A Novel Bayesian Filtering Method for Systems with Quantized Output Data

Ricardo Albornoz, Rodrigo Carvajal, Juan C. Aguero

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

2 Scopus citations

Abstract

In this paper we develop a novel scheme for state estimation of discrete-time linear time-invariant systems with quantized output data. We take a Bayesian approach, therefore, we describe the behavior of the a posteriori probability density function of the state. The difficulty of this problem lies in the probability function of the measurable output given the state, which we approach through an approximation by a Gaussian sum, that naturally leads to a Gaussian sum for the a posteriori density function.

Original languageEnglish
Title of host publicationIEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728131856
DOIs
StatePublished - Nov 2019
Externally publishedYes
Event2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019 - Valparaiso, Chile
Duration: 13 Nov 201927 Nov 2019

Publication series

NameIEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019

Conference

Conference2019 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019
Country/TerritoryChile
CityValparaiso
Period13/11/1927/11/19

Keywords

  • Gaussian sum approximation
  • Quantized data
  • State estimation

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