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# chap09classlecture - Chapter 9 Gauss Elimination Gauss...

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Chapter 9 Chapter 9 Gauss Elimination Gauss Elimination

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Gauss Elimination Gauss Elimination 9.1 Solving small numbers of equations 9.2 Naive Gauss Elimination 9.3 Pivoting 9.4 Tridiagonal Systems MATLAB M-files GaussNaive, GaussPivot, Tridiag
Small Matrices Small Matrices For small numbers of equations, can be solved by hand Graphical Cramer ' s rule Elimination = + + + = + + + = + + + n n nn 2 2 n 1 1 n 2 n n 2 2 22 1 21 1 n n 1 2 12 1 11 b x a x a x a b x a x a x a b x a x a x a

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Graphical Method Graphical Method - = - = = + = - 1 2 1 2 2 1 2 1 x 3 x 3 x 2 x rearrange 3 x x 3 x x 2 2x 1 – x 2 = 3 x 1 + x 2 = 3 One solution
Graphical Method Graphical Method 2x 1 – x 2 = 3 2x 1 – x 2 = – 1 No solution

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Graphical Method Graphical Method 6x 1 – 3x 2 = 9 2x 1 – x 2 = 3 Infinite many solution
Graphical Method Graphical Method 2x 1 – x 2 = 3 2.1x 1 – x 2 = 3 Ill conditioned

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» xx=-10:1:10; yy=-10:1:10; [x,y]=meshgrid(xx,yy); » z1=3*x-2*y+3; z2=-2*x+3*y-2; z3=x+y-5; » surf(x,y,z1); hold on; surf(x,y,z2); surf(x,y,z3); 3 equations
Cramer’s Rule Cramer’s Rule Compute the determinant D 2 x 2 matrix 3 x 3 matrix 21 12 22 11 22 21 12 11 a a a a a a a a D - = = 32 31 22 21 13 33 31 23 21 12 33 32 23 22 11 33 32 31 23 22 21 13 12 11 a a a a a a a a a a a a a a a a a a a a a a a a D + - = =

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Cramer’s Rule Cramer’s Rule To find x k for the following system Replace k th column of a s with b s (i.e., a ik b i ) n n nn 2 2 n 1 1 n 2 n n 2 2 22 1 21 1 n n 1 2 12 1 11 b x a ... x a x a b x a ... x a x a b x a ... x a x a = + + + = + + + = + + + ) ) ( ij k D(a matrix new D x =
Example Example 3 x 3 matrix 33 32 31 23 22 21 13 12 11 a a a a a a a a a D = 3 32 31 2 22 21 1 12 11 3 3 33 3 31 23 2 21 13 1 11 2 2 33 32 3 23 22 2 13 12 1 1 1 b a a b a a b a a D 1 D D x a b a a b a a b a D 1 D D x a a b a a b a a b D 1 D D x = = = = = =

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Ill-Conditioned System Ill-Conditioned System What happen if the determinant D is very small or zero? Divided by zero (linearly dependent system) Divided by a small number: Round-off error Loss of significant digits [ ] 0 A det D =
Eliminate x 2 Subtract to get = + = + 2 2 22 1 21 1 2 12 1 11 b x a x a b x a x a = + = + 2 12 2 22 12 1 21 12 1 22 2 12 22 1 11 22 b a x a a x a a b a x a a x a a a a a a b a b a x a a a a b a b a x b a b a x a a x a a 21 12 22 11 1 21 2 11 2 21 12 11 22 2 12 1 22 1 2 12 1 22 1 21 12 1 11 22 - - = - - = - = - Elimination Method Elimination Method Not very practical for large number (> 4) of equations

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MATLAB’s Methods MATLAB’s Methods Forward slash ( / ) Back-slash ( \ ) Multiplication by the inverse of the quantity under the slash b * A inv x b A x b A x b Ax 1 ) ( \ = = = = -
Gauss Elimination Gauss Elimination Manipulate equations to eliminate one of the unknowns Develop algorithm to do this repeatedly The goal is to set up upper triangular matrix Back substitution to find solution (root) = nn n 3 33 n 2 23 22 n 1 13 12 11 a a a a a a a a a a U

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Basic Gauss Elimination Basic Gauss Elimination
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## This note was uploaded on 03/07/2009 for the course CVEN 302 taught by Professor Edge during the Spring '08 term at Texas A&M.

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chap09classlecture - Chapter 9 Gauss Elimination Gauss...

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