1 / 42

Simultaneous Linear Equations

Simultaneous Linear Equations. PHYSICAL PROBLEMS. Truss Problem. a. a. c. b. b. Pressure vessel problem. Polynomial Regression. We are to fit the data to the polynomial regression model. Simultaneous Linear Equations Naive Gaussian Elimination (Naïve and the Not That So Innocent Also).

dames
Download Presentation

Simultaneous Linear Equations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Simultaneous Linear Equations http://nm.mathforcollege.com

  2. PHYSICAL PROBLEMS http://nm.mathforcollege.com

  3. Truss Problem http://nm.mathforcollege.com

  4. a a c b b Pressure vessel problem http://nm.mathforcollege.com

  5. Polynomial Regression We are to fit the data to the polynomial regression model http://nm.mathforcollege.com

  6. Simultaneous Linear EquationsNaive Gaussian Elimination(Naïve and the Not That So Innocent Also) http://nm.mathforcollege.com

  7. Naïve Gaussian Elimination A method to solve simultaneous linear equations of the form [A][X]=[C] Two steps 1. Forward Elimination 2. Back Substitution

  8. Forward Elimination The goal of forward elimination is to transform the coefficient matrix into an upper triangular matrix

  9. Forward Elimination Exercise: Show the steps for this slide (10 minutes).

  10. Back Substitution Solve each equation starting from the last equation Example of a system of 3 equations

  11. Forward Elimination A set of n equations and n unknowns . . . . . . (n-1) steps of forward elimination

  12. Forward Elimination Step 1 For Equation 2, divide Equation 1 by and multiply by .

  13. Forward Elimination Subtract the result from Equation 2. − _________________________________________________ or

  14. Forward Elimination Repeat this procedure for the remaining equations to reduce the set of equations as . . . . . . . . . End of Step 1

  15. Forward Elimination Step 2 Repeat the same procedure for the 3rd term of Equation 3. . . . . . . End of Step 2

  16. Forward Elimination At the end of (n-1) Forward Elimination steps, the system of equations will look like . . . . . . End of Step (n-1)

  17. Matrix Form at End of Forward Elimination

  18. Back Substitution Solve each equation starting from the last equation Example of a system of 3 equations

  19. Back Substitution Starting Eqns . . . . . .

  20. Back Substitution Start with the last equation because it has only one unknown

  21. Back Substitution

  22. Naïve Gauss EliminationExamplehttp://numericalmethods.eng.usf.edu

  23. Example 1 The upward velocity of a rocket is given at three different times Table 1 Velocity vs. time data. The velocity data is approximated by a polynomial as: Find the velocity at t=6 seconds .

  24. Example 1 Cont. Assume Results in a matrix template of the form: Using data from Table 1, the matrix becomes:

  25. Example 1 Cont. • Forward Elimination • Back Substitution

  26. Forward Elimination

  27. Number of Steps of Forward Elimination Number of steps of forward elimination is (n-1)=(3-1)=2

  28. Forward Elimination: Step 1 Divide Equation 1 by 25 and multiply it by 64, . . Subtract the result from Equation 2 Substitute new equation for Equation 2

  29. Forward Elimination: Step 1 (cont.) Divide Equation 1 by 25 and multiply it by 144, . . Subtract the result from Equation 3 Substitute new equation for Equation 3

  30. Forward Elimination: Step 2 Divide Equation 2 by −4.8 and multiply it by −16.8, . Subtract the result from Equation 3 Substitute new equation for Equation 3

  31. Back Substitution

  32. Back Substitution Solving for a3

  33. Back Substitution (cont.) Solving for a2

  34. Back Substitution (cont.) Solving for a1

  35. Naïve Gaussian Elimination Solution

  36. Example 1 Cont. Solution The solution vector is The polynomial that passes through the three data points is then:

  37. Determinant of a Square MatrixUsing Naïve Gauss EliminationExamplehttp://nm.MathForCollege.com

  38. Theorem of Determinants If a multiple of one row of [A]nxn is added or subtracted to another row of [A]nxn to result in [B]nxn then det(A)=det(B)

  39. Theorem of Determinants The determinant of an upper triangular, lower triangular or diagonal matrix [A]nxn is given by

  40. Forward Elimination of a Square Matrix Using forward elimination to transform [A]nxn to an upper triangular matrix, [U]nxn.

  41. Example Using Naive Gaussian Elimination method, find the determinant of the following square matrix.

  42. Finding the Determinant After forward elimination steps .

More Related