Riemannian optimal model reduction of linear second-order systems
Riemannian optimal model reduction of linear second-order systems is a scholarly work, published in 2017 in ''IEEE control systems letters''. The main subjects of the publication include mathematics, physics-informed neural networks, invariant manifold, mathematical analysis, Riemannian manifold, statistical manifold, -, applied mathematics, tangent space, geodesic curve, information geometry, Euclidean space, gradient descent, numerical method for ordinary differential equations, Riemannian geometry, manifold, Stiefel manifold, finite element method, pseudo-Riemannian manifold, and pure mathematics. This letter develops a structure preserving H 2 optimal model reduction method of linear second-order systems.