Using time-dependent neural networks for EEG classification
- 1 December 2000
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Rehabilitation Engineering
- Vol. 8 (4) , 457-463
- https://doi.org/10.1109/86.895948
Abstract
This paper compares two different topologies of neural networks. They are used to classify single trial electroencephalograph (EEG) data from a brain-computer interface (BCI). A short introduction to time series classification is given, and the used classifiers are described. Standard multilayer perceptrons (MLPs) are used as a standard method for classification. They are compared to finite impulse response (FIR) MLPs, which use FIR filters instead of static weights to allow temporal processing inside the classifier. A theoretical comparison of the two architectures is presented. The results of a BCI experiment with three different subjects are given and discussed. These results demonstrate the higher performance of the FIR MLP compared with the standard MLP.Keywords
This publication has 10 references indexed in Scilit:
- Time series classification using adaptive dynamic targetsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parametersIEEE Transactions on Rehabilitation Engineering, 1998
- EEG-based discrimination between imagination of right and left hand movementElectroencephalography and Clinical Neurophysiology, 1997
- A new method for self-regulation of slow cortical potentials in a timed paradigm.Applied Psychophysiology and Biofeedback, 1997
- Adaptive Autoregressive Modeling used for Single-trial EEG Classification - Verwendung eines Adaptiven Autoregressiven Modells für die Klassifikation von Einzeltrial-EEG-DatenBiomedizinische Technik/Biomedical Engineering, 1997
- Multichannel EEG-based brain-computer communicationElectroencephalography and Clinical Neurophysiology, 1994
- FIR and IIR Synapses, a New Neural Network Architecture for Time Series ModelingNeural Computation, 1991
- Modular Construction of Time-Delay Neural Networks for Speech RecognitionNeural Computation, 1989
- Parallel Distributed ProcessingPublished by MIT Press ,1986
- Toward Direct Brain-Computer CommunicationAnnual Review of Biophysics and Bioengineering, 1973