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National University of Singapore, Science Faculty, Computational Sci Dept
 
   
   

CZ4101: Matrix Computations


Synopsis
Linear equations. Least-squares problems. Symmetric eigenvalue problem. Singular-value decomposition, QR and Cholesky factorization. Iterative methods, conjugate gradient method. Linear algebra libraries (e.g. BLAS, Lapack).

Instructor
Dr. Chen Yu Zong
Department of Computational Science
National University of Singapore
Office: Blk S17 Room 07-24
Tel: 6874-6877. Fax: 6774-6756
E-mail: yzchen@cz3.nus.edu.sg
Web: http://www.cz3.nus.edu.sg/~yzchen
(Lots of info about biocomputing)

Schedule

  • Lectures:
    • Lect 1,
    • Lect 2
  • Labs:
    • Lab 1,
    • Lab 2
  • Tutorials:
    • Tut 1,
    • Tut 2
  • Grade:
    • Final exam,
    • Mid-term exam,
    • Lab
  • Exams:
    • One mid-term exam:
    • One final exam:

Module Outline

  • Introduction
  • Gaussian Elimination and Its Variants
  • Sensitivity of Linear Systems: Effects of Roundoff Errors
  • Orthogonal Matrices and the Least-Squares Problem
  • Eigenvalues and Eigenvectors I
  • Eigenvalues and Eigenvectors II
  • Other Methods for the Symmetric Eigenvalue Problem
  • The Singular Value Decomposition Appendices

Lab Schedule

Tutorials
Tutorials

A Note About Textbook

  1. Fundamentals of Matrix Computations. David S. Watkins. John Wiley, Singapore, 1991. ISBN 0-471-61414-9.

References:

  1. Matrix Computations. Gene H. Golub and Charles F. Van Loan, Johns Hopkins University, Press, Baltimore, 1996. ISBN 0-8018-5414-8
  2. Numerical Linear Algebra.  Lloyd N. Trefethen and avid Bau, III, Society for Industrial and Applied Mathematics, Philadelphia, 1997. ISBN 0-89871-361-7
Homework assignments
Solutions to tutorial
Solutions to Lab

   
           
 
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Department of Computational Science | National University of Singapore | Blk S17, 3 Science Drive 2, Singapore 117543