Name
Abstract | ||
|---|---|---|
Transient visual evoked potentials (EPs) are very small variations of the electroencephalogram (EEG) in response to the application of light stimuli. Because of their small amplitudes compared to those of the on-going EEG, signal extraction methods are necessary to estimate their waveforms. In order to develop improved estimation schemes an engineering model is proposed that accounts for most of the observed effects. This model includes the consideration of the information available from the EEG preceding every onset of a sensory stimulus as basis of signal enhancement by adaptive processing. System identification techniques can be applied to test the model structure and to specify its parameters. Several approaches and first results are discussed. |
Year | DOI | Venue |
|---|---|---|
1984 | 10.1109/ICASSP.1984.1172700 | Acoustics, Speech, and Signal Processing, IEEE International Conference ICASSP '84. |
Keywords | Field | DocType |
low pass filters,system identification,white noise,noise reduction,finite impulse response filter,electroencephalography,band pass filters,digital filters | Noise reduction,Noise (signal processing),Pattern recognition,Linear filter,Computer science,White noise,Speech recognition,Evoked potential,Artificial intelligence,Adaptive filter,System identification,Electroencephalography | Conference |
Volume | Citations | PageRank |
9 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rauner, H. | 1 | 0 | 0.34 |
| Werner Wolf | 2 | 39 | 10.18 |
| Ulrich Appel | 3 | 64 | 22.70 |