Quasi-Newton iteration algorithm for ICA and its application in VEP feature extraction / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 45-48, 2006.
Article
in Chinese
| WPRIM
| ID: wpr-309888
ABSTRACT
Some noises still exist in the single-trial averaged visual evoked potentials (VEP), so further extraction of the above results is of significance. Independent component analysis (ICA)can separate the sources from their mixtures and make the output statistically as independent as possible; it can remove noises effectively. In this paper, the principle, experiment analyses and results of ICA based on quasi-Newton iteration rule for VEP feature extraction are introduced, It is compared with the fixed-point FastICA algorithm. The experiment results show that the provided algorithm may reinforce signals effectively and extract distinct P300 from the single-trial averaged VEP. It is of good applicability.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Physiology
/
Algorithms
/
Signal Processing, Computer-Assisted
/
Pattern Recognition, Automated
/
Event-Related Potentials, P300
/
Principal Component Analysis
/
Evoked Potentials, Visual
/
Methods
Type of study:
Prognostic study
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2006
Type:
Article
Similar
MEDLINE
...
LILACS
LIS