A heuristic sensitivity analysis technique for high-dimensional systems

Mustafa Berke Yelten*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A viable technique for sensitivity analysis in high-dimensional systems is described in the context of bio-inspired systems. The sensitivity analysis provides critical information about the system by indicating the dominant parameters that shape the output. This knowledge becomes particularly essential to have a better understanding of complex biological network of interactions. A notable feature of many high-dimensional systems is that a large portion of all parameters have little impact on the system outcome, thus yielding sparsity. The proposed algorithm leverages the sparse properties of systems analysed and is based on a heuristic two-stage elimination strategy. The implementation of the proposed algorithm yields substantial reduction of the total simulation cost by as much as 95% for a system composed of 562500 parameters over the conventional local sensitivity analysis while retaining its accuracy above 70%.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Electronics, Circuits and Systems, ICECS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages181-184
Number of pages4
ISBN (Electronic)9781509061136
DOIs
Publication statusPublished - 2016
Event23rd IEEE International Conference on Electronics, Circuits and Systems, ICECS 2016 - Monte Carlo, Monaco
Duration: 11 Dec 201614 Dec 2016

Publication series

Name2016 IEEE International Conference on Electronics, Circuits and Systems, ICECS 2016

Conference

Conference23rd IEEE International Conference on Electronics, Circuits and Systems, ICECS 2016
Country/TerritoryMonaco
CityMonte Carlo
Period11/12/1614/12/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • biological systems
  • high dimensional systems
  • Sensitivity analysis
  • sparse methods

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