In this paper we propose a new method for the iterative computation of a few of the extremal eigenvalues of a symmetric matrix and their associated eigenvectors. The method is based on an old and ...

In this paper, we discuss an inverse eigenvalue problem for constructing a 2n × 2n Jacobi matrix T such that its 2n eigenvalues are given distinct real values and its leading principal submatrix of ...

Focuses on numerical solution of nonlinear equations, interpolation, methods in numerical integration, numerical solution of linear systems, and matrix eigenvalue problems. Stresses significant ...

Understanding and implementation of algorithms to calculate matrix decompositions such as eigenvalue/vector, LU, QR, and SVD decompositions. Applications include data-fitting, image analysis, and ...

Eigenvalue optimisation problems involve identifying design or material configurations that either maximise or minimise the eigenvalues associated with differential operators under given boundary ...

*Note: This course discription is only applicable to the Computer Science Post-Baccalaureate program. Additionally, students must always refer to course syllabus for the most up to date information.

Ordinary and partial differential equations, linear algebra, matrix/vector calculus, numerical methods, introduction to optimization methods, and other topics as time permits. Both analytical and ...

This course is compulsory on the BSc in Data Science. This course is available as an outside option to students on other programmes where regulations permit. This course is available with permission ...