Matrix Equations and Model Reduction - Lecture 5

Explore the fifth lecture in a series on Matrix Equations and Model Reduction, presented by Peter Benner from the Max Planck Institute. Delve into the Riccati Equation, understanding its basic idea and applications. Examine linear matrix equations, their solution theory, and linear system representation. Learn about classical methods such as back substitution and symmetry. Discover advanced techniques like the Hammer Lynx Q Algorithm and the Design Function Method. Investigate the concept of upon of equations and gain insights into sparse matrix operations. This comprehensive 1 hour and 52 minute lecture, hosted by the Society for Industrial and Applied Mathematics, provides a deep dive into advanced topics in matrix equations and their applications in model reduction.

Introduction
Outline
The Riccati Equation
The Basic Idea
Linear Matrix Equations
Solution Theory
Linear System Representation
Classical Methods
Back Substitution
Symmetry
Hammer Lynx
Q Algorithm
Design Function Method
Upon of Equations
Sparse Matrix Operations