With the rapid developments in very large-scale integration (VLSI) technology, design and
computer-aided design (CAD) techniques, at both the chip and package level, the operating …

In recent years, reduced-order modeling techniques based on Krylov-subspace iterations,
especially the Lanczos algorithm and the Arnoldi process, have become popular tools to …

This paper describes PRIMA, an algorithm for generating provably passive reduced order N-
port models for RCL interconnect circuits. It is demonstrated that, in addition to requiring …

In this paper, we present an approach to nonlinear model reduction based on representing a
nonlinear system with a piecewise-linear system and then reducing each of the pieces with …

This paper proposes a supervised machine learning framework for the non-intrusive model
order reduction of unsteady fluid flows to provide accurate predictions of non-stationary state …

Many reduced-order models are neither robust with respect to parameter changes nor cost-
effective enough for handling the nonlinear dependence of complex dynamical systems. In …

In this paper, we describe an approach for generating accurate geometrically parameterized
integrated circuit interconnect models that are efficient enough for use in interconnect …

The major concerns in state-of-the-art model reduction algorithms are: achieving accurate
models of sufficiently small size, numerically stable and efficient generation of the models …

The problem of automated macromodel generation is interesting from the viewpoint of
system-level design because if small, accurate reduced-order models of system component …

Closed form solutions for the 50% delay, rise time, overshoots, and settling time of signals in
an RLC tree are presented. These solutions have the same accuracy characteristics as the …