Open AccessSub‐band adaptive filtering method for electroencephalography/event related potential signal using nature inspired optimisation techniques
Author(s) -
Ahirwal Mitul Kumar,
Kumar Anil,
Singh Girish Kumar
Publication year - 2015
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2015.0048
Subject(s) - differential evolution , cuckoo search , adaptive filter , signal (programming language) , computer science , electroencephalography , decimation , genetic algorithm , artificial intelligence , event (particle physics) , pattern recognition (psychology) , particle swarm optimization , algorithm , machine learning , filter (signal processing) , computer vision , physics , biology , quantum mechanics , neuroscience , programming language
In this study, applied research based on sub‐band adaptive filtering (SAF) of electroencephalography/event related potential signal has been conducted. Noisy co‐variants of event related potential signals are filtered through sub‐band adaptive filters (AFs). SAF with evolutionary techniques (ETs) has been attempted first time. Five ETs, such as particles swarm optimisation, artificial bee colony, cuckoo optimisation algorithm, genetic algorithm, and differential evolution with their variants have been employed for optimisation of SAF. Average computational time and shape measures the difference of ET‐based sub‐AFs have been improved by decimation in sub‐bands before adaptive filtering.