row operations 6.6 Matrix Row Operations 2017 ink.notebook Page 35 Page 36 6.6 Row operations (Solve Systems with Matrices) Lesson Objectives Page 37 Standards Lesson Notes Page 38 6.6 Matrix Row Operations Press the

More information

Numerical Methods 5633

Numerical Methods 5633 Numerical Methods 5633 Lecture 7 Marina Krstic Marinkovic mmarina@maths.tcd.ie School of Mathematics Trinity College Dublin Marina Krstic Marinkovic 1 / 10 5633-Numerical Methods Organisational To appear

More information

Math 13 Chapter 3 Handout Helene Payne. Name: 1. Assign the value to the variables so that a matrix equality results.

Math 13 Chapter 3 Handout Helene Payne. Name: 1. Assign the value to the variables so that a matrix equality results. Matrices Name:. Assign the value to the variables so that a matrix equality results. [ [ t + 5 4 5 = 7 6 7 x 3. Are the following matrices equal, why or why not? [ 3 7, 7 4 3 4 3. Let the matrix A be defined

More information

CHAPTER 5 SYSTEMS OF EQUATIONS. x y

CHAPTER 5 SYSTEMS OF EQUATIONS. x y page 1 of Section 5.1 CHAPTER 5 SYSTEMS OF EQUATIONS SECTION 5.1 GAUSSIAN ELIMINATION matrix form of a system of equations The system 2x + 3y + 4z 1 5x + y + 7z 2 can be written as Ax where b 2 3 4 A [

More information

Matrices and Determinants

Matrices and Determinants pr8-78-88.i-hr /6/6 : PM Page 78 CHAPTER 8 Matrices and Determinants J ARON LANIER, WHO FIRST USED the term virtual reality, is chief scientist for the teleimmersion project, which explores the impact

More information

Add a multiple of a row to another row, replacing the row which was not multiplied.

Add a multiple of a row to another row, replacing the row which was not multiplied. Determinants Properties involving elementary row operations There are a few sections on properties. Rirst, we ll simply state collections of properties, provide some examples, and talk about why they are

More information

CHAPTER HERE S WHERE YOU LL FIND THESE APPLICATIONS:

CHAPTER HERE S WHERE YOU LL FIND THESE APPLICATIONS: CHAPTER 8 You are being drawn deeper into cyberspace, spending more time online each week. With constantly improving high-resolution images, cyberspace is reshaping your life by nourishing shared enthusiasms.

More information

Self-study session 1, Discrete mathematics

Self-study session 1, Discrete mathematics Self-study session 1, Discrete mathematics First year mathematics for the technology and science programmes Aalborg University In this self-study session we are working with time complexity. Space complexity

More information

0_PreCNotes17 18.notebook May 16, Chapter 12

0_PreCNotes17 18.notebook May 16, Chapter 12 Chapter 12 Notes BASIC MATRIX OPERATIONS Matrix (plural: Matrices) an n x m array of elements element a ij Example 1 a 21 = a 13 = Multiply Matrix by a Scalar Distribute scalar to all elements Addition

More information

Precalculus Notes: Unit 7 Systems of Equations and Matrices

Precalculus Notes: Unit 7 Systems of Equations and Matrices Date: 7.1, 7. Solving Systems of Equations: Graphing, Substitution, Elimination Syllabus Objectives: 8.1 The student will solve a given system of equations or system of inequalities. Solution of a System

More information

Linear Equation Systems Iterative Methods

Linear Equation Systems Iterative Methods Linear Equation Systems Iterative Methods Content Iterative Methods Jacobi Iterative Method Gauss Seidel Iterative Method Iterative Methods Iterative methods are those that produce a sequence of successive

More information

Curriculum Map: Mathematics

Curriculum Map: Mathematics Curriculum Map: Mathematics Course: Honors Advanced Precalculus and Trigonometry Grade(s): 11-12 Unit 1: Functions and Their Graphs This chapter will develop a more complete, thorough understanding of

More information

Independent systems consist of x

Independent systems consist of x 5.1 Simultaneous Linear Equations In consistent equations, *Find the solution to each system by graphing. 1. y Independent systems consist of x Three Cases: A. consistent and independent 2. y B. inconsistent

More information

Math 1B03/1ZC3 - Tutorial 3. Jan. 24th/28th, 2014

Math 1B03/1ZC3 - Tutorial 3. Jan. 24th/28th, 2014 Math 1B03/1ZC3 - Tutorial 3 Jan. 24th/28th, 2014 Tutorial Info: Website: http://ms.mcmaster.ca/ dedieula. Math Help Centre: Wednesdays 2:30-5:30pm. Email: dedieula@math.mcmaster.ca. Elementary Matrices

More information

Ahigh school curriculum in Algebra 2 contains both solving systems of linear equations,

Ahigh school curriculum in Algebra 2 contains both solving systems of linear equations, The Simplex Method for Systems of Linear Inequalities Todd O. Moyer, Towson University Abstract: This article details the application of the Simplex Method for an Algebra 2 class. Students typically learn

More information

Performing Matrix Operations on the TI-83/84

Performing Matrix Operations on the TI-83/84 Page1 Performing Matrix Operations on the TI-83/84 While the layout of most TI-83/84 models are basically the same, of the things that can be different, one of those is the location of the Matrix key.

More information

Classroom Tips and Techniques: Stepwise Solutions in Maple - Part 2 - Linear Algebra

Classroom Tips and Techniques: Stepwise Solutions in Maple - Part 2 - Linear Algebra Introduction Classroom Tips and Techniques: Stepwise Solutions in Maple - Part 2 - Linear Algebra Robert J. Lopez Emeritus Professor of Mathematics and Maple Fellow Maplesoft In the preceding article Stepwise

More information

hp calculators hp 39g+ & hp 39g/40g Using Matrices How are matrices stored? How do I solve a system of equations? Quick and easy roots of a polynomial

hp calculators hp 39g+ & hp 39g/40g Using Matrices How are matrices stored? How do I solve a system of equations? Quick and easy roots of a polynomial hp calculators hp 39g+ Using Matrices Using Matrices The purpose of this section of the tutorial is to cover the essentials of matrix manipulation, particularly in solving simultaneous equations. How are

More information

Solving Algebraic Equations

Solving Algebraic Equations Lesson 4. Solving Algebraic Equations 3 3 3 3 3 8 8 4 Add 3 to both sides. Divide both sides by. 4 gives the solution of the equation 3. Check: Substitute 4 for x into the original equation. 3 4 3 When

More information

SCIE 4101, Spring Math Review Packet #4 Algebra II (Part 1) Notes

SCIE 4101, Spring Math Review Packet #4 Algebra II (Part 1) Notes SCIE 4101, Spring 011 Miller Math Review Packet #4 Algebra II (Part 1) Notes Matrices A matrix is a rectangular arra of numbers. The order of a matrix refers to the number of rows and columns the matrix

More information

Put the following equations to slope-intercept form then use 2 points to graph

Put the following equations to slope-intercept form then use 2 points to graph Tuesday September 23, 2014 Warm-up: Put the following equations to slope-intercept form then use 2 points to graph 1. 4x - 3y = 8 8 x 6y = 16 2. 2x + y = 4 2x + y = 1 Tuesday September 23, 2014 Warm-up:

More information

A Study of Numerical Methods for Simultaneous Equations

A Study of Numerical Methods for Simultaneous Equations A Study of Numerical Methods for Simultaneous Equations Er. Chandan Krishna Mukherjee B.Sc.Engg., ME, MBA Asstt. Prof. ( Mechanical ), SSBT s College of Engg. & Tech., Jalgaon, Maharashtra Abstract: -

More information

Recreational Mathematics:

Recreational Mathematics: Recreational Mathematics: SOLVING LIGHTS OUT BY: ALI THOMAS Lights Out An Introduction: 5 x 5 array of lights Object of the game: Turn off all of the lights in the fewest amount of moves given lights that

More information

Numerical Linear Algebra

Numerical Linear Algebra Numerical Linear Algebra Probably the simplest kind of problem. Occurs in many contexts, often as part of larger problem. Symbolic manipulation packages can do linear algebra "analytically" (e.g. Mathematica,

More information

4. Linear Algebra. In maple, it is first necessary to call in the linear algebra package. This is done by the following maple command

4. Linear Algebra. In maple, it is first necessary to call in the linear algebra package. This is done by the following maple command 4. Linear Algebra Vectors and Matrices Maple has this wonderful linear algebra package. It has to do with vectors and matrices. A vector is simply an array of numbers written as () where a matrix is written

More information

REGULAR GRAPHS OF GIVEN GIRTH. Contents

REGULAR GRAPHS OF GIVEN GIRTH. Contents REGULAR GRAPHS OF GIVEN GIRTH BROOKE ULLERY Contents 1. Introduction This paper gives an introduction to the area of graph theory dealing with properties of regular graphs of given girth. A large portion

More information

Objectives and Homework List

Objectives and Homework List MAC 1140 Objectives and Homework List Each objective covered in MAC1140 is listed below. Along with each objective is the homework list used with MyMathLab (MML) and a list to use with the text (if you

More information

Computational Methods CMSC/AMSC/MAPL 460. Vectors, Matrices, Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science

Computational Methods CMSC/AMSC/MAPL 460. Vectors, Matrices, Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science Computational Methods CMSC/AMSC/MAPL 460 Vectors, Matrices, Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science Zero elements of first column below 1 st row multiplying 1 st

More information

Matrices and Systems of Linear Equations

Matrices and Systems of Linear Equations Chapter The variable x has now been eliminated from the first and third equations. Next, we eliminate x3 from the first and second equations and leave x3, with coefficient, in the third equation: System:

More information

DM545 Linear and Integer Programming. Lecture 2. The Simplex Method. Marco Chiarandini

DM545 Linear and Integer Programming. Lecture 2. The Simplex Method. Marco Chiarandini DM545 Linear and Integer Programming Lecture 2 The Marco Chiarandini Department of Mathematics & Computer Science University of Southern Denmark Outline 1. 2. 3. 4. Standard Form Basic Feasible Solutions

More information

LARP / 2018 ACK : 1. Linear Algebra and Its Applications - Gilbert Strang 2. Autar Kaw, Transforming Numerical Methods Education for STEM Graduates

LARP / 2018 ACK : 1. Linear Algebra and Its Applications - Gilbert Strang 2. Autar Kaw, Transforming Numerical Methods Education for STEM Graduates Triangular Factors and Row Exchanges LARP / 28 ACK :. Linear Algebra and Its Applications - Gilbert Strang 2. Autar Kaw, Transforming Numerical Methods Education for STEM Graduates Then there were three

More information

Introduction: Equipment: Getting Started Collecting the data:

Introduction: Equipment: Getting Started Collecting the data: Introduction: Collecting Ball Bounce data. Many aspects relating to the motion of a bouncing ball can be modelled mathematically. The first stage in modelling the motion is to collect some data. The Calculator

More information

5 The Theory of the Simplex Method

5 The Theory of the Simplex Method 5 The Theory of the Simplex Method Chapter 4 introduced the basic mechanics of the simplex method. Now we shall delve a little more deeply into this algorithm by examining some of its underlying theory.

More information

Math 2331 Linear Algebra

Math 2331 Linear Algebra 4.2 Null Spaces, Column Spaces, & Linear Transformations Math 233 Linear Algebra 4.2 Null Spaces, Column Spaces, & Linear Transformations Jiwen He Department of Mathematics, University of Houston jiwenhe@math.uh.edu

More information

Algorithms and Data Structures

Algorithms and Data Structures Charles A. Wuethrich Bauhaus-University Weimar - CogVis/MMC June 22, 2017 1/51 Introduction Matrix based Transitive hull All shortest paths Gaussian elimination Random numbers Interpolation and Approximation

More information

Problem 2. Problem 3. Perform, if possible, each matrix-vector multiplication. Answer. 3. Not defined. Solve this matrix equation.

Problem 2. Problem 3. Perform, if possible, each matrix-vector multiplication. Answer. 3. Not defined. Solve this matrix equation. Problem 2 Perform, if possible, each matrix-vector multiplication. 1. 2. 3. 1. 2. 3. Not defined. Problem 3 Solve this matrix equation. Matrix-vector multiplication gives rise to a linear system. Gaussian

More information

CS Elementary Graph Algorithms & Transform-and-Conquer

CS Elementary Graph Algorithms & Transform-and-Conquer CS483-10 Elementary Graph Algorithms & Transform-and-Conquer Outline Instructor: Fei Li Room 443 ST II Office hours: Tue. & Thur. 1:30pm - 2:30pm or by appointments Depth-first Search cont Topological

More information

Systems of Inequalities and Linear Programming 5.7 Properties of Matrices 5.8 Matrix Inverses

Systems of Inequalities and Linear Programming 5.7 Properties of Matrices 5.8 Matrix Inverses 5 5 Systems and Matrices Systems and Matrices 5.6 Systems of Inequalities and Linear Programming 5.7 Properties of Matrices 5.8 Matrix Inverses Sections 5.6 5.8 2008 Pearson Addison-Wesley. All rights

More information

MAT 103 F09 TEST 3 REVIEW (CH 4-5)

MAT 103 F09 TEST 3 REVIEW (CH 4-5) MAT 103 F09 TEST 3 REVIEW (CH 4-5) NAME For # 1-3, solve the system of equations by graphing. Label the equation of each line on your graph and write the solution as an ordered pair. Be sure to CHECK your

More information

How to Solve a Standard Maximization Problem Using the Simplex Method and the Rowops Program

How to Solve a Standard Maximization Problem Using the Simplex Method and the Rowops Program How to Solve a Standard Maximization Problem Using the Simplex Method and the Rowops Program Problem: Maximize z = x + 0x subject to x + x 6 x + x 00 with x 0 y 0 I. Setting Up the Problem. Rewrite each

More information

CS6015 / LARP ACK : Linear Algebra and Its Applications - Gilbert Strang

CS6015 / LARP ACK : Linear Algebra and Its Applications - Gilbert Strang Solving and CS6015 / LARP 2018 ACK : Linear Algebra and Its Applications - Gilbert Strang Introduction Chapter 1 concentrated on square invertible matrices. There was one solution to Ax = b and it was

More information

MA 162: Finite Mathematics - Sections 2.6

MA 162: Finite Mathematics - Sections 2.6 MA 162: Finite Mathematics - Sections 2.6 Fall 2014 Ray Kremer University of Kentucky September 24, 2014 Announcements: Homework 2.6 due next Tuesday at 6pm. Multiplicative Inverses If a is a non-zero

More information

Computational Methods CMSC/AMSC/MAPL 460. Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science

Computational Methods CMSC/AMSC/MAPL 460. Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science Computational Methods CMSC/AMSC/MAPL 460 Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science Matrix norms Can be defined using corresponding vector norms Two norm One norm Infinity

More information

Linear programming II João Carlos Lourenço

Linear programming II João Carlos Lourenço Decision Support Models Linear programming II João Carlos Lourenço joao.lourenco@ist.utl.pt Academic year 2012/2013 Readings: Hillier, F.S., Lieberman, G.J., 2010. Introduction to Operations Research,

More information

Coefficient Constant Equivalent expressions Equation. 3 A mathematical sentence containing an equal sign

Coefficient Constant Equivalent expressions Equation. 3 A mathematical sentence containing an equal sign 8.4.0 Lesson Date Algebra Vocabulary and Generating Equivalent s Student Objectives I can identify how many terms an expression has and what the coefficients, constants, and like terms of that expression

More information

Unit 3: Multiplication and Division Reference Guide pages x 7 = 392 factors: 56, 7 product 392

Unit 3: Multiplication and Division Reference Guide pages x 7 = 392 factors: 56, 7 product 392 Lesson 1: Multiplying Integers and Decimals, part 1 factor: any two or more numbers multiplied to form a product 56 x 7 = 392 factors: 56, 7 product 392 Integers: all positive and negative whole numbers

More information

Mastery. PRECALCULUS Student Learning Targets

Mastery. PRECALCULUS Student Learning Targets PRECALCULUS Student Learning Targets Big Idea: Sequences and Series 1. I can describe a sequence as a function where the domain is the set of natural numbers. Connections (Pictures, Vocabulary, Definitions,

More information

Working with Algebraic Expressions

Working with Algebraic Expressions 2 Working with Algebraic Expressions This chapter contains 25 algebraic expressions; each can contain up to five variables. Remember that a variable is just a letter that represents a number in a mathematical

More information

Practice Test - Chapter 6

Practice Test - Chapter 6 1. Write each system of equations in triangular form using Gaussian elimination. Then solve the system. Align the variables on the left side of the equal sign. Eliminate the x-term from the 2nd equation.

More information

Matrices for the TI-73

Matrices for the TI-73 TI Matrices for the TI-73 Getting Started Start here How To Find Installation Instructions Move Between Matrix Application Screens View and Edit a Matrix Use Matrices with Expressions Display and Copy

More information

Output: For each size provided as input, a figure of that size is to appear, followed by a blank line.

Output: For each size provided as input, a figure of that size is to appear, followed by a blank line. Problem 1: Divisor Differences Develop a program that, given integers m and k satisfying m > k > 0, lists every pair of positive integers (i,j) such that j i = k and both i and j are divisors of m. Input:

More information

Monday, 12 November 12. Matrices

Monday, 12 November 12. Matrices Matrices Matrices Matrices are convenient way of storing multiple quantities or functions They are stored in a table like structure where each element will contain a numeric value that can be the result

More information

,!7IA3C1-cjfcei!:t;K;k;K;k ISBN Graphing Calculator Reference Card. Addison-Wesley s. Basics. Created in conjuction with

,!7IA3C1-cjfcei!:t;K;k;K;k ISBN Graphing Calculator Reference Card. Addison-Wesley s. Basics. Created in conjuction with Addison-Wesley s Graphing Calculator Reference Card Created in conjuction with Basics Converting Fractions to Decimals The calculator will automatically convert a fraction to a decimal. Type in a fraction,

More information

A MATRIX FORMULATION OF THE CUBIC BÉZIER CURVE

A MATRIX FORMULATION OF THE CUBIC BÉZIER CURVE Geometric Modeling Notes A MATRIX FORMULATION OF THE CUBIC BÉZIER CURVE Kenneth I. Joy Institute for Data Analysis and Visualization Department of Computer Science University of California, Davis Overview

More information

Linear Block Codes. Allen B. MacKenzie Notes for February 4, 9, & 11, Some Definitions

Linear Block Codes. Allen B. MacKenzie Notes for February 4, 9, & 11, Some Definitions Linear Block Codes Allen B. MacKenzie Notes for February 4, 9, & 11, 2015 This handout covers our in-class study of Chapter 3 of your textbook. We ll introduce some notation and then discuss the generator

More information

Computational Methods CMSC/AMSC/MAPL 460. Vectors, Matrices, Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science

Computational Methods CMSC/AMSC/MAPL 460. Vectors, Matrices, Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science Computational Methods CMSC/AMSC/MAPL 460 Vectors, Matrices, Linear Systems, LU Decomposition, Ramani Duraiswami, Dept. of Computer Science Some special matrices Matlab code How many operations and memory

More information

Chapter 1: Foundations for Algebra

Chapter 1: Foundations for Algebra Chapter 1: Foundations for Algebra Dear Family, The student will follow the order of operations, a set of rules that standardize how to simplify expressions. Order of Operations 1. Perform operations within

More information

1.1 calculator viewing window find roots in your calculator 1.2 functions find domain and range (from a graph) may need to review interval notation

1.1 calculator viewing window find roots in your calculator 1.2 functions find domain and range (from a graph) may need to review interval notation 1.1 calculator viewing window find roots in your calculator 1.2 functions find domain and range (from a graph) may need to review interval notation functions vertical line test function notation evaluate

More information

LINPACK Benchmark. on the Fujitsu AP The LINPACK Benchmark. Assumptions. A popular benchmark for floating-point performance. Richard P.

LINPACK Benchmark. on the Fujitsu AP The LINPACK Benchmark. Assumptions. A popular benchmark for floating-point performance. Richard P. 1 2 The LINPACK Benchmark on the Fujitsu AP 1000 Richard P. Brent Computer Sciences Laboratory The LINPACK Benchmark A popular benchmark for floating-point performance. Involves the solution of a nonsingular

More information

Computer Packet 1 Row Operations + Freemat

Computer Packet 1 Row Operations + Freemat Computer Packet 1 Row Operations + Freemat For this packet, you will use a website to do row operations, and then learn to use a general purpose matrix calculator called FreeMat. To reach the row operations

More information

Optimization of Design. Lecturer:Dung-An Wang Lecture 8

Optimization of Design. Lecturer:Dung-An Wang Lecture 8 Optimization of Design Lecturer:Dung-An Wang Lecture 8 Lecture outline Reading: Ch8 of text Today s lecture 2 8.1 LINEAR FUNCTIONS Cost Function Constraints 3 8.2 The standard LP problem Only equality

More information

Matlab and Matrices. Math 45 Linear Algebra. David Arnold

Matlab and Matrices. Math 45 Linear Algebra. David Arnold Matlab and Matrices Math 45 Linear Algebra David Arnold David-Arnold@Eureka.redwoods.cc.ca.us Abstract In this exercise you will learn how to enter and edit matrices in Matlab. You will also experiment

More information

MAT 343 Laboratory 2 Solving systems in MATLAB and simple programming

MAT 343 Laboratory 2 Solving systems in MATLAB and simple programming MAT 343 Laboratory 2 Solving systems in MATLAB and simple programming In this laboratory session we will learn how to 1. Solve linear systems with MATLAB 2. Create M-files with simple MATLAB codes Backslash

More information

Cryptography. What is Cryptography?

Cryptography. What is Cryptography? Cryptography What is Cryptography? Cryptography is the discipline of encoding and decoding messages. It has been employed in various forms for thousands of years, and, whether or not you know it, is used

More information

LAB 2: Linear Equations and Matrix Algebra. Preliminaries

LAB 2: Linear Equations and Matrix Algebra. Preliminaries Math 250C, Section C2 Hard copy submission Matlab # 2 1 Revised 07/13/2016 LAB 2: Linear Equations and Matrix Algebra In this lab you will use Matlab to study the following topics: Solving a system of

More information

Chapter 1: Number and Operations

Chapter 1: Number and Operations Chapter 1: Number and Operations 1.1 Order of operations When simplifying algebraic expressions we use the following order: 1. Perform operations within a parenthesis. 2. Evaluate exponents. 3. Multiply

More information

Therefore, after becoming familiar with the Matrix Method, you will be able to solve a system of two linear equations in four different ways.

Therefore, after becoming familiar with the Matrix Method, you will be able to solve a system of two linear equations in four different ways. Grade 9 IGCSE A1: Chapter 9 Matrices and Transformations Materials Needed: Straightedge, Graph Paper Exercise 1: Matrix Operations Matrices are used in Linear Algebra to solve systems of linear equations.

More information

9 abcd = dcba b + 90c = c + 10b b = 10c.

9 abcd = dcba b + 90c = c + 10b b = 10c. In this session, we ll learn how to solve problems related to place value. This is one of the fundamental concepts in arithmetic, something every elementary and middle school mathematics teacher should

More information

Parallelizing LU Factorization

Parallelizing LU Factorization Parallelizing LU Factorization Scott Ricketts December 3, 2006 Abstract Systems of linear equations can be represented by matrix equations of the form A x = b LU Factorization is a method for solving systems

More information

MATH (CRN 13695) Lab 1: Basics for Linear Algebra and Matlab

MATH (CRN 13695) Lab 1: Basics for Linear Algebra and Matlab MATH 495.3 (CRN 13695) Lab 1: Basics for Linear Algebra and Matlab Below is a screen similar to what you should see when you open Matlab. The command window is the large box to the right containing the

More information

Multiplying and Dividing Rational Expressions

Multiplying and Dividing Rational Expressions Multiplying and Dividing Rational Expressions Warm Up Simplify each expression. Assume all variables are nonzero. 1. x 5 x 2 3. x 6 x 2 x 7 Factor each expression. 2. y 3 y 3 y 6 x 4 4. y 2 1 y 5 y 3 5.

More information

Introduction to Operations Research Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras

Introduction to Operations Research Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras Introduction to Operations Research Prof. G. Srinivasan Department of Management Studies Indian Institute of Technology, Madras Module - 05 Lecture - 24 Solving LPs with mixed type of constraints In the

More information

Geometric transformations assign a point to a point, so it is a point valued function of points. Geometric transformation may destroy the equation

Geometric transformations assign a point to a point, so it is a point valued function of points. Geometric transformation may destroy the equation Geometric transformations assign a point to a point, so it is a point valued function of points. Geometric transformation may destroy the equation and the type of an object. Even simple scaling turns a

More information

Exploration Assignment #1. (Linear Systems)

Exploration Assignment #1. (Linear Systems) Math 0280 Introduction to Matrices and Linear Algebra Exploration Assignment #1 (Linear Systems) Acknowledgment The MATLAB assignments for Math 0280 were developed by Jonathan Rubin with the help of Matthew

More information

Lesson 11: Duality in linear programming

Lesson 11: Duality in linear programming Unit 1 Lesson 11: Duality in linear programming Learning objectives: Introduction to dual programming. Formulation of Dual Problem. Introduction For every LP formulation there exists another unique linear

More information