## MAE290a - Numerical Methods (Linear Algebra & ODEs)

**Policies**: **Please read the Course & Homework Policy for this class.**

**Instructor**: Thomas Bewley (Office hours: 8:00-9:00am M-F in 1805 ebu1 and for 30 minutes after each lecture)

**Time and place**: We last taught this class in Fall 2010, and are not scheduled to teach it in the coming academic year.

**Administrative details**: Midterm: in class on Nov 2. Final: 7pm on friday, Dec 10, in Center Hall room 212.

**Text**: This class is taught from selected sections of *Numerical Renaissance*,
with supplemental texts held on reserve at the library as announced in class.

**Course description**: Numerical linear algebra, numerical methods, and numerical analysis, with an emphasis on high performance computing. Topics include direct and iterative methods for systems of linear and nonlinear equations, the fundamental matrix decompositions (QR/Schur/Eigen/Jordan/SVD/LU/Cholesky), pseudoinverses, and numerical algorithms for differentiation (finite differences), integration of functions, integration of ODEs (via CN, RK, etc.), and an introduction to the integration of PDEs.

**Prerequisites**: Undergraduate-level linear algebra, complex variables, and rudimentary computer programming tools (for loops, if statements, function calls, and floating-point operations on vectors and matrices).

**Previous exams**:
All of the old exams for MAE290a are posted below. Note that the notes have evolved significantly since 1999, so some of this material is just a repeat of what is now in the notes (and some of it is in a slightly different notation). I post these exams here mostly so you can get an idea of what my exams look like before taking one. By going through these exams, you will see that I occasionally (but not frequently) reuse some of the questions.

**Thoughts for the day**:

*Stand firm in your refusal to remain conscious during algebra. In real life, I assure you, there is no such thing as algebra.* - Fran Lebowitz

*Data is not information, information is not knowledge, knowledge is not understanding, understanding is not wisdom.* - Howard Garner