Algorithms for the solution of eigenproblems arise in many different fields of science like computational fluid dynamics, solid
mechanics, electrical networks, signal analysis, and optimisation. In
this project we will study numerical methods for the solution of
eigenvalue problems which are based on different transformation
techniques for symmetric matrices. We are going to study following
algorithms for the symmetric eigenproblem: tridiagonal QR iteration.
Rayleigh quotient iteration, Divide-and-conquer,
bisection and inverse iteration, Jacobi method.
We will discover convergence for all these algorithms and compare
their performance with respect to applicability, reliability, accuracy, and efficiency. Programs
written in Matlab will demonstrate performance for every algorithm on
the solution of practical problems.
Obs! För GU-studenter räknas projektet som ett projekt i Tillämpad Matematik (MMG900/MMG920).
Examinator Maria Roginskaya, Marina Axelson-Fisk
Institution Matematiska vetenskaper