Identification of linear time varying systems using basis pursuit

Sreemoyi Sanyal*, Sunil L. Kukreja, Eric Perreault, David T. Westwick

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

System identification involves creating mathematical models of systems using measurements of their inputs and outputs. Linear time-varying systems form an important sub-class of models that require the use of specialized system identification techniques. One such approach involves expanding the time-varying parameters onto a set of temporal basis functions and then estimating the resulting expansion coefficients. This, however, requires the estimation of a large number of parameters and often results in extreme noise sensitivity. In this paper a novel algorithm for identifying time-varying systems is presented. It combines a temporal expansion with a term selection step that uses the "Least Absolute Shrinkage and Selection Operator", or Lasso. The Lasso term selection technique constructs a model structure with a nearly minimal number of non-zero terms, and hence with relatively low estimation variances. The algorithm is demonstrated by using it to detect changes in the dynamic stiffness of the human elbow immediately following the onset of a broadband perturbation.

Original languageEnglish (US)
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages22-25
Number of pages4
StatePublished - Dec 1 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: Sep 1 2005Sep 4 2005

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
CountryChina
CityShanghai
Period9/1/059/4/05

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ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

Sanyal, S., Kukreja, S. L., Perreault, E., & Westwick, D. T. (2005). Identification of linear time varying systems using basis pursuit. In Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 (pp. 22-25). [1616332] (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings; Vol. 7 VOLS).