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Parametrized Model Order Reduction (PMOR): Sparse Data and Sparse Models (3G008009)

The main objective of this project is the development of robust and stable rational modelling algorithms to build parametrized reduced order models for complex physical systems. The order and complexity of the scalable rational models are specifically tailored towards the application at hand. The approximation and/or interpolation models are based on sparse scatterded data,spread over the design space of interest, and the models are aimed at to be sparse themselves in order to guarantee a minimal complexity.

Date:1 Jan 2009  →  31 Dec 2014
Keywords:Parametrized Model Order Reduction (PMOR), macromodel, linear time-invariant system (LTI)
Disciplines:Other information and computing sciences, Computer architecture and networks, Programming languages, Scientific computing, Information systems, Visual computing, Theoretical computer science, Distributed computing, Applied mathematics in specific fields, Information sciences