1. This course teaches advanced topics from matrix algebra and prepares the students with mathematical background for future theoretical studies, particularly in the fields of system science and engineering. The syllabus of the course is
(i) Introduction
(ii) Basic matrix operations
(iii) Eigenvalues and eigenvectors
(iv) Norms
(v) Inner products
(vi) Matrix decompositions
(vii) Special matrices
(viii) Matrix calculus
(ix) Matrices in optimization and interpolation
(x) Matrix computations
2. This course is based on the lecture notes the teacher prepares, and the main references are
?T. K. Moon and W. C. Stirling, Mathematical Methods and Algorithms for Signal Processing, Prentice-Hall Inc., 2000.
? R. A. Horn and C. A. Johnson, Matrix Analysis, Cambridge University Press, 1985.
3. Grading: Mid-term 50% and Final 50%.
4. Pre-request courses; Calculus and Linear Algebra.