Rice: Unconventional Wisdom
Thesis Defense
Graduate and Postdoctoral Studies
Electrical and Computer Engineering
Speaker: Antonio Cosmin Ionita
Doctoral Candidate

  Lagrange rational interpolation and its applications to approximation of large-scale dynamical systems
Friday, August 30, 2013
9:00 AM  to 11:00 AM
1044  Duncan Hall

We present a new, efficient algorithm that extracts low complexity models from frequency response measurements. Our work is motivated by the fact that, in many applications, analytical models of a dynamical system are seldom available. Instead, we may only have access to its frequency response measurements. For example, for a system with multiple inputs and outputs, we may only have access to data sets of S-parameters. In this setting, our new approach extracts models that interpolate the given measurements. The extracted models have low complexity (or reduced order) and, thus, lead to short simulation times and low data storage requirements. The main tool used by our approach is Lagrange rational interpolation -- a generalization of the classic result of Lagrange polynomial interpolation. We present an in-depth look at Lagrange rational interpolation and provide several new insights and straightforward proofs. This analysis leads to new algorithms that rely on the singular value decomposition (SVD) of the Loewner matrix pencil formed directly from the measurements. We show several new results on rational interpolation for measurements of linear, bi-linear and quadratic-linear systems. Furthermore, we generalize these results to parametrized measurements, that is, we show how to interpolate frequency response measurements that depend on parameters. We showcase this new approach through a series of relevant numerical examples such as n-port systems and parametrized partial differential equations.

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