MATH 375: Introduction to Numerical Computing



Time and Place: Tuesday/Thursday 12:30 pm - 1:45 am, SMLC B81
Instructor: Jehanzeb H. Chaudhry (Zeb), jehanzeb@unm.edu, www.math.unm.edu/~jehanzeb
Office Hours: Tuesday 2:00 pm - 3:30 pm, Wednesday 9:30 am - 11:00 am (SMLC 202)


Texts: Numerical Mathematics and Computing, by E. Ward Cheney and David R. Kincaid, 7th Edition. (6th Edition is also fine).
Other Recommended Texts: (1) Numerical Mathematics and Computing, M. Heath. (2) Numerical Analysis, by T. Sauer.
Prerequisites: CS 151 or CS 152 or Phys 290 or ECE 131 or comparable programming skills AND Math 316 or Math 314 or Math 321 or equivalent.

Course Description:   This is an introductory numerical analysis course. We study numerical methods to solve linear and nonlinear equations, to interpolate and approximate data, and methods for numerical integration and differentiation. We will implement all algorithms in MATLAB, and begin the course with a MATLAB tutorial.
The topics that we cover in this class are Floating-Point Representation, Linear Systems, Nonlinear Equations, Interpolation, Numerical Differentiation and Integration, Initial Value Problems and Least-Squares Methods. Additional topics may be covered at the instructor's discretion depending on time and student interest.

Grading:  
50% Homework
15% Exam 1
15% Exam 2
20% Final Exam

Important Dates:  
Exam 1:   February 25 (Thursday), during regular class hours.
Exam 2:   March 31 (Thursday), during regular class hours.
Final Exam:   May 12 (Thursday), 10:00 am - 12 noon.

Syllabus  

MATLAB Tutorial Files: MATLAB tutorial (PDF) script with all commands(matlab_tutorial.m) ApproxExp.m f1.m df1.m MyDeriv.m my_funky_fcn.m

Homework  
All homeworks are due in the beginning of class.

Homework 1   Due: Feb 4   Files I used to generate solutions: solution script my_mean.m my_fun.m
Homework 2   Due: Feb 16   Notes and Files on the solutions: scribbles solution script MyDeriv.m MyDeriv_2.m
Homework 3   Due: Feb 23 scribbles
Homework 4   Due: March 10 hw4_q1.m hw4_q2.m generate_SPD_mat_and_rhs_vec.m my_jacobi.m my_gauss_siedel.m my_cg.m
Homework 5   Due: March 24
Homework 6   Due: April 7
Homework 7   Due: April 14 eval_spine.m
Homework 8   Due: April 28 polls.csv
Homework 9   Due: May 5

Lectures  
Lecture 1 Slides 4up
Lecture 2 Slides 4up
Lecture 3 Slides 4up
Lecture 4 Slides 4up
Lecture 5 Slides 4up Matlab Files: test_flops.m GE_naive.m GE_naive_script.m
Lecture 6 Slides 4up
Lecture 7 Slides 4up
Lecture 8 Slides 4up
Lecture 9 Slides 4up
Exam 1 Review Questions
Lecture 10 Slides 4up (Suggested Reading: NMC7 3.1)
Lecture 11 Slides 4up (Suggested Reading: NMC7 3.2)
Lecture 12 Slides 4up (Suggested Reading: NMC7 3.3)
Questions for Lectures 10-12
Lecture 13 Slides 4up (Suggested Reading: NMC7 4.1)
Questions for Lecture 13
Lecture 14 Slides 4up (Suggested Reading: NMC7 4.1, 4.2, 6.1)
Lecture 15 Slides 4up (Suggested Reading: NMC7 6.1. 6.2)
Questions for Lecture 15
Lecture 16 Slides 4up diff_fwd.m diff_central.m diff_richard.m (Suggested Reading: NMC7 4.3)
Questions for Lecture 16
Lecture 17 Slides 4up trap_int_test.m simp_int_test.m (Suggested Reading: NMC7 5.1, 5.3)
Lecture 18 Slides 4up int_gauss.m int_gauss_test.m int_compare_gauss_trapezoid_simpson.m (Suggested Reading: NMC7 5.4)
Questions for Lecture 17 and 18
Lecture 19 Slides 4up (Suggested Reading: NMC7 8.1, 8.2, and this )
Questions for Lecture 19
Lecture 20 Slides 4up (Suggested Reading: NMC7 8.2, 9.1, 9.3)
Questions for Lecture 20
forward_euler_script
Questions for ODE solvers