Prerequisites: Math 110 and 128A or equivalent, and basic MATLAB skills.
Description: Iterative methods for linear systems, approximation theory, iterative solution of systems of nonlinear equations, approximation of eigenvalues and eigenvectors of matrices, applications to simple partial differential equations. Practice on the computer.
Office: Evans 811
Office Hours: Probably Tu 11-12, 1-2:15; Th 8:30-9:15
Required Text: Numerical Analysis, 2nd ed., Timothy Sauer, Pearson Pub., 2011
Comment: This is a mathematics course, and so the emphasis is on how to obtain effective methods for computation, and on analyzing when methods will, and will not, work well (in contrast to just learning algorithms and applying them).
Grading: There will be homework and there will be biweekly quizzes, which will each count for 10% of the course grade. There will be programming exercises and there will be one in-class midterm exam, which will each count for 20% of the course grade. There will be a final examination, which will count for 40% of the course grade.
Makeup midterm exams will not be given; instead, if you tell me ahead of time that you must miss the midterm exam, then the final exam and the other components will count more to make up for it. If you do not tell me ahead of time, then you will need to bring me a doctor's note or equivalent to try to avoid a score of 0. There will be no early or make-up final examination.
The final examination will take place on WEDNESDAY MAY 10 11:30-2:30 PM.
The midterm exam is expected to take place on Tuesday March 7, 9:30-11 AM.
Students who need special accommodation for examinations should bring me the appropriate paperwork, and must tell me at least a week in advance of each exam what specific accommodation they need, so that I will have enough time to arrange it.
Homework: Homework will be assigned at almost every class meeting, due at the section meeting the following week. Students are encouraged to discuss the homework and programming assignments with each other, but each student must write their own solutions, reflecting their own understanding, and not copy solutions from anyone else. Even more, if students collaborate in working out solutions or computer code, or get specific help from others, they should explicitly acknowledge this help in the written work they turn in. This is general scholarly best practice. There is no penalty for acknowledging such collaboration or help.
Course Webpage: The link is at: math.berkeley.edu/~rieffel