ENBIS-17 in Naples

9 – 14 September 2017; Naples (Italy) Abstract submission: 21 November 2016 – 10 May 2017

Statistical Challenges in Compact Models for LED Design

11 September 2017, 11:10 – 11:30

Abstract

Submitted by
Alessandro Di Bucchianico
Authors
Alessandro Di Bucchianico (Eindhoven University of Technology), Josephine Sari (Eindhoven University of Technology)
Abstract
LED lamps are a game changer in the illumination industry, because of their superior technical properties with respect to energy efficiency and life span. Design of LED lamps is much more involved than for traditional lamps, since LED lamps offer many new technical illumination features. Since competition in this industry is fierce and electro-thermal-optical simulation of new LED designs is time consuming, it is essential to provide designers with models that allow for fast simulation so that design choices can be evaluated in a timely way.
As part of the EU project Delphi4LED, so-called compact models are being derived based on combining physical laws with techniques from mathematical analysis and control theory under the name of Model Order Reduction. We will discuss data-driven versions of these techniques from a statistical point of view and show how they relate to common statistical approaches to dimension reduction. We will also discuss the statistical challenges that arise in fitting compact models to real data sets.
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