Chapter 1 Section 1.2 Echelon Form and Gauss-Jordan Elimination.

Slides:



Advertisements
Similar presentations
§ 3.4 Matrix Solutions to Linear Systems.
Advertisements

4.3 Matrix Approach to Solving Linear Systems 1 Linear systems were solved using substitution and elimination in the two previous section. This section.
Chapter 4 Systems of Linear Equations; Matrices Section 2 Systems of Linear Equations and Augmented Matrics.
1 Copyright © 2015, 2011, 2007 Pearson Education, Inc. Chapter 4-1 Systems of Equations and Inequalities Chapter 4.
Matrices & Systems of Linear Equations
1.2 Row Reduction and Echelon Forms
Lesson 8 Gauss Jordan Elimination
Matrices. Special Matrices Matrix Addition and Subtraction Example.
Chapter 1 Systems of Linear Equations
Row Reduction and Echelon Forms (9/9/05) A matrix is in echelon form if: All nonzero rows are above any all-zero rows. Each leading entry of a row is in.
LIAL HORNSBY SCHNEIDER
Lesson 8.1, page 782 Matrix Solutions to Linear Systems
Section 8.1 – Systems of Linear Equations
HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2011 Hawkes Learning Systems. All rights reserved. Hawkes Learning Systems College Algebra.
Systems of linear equations. Simple system Solution.
Linear Algebra – Linear Equations
Multivariate Linear Systems and Row Operations.
Matrix Solution of Linear Systems The Gauss-Jordan Method Special Systems.
Systems of Linear Equations and Row Echelon Form.
SYSTEMS OF LINEAR EQUATIONS
1 1.1 © 2012 Pearson Education, Inc. Linear Equations in Linear Algebra SYSTEMS OF LINEAR EQUATIONS.
Math Dept, Faculty of Applied Science, HCM University of Technology
Chapter 1 – Linear Equations
Systems and Matrices (Chapter5)
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Review for Chapter 4 Important Terms, Symbols, Concepts 4.1. Systems of Linear Equations in Two Variables.
Matrices King Saud University. If m and n are positive integers, then an m  n matrix is a rectangular array in which each entry a ij of the matrix is.
Sec 3.1 Introduction to Linear System Sec 3.2 Matrices and Gaussian Elemination The graph is a line in xy-plane The graph is a line in xyz-plane.
Euclidean m-Space & Linear Equations Row Reduction of Linear Systems.
Copyright © 2011 Pearson Education, Inc. Publishing as Prentice Hall.
Three variables Systems of Equations and Inequalities.
How To Find The Reduced Row Echelon Form. Reduced Row Echelon Form A matrix is said to be in reduced row echelon form provided it satisfies the following.
8.1 Matrices and Systems of Equations. Let’s do another one: we’ll keep this one Now we’ll use the 2 equations we have with y and z to eliminate the y’s.
Sec 3.2 Matrices and Gaussian Elemination Coefficient Matrix 3 x 3 Coefficient Matrix 3 x 3 Augmented Coefficient Matrix 3 x 4 Augmented Coefficient Matrix.
Using Matrices A matrix is a rectangular array that can help us to streamline the solving of a system of equations The order of this matrix is 2 × 3 If.
Copyright © 2013, 2009, 2005 Pearson Education, Inc. 1 5 Systems and Matrices Copyright © 2013, 2009, 2005 Pearson Education, Inc.
We will use Gauss-Jordan elimination to determine the solution set of this linear system.
Chapter 1 Section 1.3 Consistent Systems of Linear Equations.
Copyright © 2011 Pearson Education, Inc. Solving Linear Systems Using Matrices Section 6.1 Matrices and Determinants.
Matrices and Systems of Equations
Matrices and Systems of Linear Equations
Copyright © 2009 Pearson Education, Inc. CHAPTER 9: Systems of Equations and Matrices 9.1 Systems of Equations in Two Variables 9.2 Systems of Equations.
How To Find The Reduced Row Echelon Form. Reduced Row Echelon Form A matrix is said to be in reduced row echelon form provided it satisfies the following.
Section 7-3 Solving 3 x 3 systems of equations. Solving 3 x 3 Systems  substitution (triangular form)  Gaussian elimination  using an augmented matrix.
Linear Equation System Pertemuan 4 Matakuliah: S0262-Analisis Numerik Tahun: 2010.
 SOLVE SYSTEMS OF EQUATIONS USING MATRICES. Copyright © 2012 Pearson Education, Inc. Publishing as Addison Wesley 9.3 Matrices and Systems of Equations.
Section 8.6 Elimination using Matrices. Matrix Method The method computers use. The equations need to be in standard form. The coefficients and constants.
Section 4Chapter 4. 1 Copyright © 2012, 2008, 2004 Pearson Education, Inc. Objectives Solving Systems of Linear Equations by Matrix Methods Define.
Chapter 1 Linear Algebra S 2 Systems of Linear Equations.
Matrices and Systems of Equations
Meeting 19 System of Linear Equations. Linear Equations A solution of a linear equation in n variables is a sequence of n real numbers s 1, s 2,..., s.
7.3 & 7.4 – MATRICES AND SYSTEMS OF EQUATIONS. I N THIS SECTION, YOU WILL LEARN TO  Write a matrix and identify its order  Perform elementary row operations.
Chapter 1 Systems of Linear Equations Linear Algebra.
Copyright ©2015 Pearson Education, Inc. All rights reserved.
Section 5.3 MatricesAnd Systems of Equations. Systems of Equations in Two Variables.
Slide Copyright © 2009 Pearson Education, Inc. 7.4 Solving Systems of Equations by Using Matrices.
Def: A matrix A in reduced-row-echelon form if 1)A is row-echelon form 2)All leading entries = 1 3)A column containing a leading entry 1 has 0’s everywhere.
Gaussian Elimination Digital Lesson. Copyright © by Houghton Mifflin Company, Inc. All rights reserved. 2 Gaussian elimination with back-substitution.
College Algebra Chapter 6 Matrices and Determinants and Applications
Linear Equations in Linear Algebra
Section 6.1 Systems of Linear Equations
Systems of linear equations
Gaussian Elimination and Gauss-Jordan Elimination
Solving Systems of Equations Using Matrices
Chapter 8: Lesson 8.1 Matrices & Systems of Equations
Matrices and Systems of Equations
Lial/Hungerford/Holcomb/Mullins: Mathematics with Applications 11e Finite Mathematics with Applications 11e Copyright ©2015 Pearson Education, Inc. All.
College Algebra Chapter 6 Matrices and Determinants and Applications
Linear Equations in Linear Algebra
Section 8.1 – Systems of Linear Equations
Presentation transcript:

Chapter 1 Section 1.2 Echelon Form and Gauss-Jordan Elimination

Echelon Form of a Matrix A matrix that satisfies the following three conditions is said to be in echelon form. 1.Every row of all zeros is at the bottom. 2.The first nonzero entry from the left in each row is a 1 (called the leading 1). 3.All entries below the leading 1 in that column are zero. Reduced Echelon Form of a Matrix A matrix is in reduced echelon form if it is in echelon form (i.e. all entries below the leading 1 in each column are zero) and all entries above the leading 1 in each column are zero. Changing Matrix Forms To change the form a matrix is in use the row operations from the Gauss-Jordan method by starting with the top row and working your way down row by row. 1.If the leading entry is zero swap with a lower row to get a nonzero number. 2.Divide the row by the nonzero number to get the leading 1. 3.Clear out the column below the leading 1 (above for reduced echelon) by multiplying the current row by the negative value in the position to be cleared and adding it to that row.

⅓R 1 R 1 +R 2 -2R 1 +R 2 ½R 2 2R 2 +R 3 We can rewrite this so that the variables whose coefficient is the leading 1 in row of the matrix in reduced echelon form is on the right side of the equation and all other variables are on the left. General Solution Particular Solution

Consistent and Inconsistent Systems If a system of equations has at least one solution (maybe more) we say the system is consistent. If no solution for a system of equations exists we say it is inconsistent. The echelon (or reduced) form of an augmented matrix for an inconsistent system will have a leading 1 in the last (or augmented) column of the matrix. Consistent System Inconsistent System Having a leading 1 in the last column corresponds to the equation 0=1 which does not have any solution (i.e. it is always false) no matter what values you assign to the variables. Row Equivalent Matrices Since the 4 basic row operations do not change the solution to the corresponding system of equations if you can transform one matrix into another by a series of row operations we call the two matrices row equivalent.

Example Find all values for a for which the system of equations to the right will not be consistent. Augmented matrix for system ½R 1 -(2- a )R 1 +R 2 In order for this system to not be consistent It must be that the entry in the second row and second column is zero and second row third column is not zero. To make the second row and second column zero a has to be either 4 or -2. If a is -4 then the last row last column is -18 and the system is inconsistent. If a is -2 then the last row and last column -12 and the system is inconsistent. The values are 4 and -2.