APM 505 - Applied Linear Algebra

Fall 2010, TTh 10:30-11:45, PSA 307, ECA-221(dates will be announced in class) (Computer Lab)

Instructor: Zdzislaw Jackiewicz

Office: GWC 644, Phone: 965-0082

Office Hours: TTh 12:00-2:00

Textbook: "Numerical Computing with Matlab", by C. Moler, SIAM 2004.

Supplementary Texts: "Computational Science and Engineering", by G. Strang, Wellesley-Cambridge 2007; and "Matrix Theory. A Second Course", by J.M. Ortega, Plenum Press 1987.

Course Description

Fundamentals of applied and numerical linear algebra and programming with MATLAB. The topics include:

Linear systems: permutation and triangular matrices, Gaussian elimination, LU factorization, pivoting, vector and matrix norms, error analysis and conditioning, positive definite matrices, Cholesky factorization, Matlab linear algebra tools.
Least squares problems: curve fitting, Householder reflections and Givens rotations, QR factorization, pseudoinverse, rank deficiency, error analysis, Matlab least squares tools.
Eigenvalues and singular values: eigenvalue and singular value decompositions, eigenvalue and singular value sensitivity and accuracy, Jordan and Schur canonical forms, the QR algorithm, principal components and approximation of matrices, applications, Matlab tools.

Midterm, Final Exam, Homework Assignments
Midterm	40 pts (four problems)
Homework assignments	40 pts (in Matlab programming language)
Final Project	40 pts (in Matlab programming language)
Final Exam	40 pts (four problems)
Midterm will be announced at least one week in advance

Grading Policy
Midterm	40 pts
Homework assignments	40 pts
Final Project	40 pts
Final Exam	40 pts
Total	160 pts
A: 90% and above; B: 80%-90%; C: 70%-80%; D: 60%-70%; E: below 60%.