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NN
2000
Springer
159views Neural Networks» more  NN 2000»
13 years 5 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
ISBI
2009
IEEE
14 years 4 days 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...
ICASSP
2010
IEEE
13 years 5 days ago
Temporally constrained SCA with applications to EEG data
In this paper we propose an iterative algorithm for solving the problem of extracting a sparse source signal when a reference signal for the desired source signal is available. In...
Nasser Mourad, James P. Reilly, Gary Hasey, Duncan...
NIPS
1997
13 years 6 months ago
Extended ICA Removes Artifacts from Electroencephalographic Recordings
Severe contamination of electroencephalographic (EEG) activity by eye movements, blinks, muscle, heart and line noise is a serious problem for EEG interpretation and analysis. Rej...
Tzyy-Ping Jung, Colin Humphries, Te-Won Lee, Scott...
HCI
2009
13 years 3 months ago
Mind-Mirror: EEG-Guided Image Evolution
Abstract. We propose a brain-computer interface (BCI) system for evolving images in realtime based on subject feedback derived from electroencephalography (EEG). The goal of this s...
Nima Bigdely Shamlo, Scott Makeig