Instructor: Ed BuelerPhone: 474-7693 eMail: elbueler@alaska.edu Office: Chapman 301C, hours at bueler.github.io/OffHrs.htm |
Class Time: MWF 1:00--2:00 Classroom: Reichardt 204 Web Site: bueler.github.io |

Lectures will include Matlab demonstrations whenever I can fit them in. I will help you get started with Matlab, but you must show initiative in learning actual numerical computation. Homework assignments and a student-chosen project will include actual implementations in Matlab. Abstract and precise thought is, however, essential to make choices among numerical methods for solving major problems. Thus all homework assignments will have mathematical exercises, and in these you will be asked to "show" and "prove". Formal proof style is not important, but you'll need to give clear presentations of sufficiently-general logical arguments.

We will think in terms of vectors and matrices. We will not be satisfied with seeing lots of numbers or pretty pictures from our computer programs. Instead we will be concerned with the degree to which our numbers represent what we claim they approximate. We will seek the underlying linear algebra structure of PDE problems. The course will include some nonlinear examples, for which one uses a sequence of approximating linear problems.

Calendar and Course Webpage: A day-to-day (tentative) schedule for the semester is at the course webpage bueler.github.io/M615S14/.

It is assumed that students in this class have in mind, or can acquire, specific modelling problems in applied fields which can be used for a project. These will mostly, but not exclusively, be PDE problems. Students often use a simplification of a thesis/dissertation project, for instance. I am eager to help and advise on choosing and refining such problems. Twenty-five

Finally, there will be a one-hour in-class midterm exam worth only fifteen percent of the course grade. The purpose is to give a midsemester opportunity to review basics before expanding our goals in the second half.

The course grade will be determined fromhomework+project+midterm according to the schedule at right ---> I will use plus/minus grades as indicated. |
Percent91 --100 % 88 -- 90 % 84 -- 87 % 76 -- 83 % 73 -- 75 % 69 -- 72 % 57 -- 68 % 41 -- 56 % 0 -- 40 % |
GradeA A- B+ B B- C+ C D F |

Policies and makeup exams:

**Programming in the course:** You
will use *Matlab*, Octave, or pylab
(= python+scipy+matplotlib) in this course. These will be
used in homework problems and in projects. Matlab is commercial while Octave
and Pylab are free and open
source. Octave is a clone of
Matlab so the same programs will
run in both. Programs in *Matlab*/*Octave* will appear on my website (and
occasionally in *pylab*).

Copious online resources are available
for learning Matlab/Octave/pylab. They are all languages designed to do numerical analysis
coursework. Mathematical and graphical inputs and outputs are easily
manipulated. Matrices appearing in problems can be easily
analyzed. Many of the operations appearing in numerical problems are
natural and quick and require less work than in compiled
languages like *C* or *FORTRAN*.