BibTex format
@article{Hemakom:2016:10.1098/rsta.2015.0199,
author = {Hemakom, A and Goverdovsky, V and Looney, D and Mandic, DP},
doi = {10.1098/rsta.2015.0199},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences},
title = {Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications},
url = {http://dx.doi.org/10.1098/rsta.2015.0199},
volume = {374},
year = {2016}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - An extension to multivariate empirical mode decomposition (MEMD), termed adaptive-projection intrinsically transformed MEMD (APIT-MEMD), is proposed to cater for power imbalances and inter-channel correlations in real-world multichannel data. It is shown that the APIT-MEMD exhibits similar or better performance than MEMD for a large number of projection vectors, whereas it outperforms MEMD for the critical case of a small number of projection vectors within the sifting algorithm. We also employ the noise-assisted APIT-MEMD within our proposed intrinsic multiscale analysis framework and illustrate the advantages of such an approach in notoriously noise-dominated cooperative brain–computer interface (BCI) based on the steady-state visual evoked potentials and the P300 responses. Finally, we show that for a joint cognitive BCI task, the proposed intrinsic multiscale analysis framework improves system performance in terms of the information transfer rate.
AU - Hemakom,A
AU - Goverdovsky,V
AU - Looney,D
AU - Mandic,DP
DO - 10.1098/rsta.2015.0199
PY - 2016///
SN - 1364-503X
TI - Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications
T2 - Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences
UR - http://dx.doi.org/10.1098/rsta.2015.0199
UR - http://hdl.handle.net/10044/1/43150
VL - 374
ER -