State-response decomposition for model reduction

Tunneling and Decomposition-Based State Reduction for Optimal Planning

Action pruning is one of the most basic techniques for improving a planner’s performance. The challenge of preserving optimality while reducing the state space has been addressed by several methods in recent years. In this paper we describe two optimality preserving pruning methods: The first is a generalization of tunnel macros. The second, the main contribution of this paper, is a novel parti...

Model Reduction of State

The nonsymmetric Lanczos method has recently received signiicant attention as a model reduction technique for large-scale systems. Unfortunately, the Lanczos method may produce an unstable partial realization for a given, stable system. To remedy this situation, inexpensive implicit restarts are developed which can be employed to stabilize the Lanczos generated model.

Model order reduction via eigen decomposition analysis

In this paper, we have proposed a novel model order reduction technique via rational transfer function fitting and eigenmode analysis considering residues. We define a constant as a key in the sorting algorithm as one of correlations in order to sort the order of eigenvalues. It is demonstrated that the accuracy via eigenmode analysis considering residues is improved. The proposed algorithm is ...

Model Reduction via Proper Orthogonal Decomposition

Model Reduction by Proper Orthogonal Decomposition (POD)

Mathematical models for human tissue and blood flow both represent time dependent nonlinear partial differential equations in three space dimensions. Their numerical solution based on appropriate space/time discretizations requires computational times that even when using state-of-the-art algorithmic solvers are far from being acceptable for real time OR scenarios. A way to overcome this diffic...