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ISBI
2009
IEEE
13 years 11 months ago
EEG Classification by ICA Source Selection of Laplacian-Filtered Data
We studied the performance of a double-spatial filtering method for classification of single-trial electroencephalography (EEG) data that couples the spherical surface Laplacian...
Claudio Carvalhaes, Marcos Perreau Guimaraes, Loga...
KES
2008
Springer
13 years 4 months ago
On the use of spiking neural network for EEG classification
This paper presents a new classification technique of continuous EEG recordings, based on a network of spiking neurons. Human EEG signals published on the BCI Competition website w...
Piyush Goel, Honghai Liu, David J. Brown, Avijit D...
ICASSP
2008
IEEE
13 years 11 months ago
Mutual information based relevance network analysis: a Parkinson'S disease study
Monitoring the dynamics of networks in the brain is of central importance in normal and disease states. Current methods of detecting networks in the recorded EEG such as correlati...
Pamela Wen-Hsin Lee, Z. Jane Wang, Martin J. McKeo...
NN
2000
Springer
159views Neural Networks» more  NN 2000»
13 years 4 months ago
Independent component analysis for noisy data -- MEG data analysis
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
Shiro Ikeda, Keisuke Toyama
IPPS
2006
IEEE
13 years 11 months ago
Parallel ICA methods for EEG neuroimaging
HiPerSAT, a C++ library and tools, processes EEG data sets with ICA (Independent Component Analysis) methods. HiPerSAT uses BLAS, LAPACK, MPI and OpenMP to achieve a high performa...
D. B. Keith, C. C. Hoge, Robert M. Frank, Allen D....