Lévy Firefly Algorithms Applied to Improve Sequential Adaptive Processing for Fetal Electrocardiograms (FECGs)

W. K. Jenkins, M. Hussain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Previously published results demonstrated that a sequential combination of adaptive linear prediction (LPC), adaptive noise cancellation (ANC), and adaptive comb filtering (CF) can effectively remove maternal interference from noninvasive fetal ECGs. More recent research results have verified that the bio-inspired Lévy Flight Firefly Algorithm (LFFA) can be effectively applied to many different forms of linear and non-linear adaptive filter structures, including low sensitivity IIR adaptive structures that could not be used with steepest descent adaptive algorithms due to their multimodal characteristics. This paper presents results obtained when using the LFFA algorithm in various stages of the FECG sequential combination processing.

Original languageEnglish (US)
Title of host publication55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages270-273
Number of pages4
ISBN (Electronic)9781665458283
DOIs
StatePublished - 2021
Event55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 - Virtual, Pacific Grove, United States
Duration: Oct 31 2021Nov 3 2021

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2021-October
ISSN (Print)1058-6393

Conference

Conference55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021
Country/TerritoryUnited States
CityVirtual, Pacific Grove
Period10/31/2111/3/21

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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