Robust system‐parameter identification: The influence functional approach

Michael S. Asato, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The influence functional, developed by Martin and Yohai, is an asymptotic robustness measure of a parameter estimate's sensitivity to the infinitesimal occurrence of correlated outlier contamination of a measurement sequence. Here, the usefulness of the influence functional as a tool for characterizing estimator robustness in system parameter identification is explored. In particular, this utility is illustrated by examining the influence functional as a measure of robustness for the choice of the error‐shaping function in the correlation or instrumental variables approach to system parameter identification.

Original languageEnglish (US)
Pages (from-to)223-237
Number of pages15
JournalInternational Journal of Robust and Nonlinear Control
Issue number3
StatePublished - Oct 1992

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • General Chemical Engineering
  • Biomedical Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


  • Influence functions
  • Outliers
  • Robustness
  • System identification


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