@inproceedings{06fd8ade7b5347a7b77afd3adb7661cb,
title = "L{\'e}vy Firefly Algorithms Applied to Improve Sequential Adaptive Processing for Fetal Electrocardiograms (FECGs)",
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 L{\'e}vy 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.",
author = "Jenkins, {W. K.} and M. Hussain",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 ; Conference date: 31-10-2021 Through 03-11-2021",
year = "2021",
doi = "10.1109/IEEECONF53345.2021.9723113",
language = "English (US)",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
publisher = "IEEE Computer Society",
pages = "270--273",
editor = "Matthews, {Michael B.}",
booktitle = "55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021",
address = "United States",
}