We present a framework for passivity-preserving model reduction for RLC systems that includes, as a special case, the well-known PRIMA model reduction algorithm. This framework pr...
In this paper, we propose a novel statistical model order reduction technique, called statistical spectrum model order reduction (SSMOR) method, which considers both intra-die and...
Jeffrey Fan, Ning Mi, Sheldon X.-D. Tan, Yici Cai,...
A general framework for structure-preserving model reduction by Krylov subspace projection methods is developed. The goal is to preserve any substructures of importance in the matr...
We describe a prototype Web service for model reduction of very large-scale linear systems. Specifically, a userfriendly interface is designed so that model reduction can be easi...
Peter Benner, Rafael Mayo, Enrique S. Quintana-Ort...
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...