This site uses cookies to deliver our services and to ensure you get the best experience. By continuing to use this site, you consent to our use of cookies and acknowledge that you have read and understand our Privacy Policy, Cookie Policy, and Terms
We present a formal procedure for structure-preserving model reduction of linear second-order and Hamiltonian control problems that appear in a variety of physical contexts, e.g., ...
The gramian approximation methods have been proposed recently to overcome the high computing costs of classical balanced truncation based reduction methods. But those methods typi...
Abstract— We study Balanced Truncation for stochastic differential equations. In doing so, we adopt ideas from large deviations theory and discuss notions of controllability and ...