Sub-band adaptive filtering method for electroencephalography/event related potential signal using nature inspired optimisation techniques

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.