This chapter considers system‐level modeling of microelectromechanical systems (MEMS),
where model order reduction (MOR) methods based on moment matching play an important …

This paper presents a methodology for optimizing sample point selection in the context of
model order reduction (MOR). The procedure iteratively selects samples from a large …

The parametric model order reduction (PMOR) method applicable to structural matrices from
finite element model is developed for both static and dynamic analysis, so that parameter …

This Chapter introduces parameterized, or parametric, Model Order Reduction (pMOR). The
Sections are offered in a prefered order for reading, but can be read independently. Section …

In this paper we describe a flexible and efficient new algorithm for model order reduction of
parameterized systems. The method is based on the reformulation of the parametric system …

This paper describes an automatic methodology for optimizing sample point selection for
using in the framework of model order reduction (MOR). The procedure, based on the …

In this paper we summarize recent developments in compact dynamical modeling for both
linear and nonlinear systems arising in analog applications. These techniques include …

Analysis and verification environments for next-generation nano-scale RFIC designs must
be able to cope with increasing design complexity and to account for new effects, such as …

One of the most critical challenges in today's CMOS VLSI design is the lack of predictability
in chip performance at design stage. One of the process variabilities comes from the voltage …

This paper describes a Model Order Reduction algorithm for multi-dimensional
parameterized systems, based on a sampling procedure which incorporates a low order …