Learning Outcomes:
Students will be able to recognize the situations where different classes of nonnegative matrices arise and understand their properties.
Curricular information is subject to change.
Nonnegative matrices are the main objects of this course. We will explore their algebraic, geometric and combinatorial properties and introduce some applications.
The topics will include: Spectral Properties of Nonnegative matrices (Perron Frobenius Theory, Nonnegative Inverse Eigenvalue Problem), Classes of Nonnegative matrices (Stohastic Matrices, Doubly Stohastic Matrices, Totally Nonnegative Matrices, M-matrices, Completelly Positive Matrices), Stable Matrices (Lyapunov's Theorem, Semidefinite Programming)
The topics will include: Spectral Properties of Nonnegative matrices (Perron Frobenius Theory, Nonnegative Inverse Eigenvalue Problem), Classes of Nonnegative matrices (Stohastic Matrices, Doubly Stohastic Matrices, Totally Nonnegative Matrices, M-matrices, Completelly Positive Matrices), Stable Matrices (Lyapunov's Theorem, Semidefinite Programming)
About this Module
Student Effort Hours:
| Student Effort Type | Hours |
|---|---|
| Specified Learning Activities | 34 |
| Autonomous Student Learning | 118 |
| Lectures | 36 |
| Tutorial | 12 |
| Total | 200 |
Requirements, Exclusions and Recommendations
Not applicable to this module.
| Description | % of Final Grade | Timing |
|---|---|---|
| Examination: End of year exam | 70 |
2 hour End of Trimester Exam |
| Continuous Assessment: Homework/Presentations | 30 |
Unspecified |
Compensation
This module is passable by compensation
Resit Opportunities
End of Semester Exam
Remediation
If you fail this module you may repeat, resit or substitute where permissible