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 mod...
Joel R. Phillips, Luca Daniel, Luis Miguel Silveir...
Numerous approaches have been proposed to address the overwhelming modeling problems that result from the emergence of magnetic coupling as a dominant performance factor for ICs a...
In this paper, we propose a new wideband model order reduction method for interconnect circuits by using a novel adaptive sampling and error estimation scheme. We try to address t...
A dimension reduction method called Discrete Empirical Interpolation (DEIM) is proposed and shown to dramatically reduce the computational complexity of the popular Proper Orthogo...
Sequential optimal design methods hold great promise for improving the efficiency of neurophysiology experiments. However, previous methods for optimal experimental design have in...
Jeremy Lewi, Robert J. Butera, David M. Schneider,...