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Robust Fuzzy-based Data-Selective Affine Projection Algorithm

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

2 Scopus citations

Abstract

This paper presents a fuzzy-based approach to determine a threshold during the data selection process systematically. This makes the conventional data-selective affine projection algorithm (DSAP) robust to the impulse noise. In addition, an error-weighting vector is proposed to enhance our algorithm's robustness further. Simulation results confirmed that our proposed method ultimately improves stability, tracking ability, and robustness while reducing the weight-updating rate in the case of impulse noise presented.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages87-88
Number of pages2
ISBN (Electronic)9781665470506
DOIs
StatePublished - 2022
Event2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, Taiwan
Duration: 6 Jul 20228 Jul 2022

Publication series

NameProceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

Conference

Conference2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Country/TerritoryTaiwan
CityTaipei
Period6/07/228/07/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • affine projection algorithm (APA)
  • data selective
  • fuzzy
  • impulse noise

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