Identification of a class of signals imbedded in high measurement noise

Kyung Joo, Tamal Bose

Research output: Contribution to journalArticle

Abstract

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
Volume330
Issue number6
DOIs
StatePublished - Nov 1993
Externally publishedYes

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Identification of a class of signals imbedded in high measurement noise'. Together they form a unique fingerprint.

  • Cite this