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MATH 4366 - Numerical Linear Algebra

***This is a course guideline. Students should contact instructor for the updated information on current course syllabus, textbooks, and course content***

Prerequisites: MATH 2318, or equivalent, and six additional hours of 3000—4000 level Mathematics.

Course Description: Conditioning and stability of linear systems, matrix factorizations, direct and iterative methods for solving linear systems, computing eigenvalues and eigenvectors, introduction to linear and nonlinear optimization.

Textbooks:

  • Introduction to Applied Linear Algebra Vectors, Matrices, and Least Squares, by S. Boyd (Stanford) and L. Vandenberghe (UCLA). ISBN: 978-1316518960.
  • Matrix Factorizations, Iterative Methods, Minimization, a class note by L. Vandenberghe (UCLA).

Course Content:

Conditioning and stability of linear systems, matrix factorizations, direct and iter- ative methods for solving linear systems, computing eigenvalues and eigenvectors, introduction to linear and nonlinear optimization.

  • Introduction; Vectors
  • Norm, distance, angle
  • Matrices
  • Matrix inverses
  • Orthogonal matrices
  • QR factorization
  • Linear equations
  • Least squares
  • Least squares applications
  • Multi-objective least squares
  • Constrained least squares
  • Cholesky factorization
  • Nonlinear least squares

 

Course Structure and Grading Policies: Please consult your instructor's syllabus regarding any and all grading/course structure guidelines.


Justin Dart Jr. Center Accommodations:

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