Instructor:
Michael Shelley, Warner Weaver Hall 1102
Lectures: Tuesday and Thursday 11:00-12:15pm, class
starts on January 28th
Location: Warren Weaver Hall 201
Office Hours: Thursday 9-11am or by appointment - please email.
Recitation: Friday 11:00-12:15pm, WWH 517, TA: Anthony Trubiano
Midterm: March 26th, 2020
If you email me -- shelley@cims.nyu.edu -- about the class,
please start your subject line with [NA]
We will use Piazza for communication and organization. If you are registered for this class you will receive an invitation to join the course on Piazza at the beginning of the semester. Otherwise please email me and I will add you.
Content:
We will cover classical topics in Numerical Analysis: The solution of linear and nonlinear equations, conditioning, least squares, numerical computation of eigenvalues, interpolation, quadrature, and numerical methods for ODEs. The course will have a focus on the analysis of numerical methods, but also require you to use numerical software (Matlab, Python, or Julia). If you are not familiar with any of these tools, the recitation will give an introduction to Matlab during the first weeks. Additionally, I recommend that you work through one of the books listed below before the course starts or in the first weeks of the semester.
Grading policy:
30% Homework, 10% Quizzes, 25% Midterm, 35% Final.
Literature:
Endre Suli and David Mayers (2003): An Introduction to Numerical Analysis. Cambridge University Press, 2003. PDF available from campus
Further reading:
Ridgeway Scott (2011): Numerical Analysis, Princeton University Press.
Gander, W., Gander, M.J., & Kwok, F. (2014). Scientific Computing - An Introduction Using Maple and MATLAB. Texts in Computation Science and Engineering [Series, Vol. 11]. New York, NY: Springer-Verlag.
Moler, C: (2004) Numerical
Computing with Matlab, SIAM.
Lectures:
January 28, Lecture
1
January 30, Lecture
2
February 4, Lecture
3
February 6, Lecture
4
February 11, Lecture 5
February 13, Lecture 6
February 20, Lecture 7
February 25, Lecture 8
February 27, Lecture 9
March 3, Lecture 10
March 5 Lecture 11
March 10 Lecture 12
March 12 Lecture 13
Homeworks:
Homework 1, due
February 20
Homework 2, due
March 12