Identification of a class of signals imbedded in high measurement noise

Kyung Joo, Tamal Bose

Research output: Contribution to journalArticlepeer-review


The Kalman filtering algorithm is used to identify a class of signals imbedded in high amplitude measurement noise. The considered class of signals is first modeled empirically as a nonlinear equation. The equation is then linearized and formulated as a Kalman filtering state estimation problem. Computer simulations yield excellent results for a variety of examples, a couple of which are presented in this paper.

Original languageEnglish (US)
Pages (from-to)995-1003
Number of pages9
JournalJournal of the Franklin Institute
Issue number6
StatePublished - Nov 1993
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications
  • Applied Mathematics


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