Due to refined modelling of semiconductor devices and increasing packing densities, reduced order modelling of large nonlinear systems is of great importance in the design of integrated circuits (ICs). Despite the linear case, methodologies for nonlinear problems are only beginning to develop. The most practical approaches rely either on linearisation, making techniques from linear model order reduction applicable, or on proper orthogonal decomposition (POD), preserving the nonlinear characteristic. In this paper we focus on POD. We demonstrate the missing point estimation and propose a new adaption of POD to reduce both dimension of the problem under consideration and cost for evaluating the full nonlinear system.
|Title of host publication||Scientific Computing in Electrical Engineering SCEE 2008|
|Editors||J. Roos, L.R.J. Costa|
|Place of Publication||Berlin|
|Publication status||Published - 2010|
|Name||Mathematics in Industry|
Verhoeven, A., Striebel, M., & Maten, ter, E. J. W. (2010). Model order reduction for nonlinear IC models with POD. In J. Roos, & L. R. J. Costa (Eds.), Scientific Computing in Electrical Engineering SCEE 2008 (pp. 571-578). (Mathematics in Industry; Vol. 14). Springer. https://doi.org/10.1007/978-3-642-12294-1_70