“Non-stationarities are ubiquitous in EEG signals. They are especially apparent in the use of EEG-based brain-computer interfaces (BCIs): (a) in the differences between the initial calibration measurement and the online operation of a BCI, or (b) caused by changes in the subject’s brain processes during an experiment (e.g. due to fatigue, change of task involvement, etc).”
“Wavelets are mathematical functions that cut up data into different frequency components, and then study each component with a resolution matched to its scale. They have advantages over traditional Fourier methods in analyzing physical situations where the signal contains discontinuities and sharp spikes.”
Copyright
o Amara Graps, 1995-2004
o 1995 by the Institute of Electrical and Electronics Engineers, Inc
The original version of this work appears in IEEE Computational Science and Engineering, Summer 1995, vol. 2, num. 2, published by the IEEE Computer Society
Biometrics Computational Neuroscience CPG LFP Noise Machine Learning Sparse neurons Wavelets neural recordings Information Theory Modelling Dimensionality Reduction Neural Networks Clustering Statistical Analysis Neurophysiology Brain Interfaces Spike Sorting Brain Research
WP Cumulus Flash tag cloud by Roy Tanck requires Flash Player 9 or better.
Neuroinformatics news IEEE Spectrum Biomedical
Neurobot via RSS