The schedule below is tentative. Please check the class website (Announcements) for changes/updates.


   NM – Numerical Methods Design, Analysis, and Computer Implementation of Algorithms by Greenbaum & Chartier

Free Adobe pdf Viewer  [ http://get.adobe.com/reader/otherversions/ ]
 

 

Date

Lecture Notes

Week 1                         

June 10

Lecture 1: Introduction, Numbers, Operators, Numerical Error [.pdf]   NM Chp 5 (except 5.5)

June 11

Lecture 1: continued

June 12

Lecture 2: continued

June 13

Lecture 2:

Taylor Series,  Rate of Convergence ,Condition Number , Stability [.pdf]  NM Chps 4.2,5.5, 6, Appendix B

June 14

 

Week 2

June 17

Lecture 2: continued

June 18

Lecture 3: continued

June 19

Lecture 3: Root finding, Bracketing, bisection, Newton's method, Rate of Convergence, Condition Number [.pdf] NM Chps 4 (except 4.4.3, 4.5), 6

June 20

Lecture 3: continued

June 21

 

Week 3 

June 24

Lecture 4: Newton's Method in higher dimensions, Secant Method, Fractals, Matlab's fzero function [.pdf] NM Chp 4.43, 4.6,

June 25

Lecture 5: Solving systems of linear equations, simple cases.  Cramer's Rule.  [.pdf] NM Chp 7.1,7.2 (except 7.2.4), 7.3

Review of Linear Algebra [.pdf] NM Appendix A

June 26

Lecture 5: continued

June 27

Lecture 6: Gaussian elimination, LU factorization, Inverse of a matrix  [.pdf] NM Chp 7.1, 7.2(except 7.2.4)

June 28


Week 4                       

July 1

Lecture 7: GE with pivoting, LUPA, LUPAQ [.pdf]  NM Chp 7.4, 7.5

July 2

Lecture 7: continued

July 3

Midterm Exam  

July 4

Holiday (no lecture or labs)

July 5


Week 5

July 8

Lecture 7:continued

July 9

Lecture 8: Banded matrices, more LU, orthogonal, symmetric and symmetric positive definite matrices, Cholesky factorization, SVD [.pdf] NM Chp 7.2.4

July 10

Lecture 8: continued

July 11

Lecture 8: continued

July 12

 

 


 




Week 6

July 15

Lecture 9: Least Square Problems, QR factorization, SVD and least squares [.pdf] NM Chp 7.6.1, 7.6.2

July 16

Lecture 9: continued

July 17

Lecture 10: Sparse matrices. Jacobi, Gauss-Siedel, Conjugate Gradient iterative methods for solving a linear system. Power method, inverse power method for finding eigenvalues. [.pdf] NM Chp 12.1.1, 12.2.1-12.2.4

July 18

Lecture 10: continued

July 19

 

Week 7

July 22

Lecture 11: Polynomial Interpolation , Lagrange and Newton polynomials [.pdf] NM Chp 8.1-8.5

July 23

Lecture 11: continued

July 24

Lecture 12: Polynomial Interpolation. Piecewise polynomials, Splines [.pdf] NM Chp 8.6

July 25

Lecture 12: continued

July 26

 

Week 8

July 29

Lecture 13: Definite Integrals, Newton-Cotes, Monte Carlo, Random Numbers, Gaussian Quadrature [.pdf] NM Chp 10.1-10.3

July 30

Lecture 13: continued

July 31

Lecture 13: continued

August 1

READINGS DAY 1pm

August 2

Final Exam (Time and location to be determined)