Math/CS 143M, Numerical
Scientific Computing (Matrices), Fall 2017
Instructor: Plamen Koev
New room for the rest of the semester: SH 346!
New office hours: M 4-4:30 and W 3-4:30 and by appointment only on Mondays 3-4
New date for midterm 1: October 4, in class (Wednesday instead of Monday)
- Lecture Notes
- Software used for demonstration in class.
- Student-run Facebook group from Fall 2016. Let me know if you form a new one for me to put the link here.
- Due September 18: CORRECTION: Solve all problems from chapter 1, sections 2, 3, and 4 of the lecture notes. Make sure to download the latest version of the notes.
- NEW DATE: Due October 4: Solve all problems from chapter 1, sections 5, 7, and 8, and only problem 1 from chapter 1, section 6 of the lecture notes.
- Due October 23. Solve all problems from Chapter 2, section 2, and Chapter 3, sections 1 through 6.
- Due November 27. Solve all problems from Chapter 4, and Chapter 5, sections 1-7.
- Due December 11 (Firm! There will be no extensions!): Solve problems in Chapter 5, section 8, problems 1, 2, 4, or problems 1, 4, 5.
- Practice exams for Fall 2017:
- Tasks you'll need to know how to perform in order to pass the class. These are in no particular order. Unless it says "on a computer" you should be able to do the tasks by hand.
- Compute 1, 2, and infinity norms of vectors and of up to 3-by-3 matrices.
- Calculate the cost of an algorithm both by hand an on a computer.
- Generate matrices that subtract one row of a matrix from another, multiply a row by a number, or swap rows.
- Generate (potentially complex) Givens rotations that create zeros in matrices.
- Compute the LU, LDU, LU with partial pivoting, Cholesky, and QR decompositions on up to 3-by-3 matrices. Compute the LQ, QL, RQ decomposition on 2-by-2 matrices.
- Perform 1 step of QR iteration with a shift on a 2-by-2 matrix.
- On a computer: Write code that creates zeros in a matrix using elementary elimination operations or Givens rotations.
- Understand properties of orthogonal matrices and be able to check if a matrix is orthogonal.